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A biomimetic sperm selection device for routine sperm selection

January 16, 2026August 27, 2024 by CadWorks3DAdmin

Academic Article

A biomimetic sperm selection device for routine sperm selection

by Steven A. Vasilescu, Dale M. Goss, Kathryn H. Gurner, Rebecca L. Kelley, Maria Mazi, Fabrice K. De Bond, Jennifer Lorimer, Fabrizzio Horta, Farin Y. Parast, David K. Gardner, Reza Nosrati and Majid E. Warkiani

Abstract

Research question: Can a biomimetic microfluidic sperm sorter isolate motile sperm while minimizing DNA damage in comparison with density gradient centrifugation (DGC)?

Design: This was a two-phase study of 61 men, consisting of a proof-of-concept study with 21 donated semen samples in a university research laboratory, followed by a diagnostic andrology study with 40 consenting patients who presented at a fertility clinic for semen diagnostics. Each sample was split to perform DGC and microfluidic sperm selection (one-step sperm selection with 15 min of incubation) side-by-side. Outcomes evaluated included concentration, progressive motility, and DNA fragmentation index (DFI) of raw semen, and sperm isolated using DGC and the microfluidic device. Results were analysed using Friedman’s test for non-parametric data (significant when P < 0.05). DFI values were assessed by sperm chromatin dispersion assay.

Results: Sperm isolated using DGC and the microfluidic device showed improved DFI values and motility compared with the raw semen sample in both cohorts. However, the microfluidic device was significantly better than DGC at reducing DFI values in both the proof-of-concept study (P = 0.012) and the diagnostic andrology study (P < 0.001). Progressive motility was significantly higher for sperm isolated using the microfluidic device in the proof-of-concept study (P = 0.0061) but not the diagnostic andrology study. Sperm concentration was significantly lower for samples isolated using the microfluidic device compared with DGC for both cohorts (P < 0.001).

Conclusion: Channel-based biomimetic sperm selection can passively select motile sperm with low DNA fragmentation. When compared with DGC, this method isolates fewer sperm but with a higher proportion of progressively motile cells and greater DNA integrity.

Keywords: sperm selection; microfluidics; density gradient centrifugation; DNA fragmentation

We kindly thank the researchers at University of Technology Sydney for this collaboration, and for sharing the results obtained with their system.

Introduction

Infertility affects approximately 15% of couples worldwide, with approximately 55% of those having a male contributing factor (WHO, 2023). The use of medical intervention in the form of assisted reproductive technology (ART) is growing annually, yet the success rate of assisted reproduction cycles per embryo transfer has stagnated at approximately 33% per cycle, and the proportion of live births has plateaued at approximately 26% per cycle over the last two decades (Adamson et al., 2018; Nosrati et al., 2017). Many factors play a role in the success of a cycle, and one crucial aspect of all methods is sperm selection, where sperm quality can have a direct effect on outcomes (Donnelly et al., 1998; Tandara et al., 2014).

An increased DNA fragmentation index (DFI) is prevalent in infertile men and in men aged >40 years, and is even higher in those with abnormalities in conventional semen parameters such as motility, morphology and concentration (Moskovtsev et al., 2009). Furthermore, couples with idiopathic infertility and recurrent pregnancy loss, where conventional sperm parameters lie within healthy norms, show a higher incidence of DNA fragmentation (Esteves et al., 2021; Tan et al., 2019). Studies have shown, using the sperm chromatin structure assay (SCSA), that approximately 28% of men from infertile couples have moderate (>20%) or high (>30%) DFI values (Erenpreiss et al., 2008), while in couples with ‘unexplained infertility’, the percentage of men with moderate-to-high DFI values is 26.1% (Oleszczuk et al., 2013); this incidence increases with age. High levels of DNA fragmentation (>30%) in sperm have been shown to increase the risk factors involved in IVF by reducing embryo quality, lowering implantation rates, and increasing the chance of miscarriage up to 3.9 times that of patients using sperm with low DFI values (Borges Jr et al., 2019; Duran et al., 2002; Robinson et al., 2012; Sedó et al., 2017).

Density gradient centrifugation (DGC) and swim-up methods are the most common techniques used for processing semen samples and selecting sperm for use in assisted reproduction. However, in recent studies, these methods have been implicated in the increase in sperm DNA fragmentation, purportedly due to the generation of reactive oxygen species (Aitken et al., 2014; Muratori et al., 2016; Stevanato et al., 2008). As it is not yet possible to assess sperm DNA fragmentation non-invasively prior to use in IVF or intracytoplasmic sperm injection (ICSI), innovative methods are required to select and isolate sperm with low DFI values for use in IVF or ICSI at appropriate concentrations. There have been several attempts to create an alternative sperm selection method, including the MACS ART Annexin V System (Miltenyi Biotec, Australia), Physiological Intracytoplasmic Sperm Injection dish (CooperSurgical, USA) and the DGC-zeta potential method (Hasanen et al., 2020; Karimi et al., 2020), and many innovative approaches have originated from the application of microfluidics (Keskin et al., 2022; Quinn et al., 2018; Suh et al., 2006; Villeneuve et al., 2023).

Microfluidic devices have been developed to select high-quality sperm using flow or sperm migration behaviour, without the need for active input such as centrifugation or electrophoretic fields. These devices purport to reduce exposure to oxidative stress and subsequent DNA fragmentation (Dadkhah et al., 2023; Nosrati et al., 2014; Simchi et al., 2021). However, the clinical translation and adoption of many of these technologies have been limited (Nosrati, 2022), largely due to their complexity of workflow, operational instability and/or inconsistent results. Without an intuitive user interface, many devices have not seen further side-by-side clinical testing to evaluate their performance in the hands of clinical scientists. An effective sperm selection platform must not only provide high-quality sperm in a timely manner, but must also be simple to use and consistent in its performance over a range of sperm motility levels (Nosrati et al., 2017; Rappa et al., 2016).

This study aimed to test a novel microfluidic channel-based biomimetic sperm selection device against the gold standard, DGC, to isolate motile sperm from a range of semen samples. This radial microfluidic device selects sperm based on their preference to follow boundaries in a static fluid environment mimicking the geometries of the female reproductive tract (Figure 1). This device consists of a radial array of hundreds of media-filled channels, whereby semen interfaces with the entrances to these channels, selecting sperm by their ability to traverse corners, boundaries and troughs, mimicking the endometrium and epithelium of the oviduct, towards a central outlet port. It was postulated, based on the authors’ previous insights into motile sperm behaviour in confined geometries and channels (Eamer et al., 2016; Nosrati et al., 2014; Vasilescu et al., 2023), that the boundary-following tendencies of sperm will lead to the isolation of a sample with high motility and low DFI values.

Figure 1. Overview of the microfluidic device selection process. (A) Schematic representation of the stages of operation of the microfluidic device. (i) Loading the device with media from the centre outlet, (ii) raw semen is then loaded into the outer inlet to create the semen–media interface, (iii) the centre outlet is sealed with tape and the device is left untouched for 15 min, and (iv) the tape is removed, and isolated and washed sperm are aspirated from the centre well ready for assessment and use. (B) A representative image of the microfluidic sperm selection device pre-loading with gamete buffer labelled with the key stages of device operation. Red sperm and round cells indicate non-motile cells and debris, blue sperm represent low motility sperm, and green sperm represent highly motile sperm.

Materials and Methods

Device fabrication

The microfluidic device contained a semen reservoir designed to hold 1 ml of raw semen. The semen reservoir was connected to a sperm trapping and collection area via a radial array of microchannels (Figure 1 and Supplementary Video 1). Microfluidic devices were fabricated via a moulding process using three-dimensional-printed moulds adapted from Shrestha et al. (2019). The moulds were fabricated using a digital light processing three-dimensional printer (MiiCraft Ultra 50; MiiCraft, Taiwan) and a photopolymer resin (BV-007; Creative CADWorks, Canada). The microfluidic device design was created in Solidworks 2019 (SolidWorks Corp., USA) and sliced at 25 µm. The device was made from two separate moulds comprising the top and bottom layers of the device. After printing, each mould was washed with isopropanol, and dried with an air gun to remove any excess liquid resin from the microchannels. Washing with isopropanol was repeated three times, and the moulds were cured in an ultraviolet curing box for 2 min prior to being placed in a 70% ethanol bath for 2 h. The moulds were subsequently dried with an air gun and treated with oxygen plasma (Basic Plasma Cleaner PDC-002; Harrick Plasma, USA) for 2 min, followed by salinization using trichloro (1H, 1H, 2H-perfluoro-octyl) silane (Sigma-Aldrich, USA) in a desiccator under vacuum for 1.5 h. The moulds were cast with polydimethylsiloxane (PDMS) (Sylgard 184; Dow Corning, USA), a non-toxic polymer (Colucci et al., 2018), prepared using a mixture of base and curing agents in a ratio of 1:10. The mixture was degassed to remove all bubbles before casting on to the moulds and cured in a hot air oven (75°C) for 2 h. After curing, the PDMS layers were gently peeled off the moulds; holes were punched for the semen inlet, overflow reservoir and sperm collection outlet; and then oxygen plasma treatment was used for bonding.

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Semen collection and patient demographics

Human semen samples were obtained through ejaculation after 2–4 days of sexual abstinence as recommended by the World Health Organization (WHO, 2021). Raw semen samples were kept on a shaker at room temperature for 15–20 min to allow for full liquefaction. The proof-of-concept study was approved by Monash University Human Research Ethics Committee (ID 26713, approval date 9 December 2020), and the diagnostic andrology study was approved by Melbourne IVF Human Research Ethics Committee (88-22-MIVF, approved 10 May 2022). Samples were obtained from donors for the proof-of-concept study, and from patients presenting for semen analysis for the diagnostic andrology study. Specific age information is not available for the proof-of-concept study, but these donors were students between the ages of 18 and 24 years. Patients in the diagnostic andrology study were between 26 and 54 years of age (mean 36.3 years) (Table 1). Differences were found between the two populations; specifically, the average semen volume was greater in the diagnostic andrology group (P = 0.012). All participants provided informed consent for their inclusion as completely de-identified participants in this study.

The exclusion criteria for both groups were azoospermia, severe oligozoospermia (<1 million/ml sperm concentration) or absolute asthenozoospermia (0% motile sperm). Additionally, participants providing samples <1 ml volume, and those designated for cryopreservation in the diagnostic andrology study were excluded. Finally, patients who reported active infection or had samples with signs of active infection or inflammation (presence of many round cells) were also excluded.

Experimental procedure

In total, 61 patient and donor samples were processed across two separate studies. Although the two studies were performed at different sites and by different personnel (research embryologists in the proof-of-concept study, and clinical embryologists and andrologists in the diagnostic andrology study), both studies followed the same approach whereby all samples were split into three groups – raw semen, and sperm isolated using DGC and the microfluidic device – and processed in parallel. In cases where the semen volume was <2.1 ml, the unprocessed sample was diluted to 2.1 ml in G-MOPS Plus medium (Vitrolife, Sweden) to enable parallelized processing (nine of 61 samples), as 1 ml was required for both DGC and the microfluidic device, and 100 μl of raw semen was required as the control.

To perform sperm selection with the microfluidic device (see Figure 1Ai–iv), the device was pre-filled with Sydney IVF Gamete Buffer (Cook Medical, USA) at room temperature for the proof-of-concept study, or G-MOPS Plus medium (Vitrolife) for the diagnostic andrology study by injecting 1.5 ml through the central outlet using a filled 3-ml plastic syringe (Becton, Dickinson and Company, USA). These two media are the sperm processing buffers used routinely at each site. A strip of AS-110 acrylic medical grade adhesive tape (AR Care Ltd, UK) was placed over the central outlet to create an airtight seal for channel stability, preventing undesired flow of fluids. The device was then left for 5–10 min on a warm plate (37°C) to equilibrate. Next, 1 ml of liquified semen was injected into the device using a 1-ml plastic syringe, and the device was left undisturbed at 37°C (on a heated stage) for 15 min. After incubation, the tape was removed, and 200 µl of sperm suspended in media was collected from the central outlet using a 200-µl pipette and transferred to a final tube for analysis. The migration of sperm through various stages of the device can be seen in Supplementary Video 1.

In the proof-of-concept study, DGC was performed using Sydney IVF 80/40 gradients (Cook Medical, USA). First, 1 ml of 40% gradient was placed in a conical 15-ml tube and underlaid with 80% gradient. Next, 1 ml of semen was layered carefully on top of the 40% density gradient layer using a 1-ml pipette. The solution was centrifuged at 500 x g for 10 min, and the pellet was aspirated directly from the bottom of the tube by collecting 200 µl of fluid. The pellet was resuspended in 3 ml of Sydney IVF Gamete Buffer, centrifuged for 5 min at 500 x g, the subsequent pellet was aspirated from the bottom by collecting 200 µl of sperm in Sydney IVF Gamete Buffer, followed by transfer to a final tube for analysis.

In the diagnostic andrology study, DGC was performed using PureSperm 80/40 gradient (Nidacon, Sweden). With aseptic techniques, 1 ml of 40% PureSperm density gradient was pipetted into a 15-ml conical tube. Using a new pipette, 1 ml of PureSperm 80% density gradient was underlaid carefully to avoid mixing the two layers. After layering 1 ml of semen sample carefully on to the gradient, without disrupting the density gradient, the gradient tube was centrifuged at 500 x g for 10 min. After centrifugation, the gradient tube was removed carefully from the centrifuge to avoid mixing the layers. The pellet was removed using a clean Pasteur pipette, transferred to a clean 15-ml blue-capped Falcon conical tube containing 8 ml of G-MOPS Plus media, and centrifuged at 500 x g for 5 min. Finally, the pellet was transferred to the final tube with 200 µl of G-MOPS Plus media. The same media were used at both sites for both the microfluidic device and the wash centrifugation step of DGC processing.

Sperm chromatin dispersion assay and motility analysis

DFI was assessed with a modified sperm chromatin dispersion (SCD) test, using the HT-HSG2 kit (Halotech DNA, Spain) as reported previously (Vasilescu et al., 2021). Sperm DNA fragmentation was obtained for the raw semen sample and for sperm isolated using the microfluidic device and DGC. Briefly, 80 μl of sperm suspension was added to 80 μl of pre-aliquoted warmed agarose in a 2-ml Eppendorf tube (Eppendorf, Germany). Thereafter, 10 μl of the semen–agarose mixture was pipetted on to pre-coated slides and covered with a coverslip. The slides were placed on a cold plate at 4°C for 5 min to allow the agarose to set. The coverslips were then slid gently off the slides, and the slides were immediately immersed horizontally in an acid solution and incubated for 7 min with a new coverslip placed on top. Next, slides were gently tilted vertically to allow the acid solution to run off. Slides were then immersed horizontally in the lysing solution for 20 min, washed with distilled water for 5 min, and then dehydrated in increasing concentrations of ethanol (70% and 100%) for 2 min each, air-dried, and stored at room temperature in the dark. Sperm were categorized into one of five groups during counting following SCD: (i) sperm with a halo width equal to or larger than the minor diameter of the core; (ii) sperm with a small halo, similar to or smaller than one-third of the minor diameter of the core; (iii) sperm with a medium halo, between the size of small and large halos from Groups i or ii; (iv) sperm with no halo; and (v) sperm with a degraded halo. Sperm with a small, degraded or absent halo contained fragmented DNA (Groups ii, iv and v). DFI values were recorded as the percentage of sperm cells with fragmented DNA. Three hundred sperm were counted per sample, and each sample was counted twice; counts were considered to be accurate if the difference in DFI value was within 5%. Seven samples were removed from the DFI results due to inadequate staining for reliable counting.

Motility and concentration for each group were assessed using the WHO guidelines (WHO, 2021), Sperm were classified as either progressively motile, non-progressive or immotile, with a minimum of 200 sperm assessed for motility. This method for assessing sperm concentration and motility was performed consistently at both sites to ensure accurate comparisons and minimize confounding variables. For assessing sperm concentration, a 1:10 dilution of raw semen with gamete buffer (Sydney IVF Gamete Buffer for the proof-of-concept study; G-MOPS Plus for the diagnostic andrology study) was required for 10 of the 50 samples. Concentration was assessed under a phase contrast microscope (Olympus CKX53; Evident, Japan) using a haemocytometer at 200 X, and a duplicate count was performed between two scientists, with the counts repeated if the difference between the two counts exceeded 5%. All sperm were counted in the four corner squares and the centre square, and the total number of sperm was multiplied by the dilution factor for each sample where applicable. For motility assessment, samples were assessed under similar conditions after liquefaction of semen within 1 h of collection, and immediately after processing with DGC and the microfluidic device. Sperm were also assessed by two scientists, and the assessment was repeated if the difference between counts exceeded 5%.

Statistical analysis

All statistical analyses were performed using GraphPad Prism 6.0 (GraphPad Software, USA). The normality of distribution was assessed using the Shapiro–Wilk test. The significance of differences between values for demographic data (Table 1) was assessed using the Mann–Whitney U-test. Experimental analysis (Table 2) was assessed using Friedman’s test for non-parametric data to account for repeated measures from the same patient after Dunn’s multiple comparisons test to correct for multiple comparisons. Pearson’s correlation test was performed to assess the linear relationship between DFI values of sperm isolated using the microfluidic device and DGC. Pearson’s correlation coefficient (r-value) was calculated to quantify the strength and direction of the linear association between these two variables. Data are presented as median and interquartile range (IQR) and mean ± SEM. P < 0.05 was considered to indicate significance.

Table 2. Sperm assessments for raw semen, and sperm isolated using density gradient centrifugation and the biomimetic microfluidic device. Data presented as median (interquartile range) and mean ± SEM. Data were assessed using Friedman's test for non-parametric data after Dunn's multiple comparisons test. Bold type indicates a significant result. a (superscript): Compared with DGC. b (superscript): Compared with sperm isolated using the microfluidic device. DGC, density gradient centrifugation.

Results

The radial microfluidic device selects sperm based on their preference to follow boundaries in a confined space within a static fluid environment, as shown in Figure 1Bii and iii. Table 2 shows the sperm quality metric values for DFI, motility and concentration for the three groups processed in parallel (raw semen, DGC and microfluidic device) for both the proof-of-concept study and the diagnostic andrology study.

Proof-of-concept study

The proof-of-concept study showed that sperm isolated using the microfluidic device had significantly lower median DFI values compared with sperm isolated using DGC (0.7% versus 4.1% respectively, P = 0.0012) (Figure 2A). Sperm isolated using the microfluidic device also showed consistently lower DFI values than sperm isolated using DGC in all 21 samples, as the distribution of DFI values compared between split samples shows in Figure 2B. There is a positive correlation with a slope <1 and r = 0.81, showing that increases in DFI values for sperm isolated using DGC were accompanied by increases in DFI values for sperm isolated using the microfluidic device, although the latter increased at a lower rate. Sperm isolated using the microfluidic device yielded a 92.2% decrease in the average DFI value (calculated as the percentage reduction in DFI value compared with the raw semen sample), outperforming DGC which reduced the average DFI value by 57.4% (P < 0.0001). A significantly higher percentage of sperm isolated using the microfluidic device were progressively motile compared with sperm isolated using DGC (92.8% versus 77.7%, respectively; P = 0.0061), with the former showing improvement in 20 of 21 samples (Supplementary Figure 1 and Figure 2C). This represents a two-fold average increase in progressive motility in sperm isolated using the microfluidic device compared with DGC (61.1% for microfluidic device, 30.5% for DGC). Microfluidic selection reduced sperm concentration significantly compared with DGC selection (2.9 × 10⁶ sperm/ml versus 61.0 × 10⁶ sperm/ml, respectively; P < 0.0001) (Figure 2D). The concentration difference between raw semen and sperm isolated using DGC was not significant. Each selection method resulted in a 200-µl suspension of sperm in gamete buffer. Results for before and after microfluidic device processing can be seen in Figure 2E and F, respectively.

Diagnostic andrology study

The diagnostic andrology study repeated trends observed in the proof-of-concept study in a population of patients presenting for infertility. Of the 33 samples processed for DFI values, the sperm isolated using the microfluidic device had significantly lower median DFI values compared with sperm isolated using DGC (1.0% versus 3.9%, respectively; P < 0.001), and a reduction was seen in 30 of 33 samples assessed (Supplementary Figure 2 and Figure 3A,B). Although the DFI values of sperm isolated using the microfluidic device and DGC were significantly reduced compared with the raw semen sample (P < 0.0001 and P = 0.0022, respectively), use of the microfluidic device yielded an 82.9% average improvement (calculated as the percentage reduction in DFI value compared with the raw semen sample), significantly outperforming DGC (P < 0.001) which reduced the DFI value by an average of 44.4%. Furthermore, irrespective of the DFI value of raw semen, DFI values of sperm isolated using the microfluidic device were consistently reduced to <10%; in comparison, the use of DGC resulted in 10 of 33 samples with DFI values >10% (Figure 3B). Although a weak positive correlation was found, with a slope < 1 and r = 0.44, a less pronounced increase in the DFI values of sperm isolated using the microfluidic device was observed compared with sperm isolated using DGC. Unlike the proof-of-concept study, there was no significant difference in progressive motility of sperm isolated using the microfluidic device compared with DGC, and both the microfluidic device and DGC improved progressive motility significantly compared with the raw semen sample (Figure 3C, both P < 0.0001). Furthermore, the sperm concentration reflected similar results as the proof-of-concept study, with samples isolated using the microfluidic device yielding a lower median sperm concentration compared with samples isolated using DGC (2.0 × 10⁶ sperm/ml versus 20.0 × 10⁶ sperm/ml, respectively; P < 0.0001) (Table 2 and Figure 3D).

Site comparison

Results from each site were compared (Supplementary Figures 3A–C), and both progressive motility (P < 0.0001) and concentration (P = 0.0015) of sperm isolated using DGC were significantly lower in the proof-of-concept study compared with the diagnostic andrology study. No other significant differences were observed between the sites.

Discussion

This study demonstrated that passive biomimetic microfluidic channel-based processing of semen, from healthy donors as well as patients attending an IVF clinic for diagnostic andrology, enables the selection of a high proportion of progressively motile sperm with significantly lower DFI values compared with conventional DGC. A biomimetic mode of sperm selection offers consistent results and can be performed with minimal training, with the operation of the microfluidic device requiring only a syringe, a pipette, and a heated stage or incubator to operate the device (Figure 1A,B). During the incubation time, only motile sperm make their way from the semen reservoir down the microchannels via boundary-following behaviour towards the collection chamber, and in doing so, are resuspended in the gamete buffer (Figure 1Aiii). A sharp decrease in height and a gradual reduction in the channel height towards the centre of the device effectively limits the chance for sperm to exit the 200-µL collection zone. Passive sperm selection may also minimize iatrogenic DNA damage by avoiding any centrifugal forces, and selects sperm based on previously reported boundary-following behaviour which correlates with reduced DNA fragmentation (Denissenko et al., 2012; Eamer et al., 2016).

The present research group has tested a similar device against swim-up sperm selection on a smaller cohort of donors, which harnessed MACS ART Annexin V beads (Miltenyi Biotec) and opposing neodymium magnetic plates (AMF Magnetics, Australia) to negatively select apoptotic sperm (Vasilescu et al., 2023). This previous device was more complex in operation, required multiple reagents, was fabricated from a different material (three-dimensional-printed photopolymer resin), and was designed with different internal geometry. The current device uses a simpler, more accessible approach aimed at routine use. To test this microfluidic device, donor samples were used to compare DGC against the microfluidic method of sperm selection, and the latter allowed selection of sperm with higher DNA integrity and progressively motile sperm from this cohort. While conventional semen processing with DGC did result in an average improvement in motility and DFI values compared with unprocessed semen, it did so with a higher level of variability in sperm quality. Specifically, three of 21 samples processed via DGC showed an increase in DFI values, and many samples only showed an incremental reduction (<10%) (Supplementary Figure 1). Conversely, all samples processed with the microfluidic device showed a significant improvement, irrespective of the starting DFI value and motility. The average DFI value of sperm isolated using the microfluidic device was <1%, demonstrating that this method of sperm selection, when applied to motile sperm populations, is effective regardless of the starting DFI value. Similarly, the motility of sperm isolated using the microfluidic device was consistently higher compared with the motility of sperm isolated using DGC (Figure 2C). These results were consistent with previous studies indicating a high level of variance in recovered sperm motility when using DGC (Malvezzi et al., 2014; Muratori et al., 2016).

When performing a study on 40 consenting patients undergoing diagnostic andrology, similar trends were observed. Despite being a more clinically diverse cohort, notable improvements in DFI values were observed in 30 of 33 samples of sperm isolated using the microfluidic device compared with DGC (two samples had identical DFI values for both groups). This consistency highlights the usability and standardization achievable with a biomimetic device. Additionally, although overall improvements in DFI values were observed in sperm isolated using DGC (44.4% average), three samples had increased DFI values, possibly due to the iatrogenic damage caused by centrifugation on particularly susceptible samples, but this would require further investigation (Supplementary Figure 2). This was not observed when using the biomimetic device, which showed an average improvement in DFI values of 82.9%, with only one sample showing a reduction in DFI value <60%. Another noteworthy observation made in both studies was that, although DFI values were reduced in most samples isolated using DGC, the average reductions in DFI values of 57.4% and 44.4% for the proof-of-concept study and diagnostic andrology study, respectively, were inefficient compared with the average reductions observed in the samples isolated using the biomimetic device (92.2% and 82.9%, respectively). Compared with DGC, use of the microfluidic device increases the chance of selecting sperm with high DFI values, and this creates a population of sperm for fertilization which has lower DNA damage and may provide clinical benefit within IVF workflows by reducing the incidence of miscarriage and failed implantation, as suggested in the literature (Borges Jr et al., 2019; Duran et al., 2002; Robinson et al., 2012; Sedó et al., 2017).

The microfluidic device performed consistently between sites for all three key parameters measured (Supplementary Figures 3A–C). Although differences were observed in progressive motility and concentration between the DGC groups, these differences can be attributed to multiple factors, including operator experience between research scientists at the university research laboratory for the proof-of-concept study versus clinical embryologists in the diagnostic andrology study. Although there were differences in the density gradients used at the two sites, both gradients were a 40% and 80% gradient solution combination, and were silane-coated silica-based.

The average DFI values in sperm isolated using DGC vary in the literature, and depend largely on sample populations. Some studies have indicated an increase in total DNA fragmentation (Muratori et al., 2019), and others have suggested an average improvement in DFI values, with a subpopulation of samples experiencing an increase in DFI values or no improvement in DFI values, which is consistent with the results of this study (Rappa et al., 2016; Stevanato et al., 2008). DNA fragmentation in sperm is commonly attributed to oxidative stress, plausibly induced by repetitive centrifugation used in conventional sperm selection methods (Henkel et al., 2005; Hernández-Silva et al., 2021; Nabi et al., 2014). High DNA fragmentation is associated with pregnancy loss in conventional IVF and ICSI, as well as lower implantation rates and a reduction in average embryo quality (Benagiano et al., 2017; Coughlan et al., 2015; Larson-Cook et al., 2003; Robinson et al., 2012). What is perhaps more concerning is that sperm DNA fragmentation has no obvious effect on fertilization, but becomes apparent during blastocyst development by reducing the generation of good-quality blastocysts and ability to achieve successful implantation (Newman et al., 2022; Seli et al., 2004). As a result, the risk of using compromised sperm remains present in clinical practice, and highlights the need for the selection of sperm with high DNA integrity. Importantly, this is of relevance when considering that advanced reproductive age has an increased negative effect on sperm DNA damage (Horta et al., 2020). Furthermore, male ageing has been linked to a significant increase in miscarriage rate, and a decrease in live birth rate, with a larger impact in women of advanced reproductive age (Horta et al., 2019).

A clear limitation of the output of the current microfluidic device, and arguably of microfluidic motility-based sperm selection in general, is the smaller number of sperm isolated when using the microfluidic device when compared with DGC. In conventional IVF, 50,000 sperm are typically required per oocyte, and an average of 10–12 oocytes are harvested per stimulated cycle (Oseguera-López et al., 2019). However, it has been shown that high fertilization and cleavage rates are possible with as few as 2000–4000 sperm per oocyte (Fiorentino et al., 1994). The average number of sperm isolated using the microfluidic device was approximately 720,000, which may be too few for many conventional IVF cases if clinics were to adhere to the requirement of approximately 50,000 motile sperm per oocyte (Li et al., 2018). Logically speaking, sperm selected using passive biomimetic selection, such as the device in this study, may have higher fertilization efficiency than those selected using active measures such as centrifugation; therefore, fewer sperm may be required for conventional IVF, similar to that of in-vivo fertilization whereby only approximately 200 sperm fertilize the oocyte (Chaffey, 2003). Nevertheless, in future prototypes of this biomimetic device, improvement in the yield of motile sperm for high-responder women for whom many oocytes are collected will improve the potential for clinical adoption, as the yield and high selectivity of this device is better suited for ICSI cases which require fewer sperm for insemination, and ICSI is often prescribed for cases where the male partner has a high DFI value. The form factor of the device also enables the adherance of an 18 mm x 36 mm automatic witnessing tag and patient label for seamless clinical integration.

Semen processing using DGC requires several manual interventions during sample handling, each with the potential for human error. Passive devices such as that used in this study, as well as ZyMōt (ZyMōt Fertility, USA) and Lenshooke CA0 (Hamilton Thorne, USA), limit human interaction in semen to sample injection and sperm collection, usually without centrifugation (Shirota et al., 2016). The microfluidic device used in this study, with a simple three-step operation, will reduce the clinical workload while offering a greater reduction in DFI value after processing. While many studies have investigated the impacts of commercialized microfluidic devices, and these have been reviewed systematically (Ferreira Aderaldo et al., 2023), the present biomimetic device takes a different approach to sperm selection by leveraging the boundary-following behaviour of sperm to perform selection, and requiring sperm to travel several millimetres to a collection zone. Reductions in DNA fragmentation and the simplicity of this device are comparable to existing commercial devices such as ZyMōt and LensHooke (Parrella et al., 2019; Hsu et al., 2023), both of which exploit sperm motility via membrane filtration. In a recent study comparing DGC, ZyMōt and LensHooke CA0, Hsu et al. (2023) demonstrated progressively motile sperm counts of 80.6%, 85.6% and 90.8%, respectively, and DFI values of 11.8%, 3.7% and 2.4%, respectively, in normospermic samples (Hsu et al., 2023). Further comparative studies are now required to determine whether the use of a biomimetic device that leverages boundary-following behaviour in sperm will lead to improved outcomes.

This study has several limitations which can be addressed in larger follow-up studies. Firstly, limited access to samples with high DFI values (>25%) prevented a robust testing approach on extreme cases, which are perhaps those which would benefit the most from a reduction in DFI value. Secondly, to prove the clinical usefulness of this approach, clinical outcomes are required when assessing the device on a range of patients, whereby the effect of each sperm selection method on fertilization and embryo development is evaluated thoroughly. Ideally, a randomized controlled trial or sister oocyte study (whereby half the oocytes are inseminated with sperm isolated using conventional methods, and half the oocytes are inseminated with sperm isolated using the microfluidic device) will better display the clinical utility of this microfluidic device in IVF workflows. The prototype in its current format does show utility for ICSI cases, for which lower numbers of high-quality sperm are sufficient. This format suits a side-by-side study for an ICSI cohort, but may not suit an IVF insemination side-by-side comparison with DGC. Thirdly, the method of DNA fragmentation assessment, SCD, only identifies single-stranded DNA breaks, and has limitations in the subjective nature of the assessment. Future studies and validation are needed using SCSA for a more robust assessment of DFI values by detecting double-stranded DNA breaks. SCD is also susceptible to human error and sperm concentration restraints during the preparation and staining of samples, as shown by seven of 40 patients with inadequate staining for SCD assessment in this study. Finally, the current biomimetic prototype does limit the output of sperm by only processing 1 ml of semen, whereas conventional methods process the entire ejaculate. The purpose of this was to enable side-by-side testing against DGC; however, further studies are currently evaluating a larger volume platform capable of processing an entire semen sample to maximize the sperm yield for use in IVF and intrauterine insemination.

This study reports a novel, highly selective biomimetic method for sperm selection in a simple-to-use, single-use chip format for isolating highly motile sperm with minimal DNA fragmentation, without the need for centrifugation or other active mechanisms. Considering the limitations of this study, this proof-of-concept test shows that highly selective, lower output sperm isolation, such as channel-based microfluidic selection in its current form, may prove to be a practical alternative for ICSI cycles if higher motile concentrations for larger oocyte numbers are preferred for conventional IVF. As many patients with high DFI values tend to be prescribed ICSI as a method of fertilization, this device does have the potential to address these cases, considering its ability to reduce DFI values consistently compared with DGC. The novel selectiveness of mimicking the female reproductive system provides a high-quality population of sperm for use in treatments. Clinical studies have now been initiated to validate the proposed benefits of this selection mechanism.

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References

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Evaluation of industrial and consumer 3-D resin printer fabrication of microdevices for quality management of genetic resources in aquatic species

January 16, 2026July 23, 2024 by CadWorks3DAdmin

Academic Article

Evaluation of industrial and consumer 3-D resin printer fabrication of microdevices for quality management of genetic resources in aquatic species

by Seyedmajid Hosseini, Jack C. Koch, Yue Liu, Ignatius Semmes, Isabelina Nahmens, W. Todd Monroe, Jian Xu and Terrence R. Tiersch

Abstract: Aquatic germplasm repositories can play a pivotal role in securing the genetic diversity of natural populations and agriculturally important aquatic species. However, existing technologies for repository development and operation face challenges in terms of accuracy, precision, efficiency, and cost-effectiveness, especially for microdevices used in gamete quality evaluation. Quality management is critical throughout genetic resource protection processes from sample collection to final usage. In this study, we examined the potential of using three-dimensional (3-D) stereolithography resin printing to address these challenges and evaluated the overall capabilities and limitations of a representative industrial 3-D resin printer with a price of US$18,000, a consumer-level printer with a price <US$700, and soft lithography, a conventional microfabrication method. A standardized test object, the Integrated Geometry Sampler (IGS), and a device with application in repository quality management, the Single-piece Sperm Counting Chamber (SSCC), were printed to determine capabilities and evaluate differences in targeted versus printed depths and heights. The IGS design had an array of negative and positive features with dimensions ranging from 1 mm to 0.02 mm in width and depth. The SSCC consisted of grid and wall features to facilitate cell counting. The SSCC was evaluated with polydimethylsiloxane (PDMS) devices cast from a typical photoresist and silicon mold. Fabrication quality was evaluated by optical profilometry for parameters such as dimensional accuracy, precision, and visual morphology. Fabrication time and cost were also evaluated. The precision, reliability, and surface quality of industrial-grade 3-D resin printing were satisfactory for operations requiring depths or heights larger than 0.1 mm due to a low discrepancy between targeted and measured dimensions across a range of 1 mm to 0.1 mm. Meanwhile, consumer-grade printers were suitable for microdevices with depths or heights larger than 0.2 mm. While the performance of either of these printers could be further optimized, their current capabilities, broad availability, low cost of operation, high throughput, and simplicity offer great promise for rapid development and widespread use of standardized microdevices for numerous applications, including gamete quality evaluation and “laboratory-on-a-chip” applications in support of aquatic germplasm repositories.

Keywords: germplasm repository; aquatic species; 3-D resin printing; soft lithography; photolithography; aquaculture industry; genetic resources

We kindly thank the researchers at Louisiana State University for this collaboration, and for sharing the results obtained with their system.

1. Introduction

Throughout history, ensuring the protection of economically important agricultural species has involved the storage, assessment, and distribution of genetic resources. One preservation method for these resources involves placing them in a frozen state, a technique known as cryopreservation. Cryopreserved samples are commonly stored in collections or repositories [[1], [2], [3], [4]]. However, scalable cryopreservation technologies and germplasm repositories are not in place for most aquatic species despite the urgent need to protect the genetic resources that provide the foundation for aquaculture, food security, biomedical research, conservation, and wild fisheries. The genetic resources that support billions of dollars [5] of capture fisheries and human livelihoods are not protected, and the risk and expense of maintaining live animals (rather than frozen samples) hinder the growth of numerous aquatic industries [6]. These risks and expenses can be minimized by developing proprietary or shared (open) hardware devices that are capable of accelerating repository development and aiding in management and processing operations for the protection of genetic resources [7].

The growing climate crisis has exacerbated costs, risks, and needs associated with safeguarding genetic resources of aquatic species around the world. A vast majority of aquatic species that are important for aquaculture, food security, biomedical research, conservation, and wild fisheries are native to low-to-middle income nations where genetic resource protection is not a long-term priority or where equipment and reliable resources are scarce. Policy and long-term agendas must be addressed at scales beyond the individual. With the rapid growth of open-additive manufacturing, sustainable capabilities and resources can become widely accessible, and can be developed, customized, and fabricated by anyone.

Reliable tools and devices are essential for safeguarding genetic resources because they enable critical processing and quality management (QM) steps from sample collection to final usage. A relevant example is Bangladesh which is home to >600 species of freshwater and marine fishes. These fishes provide a primary protein source to sustain a growing human population of 171 million. Land use changes, introduced species, overharvesting, and other anthropogenic effects have strained open-water fisheries, and the country now relies heavily on farmed fishes (i.e., aquaculture) [8] with a narrowing gene pool. Cryopreservation is essential for preserving quality genetics, sustaining livelihoods, and ensuring sustainable production and improvement of aquatic species in Bangladesh and abroad. There are ongoing efforts to develop germplasm repositories for aquatic species in Bangladesh [8,9], but access to reliable tools and supplies, especially for quality management, are major roadblocks to these efforts. These same urgent needs for protection of aquatic genetic resources exist throughout the world, including the United States.

Capability needs for cryopreservation are driven by processing steps such as germplasm collection (e.g., sperm, eggs, early life stages, cells), quality evaluation, cryopreservation, storage, thawing, and final usage. Sample quality is of critical importance as the samples frozen today may be stored for decades and processing of poor quality samples wastes time and resources today and in the future. Quality management is a major driving force behind the need to develop novel, customizable, and accessible microdevices (e.g., micromixers [10], microfluidic lab-on-a-chip systems [11], and micro-separators [12]) to assist in safeguarding aquatic genetic resources. Such microdevices need to be versatile and practical for activities centered around germplasm QM, including quality planning, quality assurance (QA, process oriented), quality control (QC, product oriented), quality evaluation, and quality improvement.

There are existing devices to accomplish these processes, but they are often fixed in design, not suitable for multiple species, and prohibitively expensive for global deployment. For example, the process of counting sperm to calculate concentration can be accomplished by use of commercial devices such as a hemocytometer (>US$100) or a Makler chamber (>US$750) with counting by eye (which requires experience and is prone to variation) or by use of a computer-assisted sperm analysis (CASA) system (highly repeatable but >US$25,000). Integration of open-hardware microfluidic and microdevice systems would play a pivotal role in ensuring the dependable quality of germplasm materials, facilitating the isolation and culture of gametes and embryos, and optimizing the efficiency of sperm sorting and separation [13].

The use of soft lithography to develop microdevice systems (e.g., the Microfabricated Enumeration Grid Chamber [MEGC, 14] or the Single-piece Sperm Counting Chamber [SSCC, 15]) began to address some of the issues with sperm counting devices but suffer from prohibitively expensive initial costs and a lack of efficient options for iterative customization. Soft lithography typically makes use of the material, polydimethylsiloxane (PDMS) which yields high-resolution parts with excellent surface finish and low cytotoxicity [[14], [15], [16], [17], [18]]. In traditional PDMS-based soft lithography, microdevice fabrication relies on a master mold created through intensive soft lithography processes (e.g., photolithography and etching) [19]. Microdevice creation entails pouring the PDMS onto the master mold, letting it cure, and peeling it off to replicate the mold pattern. Despite its effectiveness, this process is expensive, time-consuming, complex [20], and has a number of drawbacks that limit use, especially for rapid prototyping. Soft lithography is more than capable of fabricating high-resolution devices for germplasm samples that exist at the smallest size ranges of aquatic germplasm (e.g., sperm of zebrafish [0.002 mm head width] or swordtails [0.001 mm head width]). However, it is not reliable for creating devices with larger or varied heights and depths that are required for most other species, and is slow, costly, and restricted to specialized facilities. In this study, we did not directly compare PDMS and resin prints, although such evaluations have been conducted in the past [[21], [22], [23], [24], [25], [26]]. Instead, our focus was on the evaluation of the potential for shifting to new fabrication techniques, including overall consideration of factors such as cost reduction, improved fabrication accessibility, and development of open-hardware communities based on the sharing of digital design files.

Three-dimensional (3-D) resin printing techniques such as stereolithography (SLA) and digital light projection (DLP) offer a promising and effective alternative to soft lithography and are gaining traction in the development and prototyping of microdevices. These rapidly advancing technologies can play a crucial role in addressing the creation of hardware devices with broad applications in genetic resource protection [14,15,27,28]. Three-dimensional resin printers surpass many of the constraints of soft lithography and other traditional methods through layer-by-layer transformation of computer-aided designs into tangible hardware, crafting accurate 3-D shapes. This process eliminates the need for photo masks, alignment processes, etching, and bonding which require specialized facilities and well-trained personnel, offering a more efficient and flexible manufacturing approach [29]. In addition, resin printers have access to thousands of resin types, including those developed for application in human medicine (e.g., dental-grade resins) and for use with germplasm [e.g., [30]].

Two major levels of resin printers are industrial-grade and consumer-grade. In general, consumer-grade printers have lower prices (US$400 – US$1,000) and lower-grade components, often limiting the resolution that can be achieved. Industrial-grade printers come with greater up-front costs (>US$10,000) but have higher-grade components, access to customizable resin materials, optimized resin polymerization, and system processing features for faster and more successful prints. Even the higher-priced machines, however, are much more widely available and less expensive than traditional soft lithography. Although some groups have taken the approach of pushing the capabilities of consumer-grade printers, a slow and resource-intensive process [31], there are few studies that evaluate the accuracy and precision available and resources required for device fabrication using these different techniques (resin printing and soft lithography) and printer types (industrial and consumer). This understanding is vital for aquaculture and aquatic research communities outside of traditional engineering departments. Consumer-grade products are beneficial because of their accessibility, but for technology developers, it may be more advantageous to prototype quickly with industrial-grade printers before pushing the boundaries of consumer-grade products to make devices widely available. By finding a balance among these factors, 3-D resin printing can offer new opportunities for rapid prototyping and production of micro-scale devices as an alternative to conventional soft lithographic methods.

Thus, the goal of this study was to evaluate the capabilities of 3-D resin printers and demonstrate the fabrication quality of microdevices using industrial and consumer 3-D resin printers and conventional soft lithography (photolithography) techniques. The specific objectives were to: 1) evaluate accuracy and precision in feature fabrication with opaque and clear resins; 2) assess the accuracy and precision between fabrication techniques (resin printing and photolithography), particularly for small features (<1 mm); 3) analyze the visual morphology of features produced by different methods, and 4) evaluate the utility, time, and cost requirements for overall comparison of microfabrication among the methods.

2. Materials and methods

2.1. Device description and fabrication

There is a wide range of forms and functions of microdevices. This study evaluated two representative devices: one with real-world application and one specifically designed to test the limits of resin 3-D printers. Both devices were designed using computer-aided design (CAD) software (Fusion 360, Autodesk, San Rafael, CA, USA) for systematic evaluations. The first was the Single-piece Sperm Counting Chamber (SSCC) [15], which consisted of grid and wall features with height of 0.01 mm (photolithography) or 0.1 mm (resin printing), including gaps in the gridlines that connect the squares to allow better distribution of samples for counting or quality evaluation (e.g., sperm motility) (Fig. 1, left column images). This difference in wall height between fabrication technologies prevented direct comparison but was necessary based on the current limitations and nature of the technological processes (e.g., photolithography spinning and resin printing layer height). The SSCC was specifically designed to accurately count sperm concentration in aquatic species such as zebrafish [15]. Its functionality heavily depends on the chamber volume, ensuring precise counting. This chamber provides a simple, customizable, and cost-effective alternative to traditional counting methods, aiding research in reproductive biology and assisted reproduction technologies.

The second was the Integrated Geometry Sampler (IGS), which featured an array of negative and positive features such as a semi-spheres, channels with dimensions ranging from 1 mm to 0.02 mm in width and depth, and concentric circles ranging in diameter from 4.2 mm to 0.6 mm and with step sizes of 0.2 mm (Fig. 1, right column images). Fabricating the IGS with traditional photolithography techniques would be cumbersome due to the many different feature heights on the device, each of which necessitates a separate masking, exposure, and development process. The IGS was designed specifically to evaluate the fabrication quality of 3-D resin printers.

2.1.1. Fabrication by use of soft lithography

The photolithography-based SSCC devices evaluated in this study were fabricated using a master mold created previously [12] on a silicon wafer. The process is briefly described below. A clean silicon wafer (UniversityWafer Inc., South Boston, MA, USA) served as a mold substrate. A 0.01-mm layer of SU-8 photoresist (MicroChem Corp., Newton, MA, USA) was spin-coated (Laurell Technologies Corporation, North Wales, PA, USA) on the wafer. This photoresist was chosen for its resolution and ease of microfabrication [32]. Spin-coater settings (e.g., rotational velocity) and photoresist type [33] determine the minimum and maximum feature height that can be achieved. A precisely aligned mask was set on top of the wafer to transfer the pattern during UV light exposure (American Ultraviolet®, Lebanon, IN, USA). The unexposed SU-8 photoresist was subsequently removed by application of SU-8 developer (MicroChem Corp., Newton, MA, USA), revealing the pattern on the wafer. A 10:1 mixture of PDMS and curing agent (Sylgard-184, Sigma-Aldrich, Inc., MO, USA) was prepared according to the manufacturer’s specifications and was poured onto the mold, covering the SSCC pattern. To remove air bubbles, the PDMS was degassed in a vacuum chamber, followed by curing in an oven at 70 °C for 2 h to solidify the PDMS. The de-molded PDMS was cleaned with 70% isopropyl alcohol (IPA), deionized (DI) water, and dried with nitrogen gas.

2.1.2. Selection of 3-D printers and resin materials

This study evaluated two 3-D resin printer models representative of current (as of January 2024) industrial and consumer levels. This work was not intended as a direct comparison of manufacturers or models. To broadly evaluate the capabilities of 3-D resin printers and microfabrication, we chose an industrial 3-D resin printer (ProFluidics 285D, CADworks3D, Concord, ON) and a consumer-grade printer (Sonic Mighty 8K, Phrozen, Hsinchu City, Taiwan). The IGS produced using the industrial 3-D printer was evaluated against another made with the consumer 3-D printer. Versions of the SSCC made with industrial and consumer 3-D printers were also evaluated with a photolithography-based SSCC, although this was again not intended to be a direct comparison because of a pre-selected difference in the SSCC grid-wall heights (0.1 mm for resin printers and 0.01 mm for photolithography).

The industrial 3-D printer had a 28.5-μm dynamic pixel size and an approximate cost of US$18,000. For the fabrication of devices with the industrial 3-D printer, opaque green mastermold resin (CADworks3D, Concord, Ontario) and clear microfluidic resin (CADworks3D) were used. The consumer 3-D resin printer had a 28-μm pixel size and cost approximately US$700. For fabrication of devices with the consumer 3-D printer, opaque gray Aqua 8K resin (Phrozen, Hsinchu City, Taiwan) and Nova3D ultra-clear resin (Nova3D, Guangdong, China) were used.

Apparatus Used

Clear Microfluidic Resin

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Master Mold for PDMS

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ProFluidics 285D

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2.1.3. Three-dimensional resin printing process

Pre-processing: During the printer slicing process for the SSCC and IGS models, variations were introduced to the dimensions because the slicer needed to adjust the lateral measurements to align with the pixel sizes (∼28 μm) of the LCD array – i.e., the printer cannot use half a pixel to accommodate a specific dimension [34]. This device-pixel alignment improved grid line consistency and uniformity in square designs. Thus, the X-Y dimensions of each device were scaled by a factor of 28. For example, the SSCC width was set at 392 μm, which is divisible by 28. Designs were converted to STL format for slicing using Utility (Ver 6.4.4.t12) for the industrial 3-D printer and LycheeSlicer (Ver 5.2.201) for the consumer 3-D printer. Multiple printing configurations were evaluated for both printers and the chosen settings are listed in Supplementary Table 1. These settings were selected to balance printing of positive and negative features. Based on printer behavior with specific geometries (e.g., a channel printed 20% deeper than expected), device dimensions (e.g., decreased channel depth) and slicer settings can be optimized to target positive or negative features. This study thus evaluated print quality without focus on single fine-tuned adjustments, illustrating the mechanical precision and accuracy differences of industrial and consumer-grade resin printers across a composite range of feature types and sizes that would occur in quality-management devices for aquatic species.

Post-processing: After printing, residual resin was removed by immersing the devices in a plastic bag containing 70% IPA and placing the bag into an ultrasonic water bath for 4 min. The devices were rinsed with fresh 70% IPA and DI water to ensure the complete removal of uncured resins. After 2 min of air drying, devices were exposed to a 405 nm UV light (Elegoo, Mercury X Cure, China) for 1 min to complete curing and post-processing.

2.2. Fabrication quality assessment

Comparison of multiple device features was used to provide insight into fabrication quality, accuracy, and precision among the different fabrication technologies and served as a preliminary evaluation for the widespread transition from conventional microfabrication approaches to 3-D resin printing. In fabrication of microdevices such as microchannels, clarity in the final device is crucial for use in light microscopy. While clear resin is typically preferred for this purpose in 3-D resin printing, we encountered challenges from reflected light when conducting profilometry on devices crafted from clear resin, which hampered dimensional measurements. To address this, we conducted experiments wherein devices were fabricated in parallel using opaque and clear resins.

To directly address the profiling of clear resin, a thin coating (<0.005 mm) of titanium dioxide (TiO₂) nanoparticles was applied to devices. Titanium dioxide nanoparticles were suspended in isopropanol (0.1 mg/ml) and spray coated by use of an airbrush to enhance the surface optical properties (Semmes et al., unpublished data). The gray devices did not require the addition of a TiO₂ coating layer. All devices were scanned by use of an optical profiler (Keyence VR-6100, Osaka, Japan) that used non-destructive, non-contact analysis principles. The profiler utilized light to examine surface topography, splitting the light source into two paths: one directed at the surface and the other at a reference mirror. Upon recombination, reflections were projected onto an array detector, enabling precise (0.001 mm) measurements with minimal interference. Dimensional measurements were analyzed using 3D Optical Profilometer VR-6000 software (Keyence). The reference plane for the SSCC was at the bottom of the counting chamber, and for the IGS was at the middle surface between negative and positive features.

While simple 3-D printed parts with large feature sizes can be assessed by visual observation for suitability, microdevices with features and dimensions that differ from the target dimensions (e.g., micromixers) can show altered performance and require closer inspection upon fabrication. Thus, this study evaluated accuracy and precision of printed device features. Accuracy refers to the closeness of measured values to target values, while precision indicates the consistency and reproducibility of measurements. These metrics are crucial for understanding the reliability and performance of fabrication processes, particularly in the context of transitioning from conventional microfabrication methods to emerging 3-D printing techniques. In this study, accuracy was evaluated by the difference between the target dimension and the mean of measured dimensions (photolithography, n = 6 measurements on 1 device; resin printing, n = 6 measurements each on 4 devices). Precision was assessed by calculating the standard deviation to quantify consistency and reproducibility of the fabrication processes.

To visually assess surface morphology and examine small changes in residual resin, samples were examined by use of a scanning electron microscope (SEM) (JSM -6610 LV SEM, Jeol USA, Peabody, MA, USA). Preparing devices for SEM imaging involved several steps to achieve high-resolution images. Devices were cleaned with IPA, rinsed with DI water, and air dried. A thin layer of titanium was sputter-coated onto the sample to prevent charging and improve image quality. Prepared devices were loaded into the SEM chamber. A high vacuum was pulled on the chamber in preparation for imaging. Devices were positioned and images from several angles and magnifications were captured for later visual analyses.

2.3. Time and cost requirements of microfabrication techniques

An evaluation was conducted of the time and cost associated with fabrication, assessing photolithography-based SSCC and devices printed by use of 3-D resin printing. For the photolithography time estimate, we assumed that all necessary equipment was at one facility to perform typical tasks as follows: mask preparation, spin-coating SU-8 photoresist, aligning and UV exposing, developing and curing the photoresist, pouring the PDMS mixture onto the mold, vacuum degassing, curing in an oven, and cleaning and drying the de-molded PDMS. For evaluation, the total printing duration comprised the active printing time (provided by the 3-D printer) and the associated pre-processing (e.g., slicing) and post-processing (e.g., cleaning and curing) steps. For photolithography, costs included mask creation, silicon wafer production, SU-8, SU-8 developer, and PDMS; for the 3-D printers, the cost calculation incorporated the expenses of resin materials.

3. Results

3.1. Accuracy and precision in feature fabrication with opaque resin

Dimensional accuracy (difference between target dimensions and the mean of measured dimensions) and precision (standard deviation) were assessed in fabrication of negative features (microchannel depth) on the IGS using opaque resins. For channel depths of 0.4–1 mm, the industrial 3-D printer depth showed a difference of <2% between the target and measured dimensions (Fig. 2a). In contrast, the consumer 3-D printer displayed a 3–8% discrepancy in channel depths across this range. For smaller channels of 0.1–0.2 mm, the industrial 3-D printer depth showed a difference of about 13% (Fig. 2b). Using the settings described herein, the consumer printer failed to reliably fabricate channels <0.2 mm. The standard deviation of measurements for all channel depths ranged from 0.011 to 0.039 mm for the industrial 3-D printer configuration. In comparison, the consumer printer exhibited standard deviation values ranging from 0.018 to 0.046 mm for all channel depths.

Figure 2. Comparative analysis of IGS positive and negative microchannel features of devices fabricated with industrial-level (white) and consumer-level (black) 3-D resin printers compared to target dimensions (gray). Devices were printed using opaque resin with features ranging from 1 to 0.4 mm (panel a), and ranging from 0.2 to 0.05 mm (b); and clear resin with features ranging from 1 to 0.4 mm (c), and ranging from 0.2 to 0.05 mm (d). Sample size of four devices with six measurements per device were averaged and error bars were reported as standard deviation.

Analysis of the accuracy of positive features (raised microchannels) on the IGS using opaque resins for heights of 0.4–1 mm fabricated by the industrial 3-D printer showed a difference of <2% between the target and measured dimensions (Fig. 2a). In contrast, evaluation of the accuracy of positive (raised) features produced by the consumer 3-D printer revealed fluctuations exceeding 30%. For smaller heights of 0.1–0.2 mm, the industrial 3-D printer depth showed a difference of about 19% (Fig. 2b). The standard deviation of measurements for all channel heights ranged from 0.01 to 0.031 mm for the industrial 3-D printer. In comparison, the consumer 3-D printer exhibited standard deviation values ranging from 0.007 to 0.029 mm.

Seven positive and seven negative stepped features were designed in the IGS with heights and depths of 0.2 mm per step (1.4 mm overall). For the first five negative stepped features the depths fabricated with the industrial 3-D printer showed a difference of <6% between the target and measured dimensions (Fig. 3a). In contrast, the consumer-level printer displayed a 12–26% discrepancy between target and measured dimensions in seven-stepped feature depths. Using the settings described herein, the industrial printer failed for the last two bottom (6th and 7th) stepped features. The standard deviation of depth measurement ranged from 0.011 to 0.042 mm for the industrial printer. In comparison, the consumer printer exhibited standard deviation values ranging from 0.024 to 0.041 mm.

For the positive stepped features (diameter range from 4.2 mm to 0.6 mm), accuracy of the industrial 3-D printer had a difference of <5% between the target and measured heights. In contrast, accuracy of positive stepped features produced by the consumer printer was <11% other than the first and second round features (diameters of 4.2 and 3.6 mm) which deviated from the target values by over 40%. The standard deviation of height measurement ranged from 0.011 to 0.019 mm for the industrial printer. In comparison, the consumer printer exhibited standard deviation values ranging from 0.01 to 0.041 mm (Fig. 3a).

Analysis of the accuracy of the opaque SSCC (with a grid height of 0.1 mm) fabricated with the industrial 3-D printer had a 4% discrepancy between target and measured heights (Fig. 4). The consumer printer had a discrepancy of 37% in dimensional height when utilizing opaque resin. The standard deviation for the samples fabricated with the industrial printer was 0.003 mm. Despite the discrepancies with the consumer printer, the standard deviation was 0.004 mm.

Figure 4. Comparative analysis of the target depth versus the mean of measured depth using opaque resin and clear resin for SSCC fabricated with an industrial 3-D printer (white), consumer 3-D printer (black), and photolithography (cross-hatched), compared to target dimensions (gray). Percent difference of the mean measured depth from the target depth was indicated at the top of each bar. Standard deviation was indicated by error bars. The target height for SSCC fabricated by use of resin printers was 0.1 mm and the target height for SSCC fabricated by use of photolithography was 0.01 mm. For resin prints, four devices with six measurements per device were averaged. For photolithography, one device with six measurements were averaged.

3.2. Accuracy and precision in feature fabrication with clear resin

While clear resin proved to be an ideal choice for fabricating microfluidic channels, SSCCs, or any devices requiring transparency (e.g., for visual observation), there were several challenges related to printing and profilometry that must be taken into consideration. During printing, parts in clear resins were vulnerable to distortion from additional light exposure “bleed” from layers above and below the intended layer. Also, during profilometry, reflection and refraction can distort the measurements due to changes in the optical properties of the medium.

For channel depths of 0.1–1 mm, the industrial 3-D printed IGS showed a depth difference of <4% between target and measured dimensions (Fig. 2c and d). In contrast, for channel depths of 0.4–1 mm, the consumer-level printer had less than a 6% discrepancy. It exhibited a 12–15% discrepancy for features of 0.1–0.2 mm. The standard deviation of depth measurement ranged from 0.004 to 0.03 mm for the industrial printer. In comparison, the consumer printer had standard deviation values ranging from 0.003 and 0.027 mm.

Analysis of the accuracy of positive features (raised microchannels) of the IGS fabricated with the industrial 3-D printer using clear resins for heights of 0.1–1 mm showed a difference of 0.5–5% between target and measured dimensions (Fig. 2c and d). In contrast, for channel heights of 0.4–1 mm the consumer-level printer had a 15–17% discrepancy. However, this exceeded 33% for channels ranging from 0.1 to 0.2 mm. The standard deviation of height measurements ranged from 0.005 to 0.031 mm for the industrial printer. In comparison, the consumer printer had standard deviation values ranging from 0.017 to 0.063 mm.

For the first five negative stepped features (diameter range from 4.2 mm to 1.8 mm) the depths with the industrial 3-D printer using clear resin had a difference of <4% between target and measured dimensions (Fig. 3b). In contrast, the consumer-level printer had a 2–15% discrepancy in seven stepped-feature depths (diameter range from 4.2 mm to 0.6 mm). Using the settings described herein, the industrial printer failed for the last two bottom (6th and 7th) stepped features with diameters of 1.2 and 0.6 mm. The standard deviation of depth measurements ranged from 0.009 to 0.044 mm for the industrial printer. In comparison, the consumer printer had standard deviation values ranging from 0.07 to 0.039 mm.

For the positive stepped features (diameter range from 4.2 mm to 0.6 mm), accuracy of the industrial 3-D printer showed a difference of <6% between target and measured heights. In contrast, accuracy of positive stepped features produced with the consumer printer was <12% other than the first and second stepped features (diameters of 4.2 and 3.6 mm) which failed to print. The standard deviation of height measurements ranged from 0.01 to 0.022 mm for the industrial printer. In comparison, the consumer printer had standard deviation values ranging from 0.014 to 0.029 mm (Fig. 3b).

Analysis of the accuracy of the clear SSCC (with grid height of 0.1 mm) fabricated with the industrial 3-D printer had a 2% discrepancy between target and measured heights (Fig. 4). The consumer printer had a discrepancy of 24% in dimensional height when utilizing clear resin. The standard deviation for the samples fabricated with the industrial printer was 0.008 mm. Despite the discrepancies for samples fabricated with the consumer printer, the standard deviation was 0.012 mm.

For the photolithography-based SSCC (cast from the wafer), a 0.8% difference between target and measured heights was observed (Fig. 4). The standard deviation was 0.001 mm.

3.3. Visual morphology

Achieving optimal squareness in 3-D printed features posed a notable challenge. Images captured with the optical profilometer illustrated differences in IGS negative features fabricated with industrial and consumer 3-D resin printers using opaque and clear resins (Fig. 5a-e).

Figure 5. Two-dimensional images produced by optical profiling of IGS channels with square cross-sectional design (ranging from 1 mm to 0.05 mm) fabricated with industrial 3-D printer using clear resin (panel a), industrial 3-D printer using opaque resin (b), consumer printer using clear resin (c), consumer printer using opaque resin (d), in comparison to a representative 3-D image (industrial printer using opaque resin) of the negative features (e). Blue colors indicate values below the reference plane and green colors indicate depths closer or equal to the reference plane. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

In general, deeper features appeared to have better squareness at their bottoms. Visually, the industrial resin printer (Fig. 5a and b) was able to produce sharper angles at the bottom and top of negative features compared with the consumer resin printer (Fig. 5c and d).

Visual analysis of stepped features identified different problems than square features. To facilitate visual analysis, a Keyence tool called “CAD Compare” was used (Fig. 6). The line plots (top of each panel) showed that the industrial printer with opaque resin performed best at depth and height feature fabrication. The consumer printer did well when printing negative features with clear resin, while the industrial printer did better when printing positive features with clear resin. This CAD Compare analysis also assessed the roundness of the cylinders which is important in some applications but was not directly addressed herein. Visually, the roundness of the cylinders was good with both printer types and resins, until the smallest (deepest and tallest) layers. This was also where the printers struggled to fabricate accurate depths and heights (Fig. 3).

Figure 6. Images produced by optical profiling of IGS stepped features for target profile, sample profile, and CAD comparison (height difference between target and printed sample) for the industrial 3-D printer with clear resin (panel a), industrial 3-D printer with opaque resin (b), consumer printer with clear resin (c) and, consumer printer with opaque resin (d). Reds indicated measured depths that were shallower than the target, green indicated measured depths and heights that were near or equal to the target, and blues indicated measured heights that were shorter than the target. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

The surface quality of the SSCC imaged by use of scanning electron microscopy (SEM) revealed differences in performance among the fabrication methods (Fig. 7a-c). This showed the pre-selected difference in grid-wall height between the photolithography-based (0.01 mm) and resin-based (0.1 mm) SSCCs. The channels between grids were reliably fabricated with photolithography and the surface detail at the bottom of each cell was smooth (Fig. 7a). In resin-based devices, the channels between the grids were not reliably created, although the surface detail was relatively smooth (Fig. 7b and c). A texturing is visible resembling the pixel pattern from the printer LCD. Of note are the visible layer lines produced with the industrial 3-D resin printer (Fig. 7b). The grid walls appear to be 2-layer lines thick (0.03 mm layer height and 0.1 mm target grid height).

Figure 7. Scanning electron microscopy of SSCC devices fabricated using: photolithography (panel a), industrial 3-D resin printing (b), and consumer 3-D printing (c) (scale bars = 0.1 mm). The SSCC consisted of grid and wall features with heights of 0.01 mm (photolithography) or 0.1 mm (resin printing), including gaps in the gridlines that connected the squares to allow better distribution of sample for counting or quality evaluation (e.g., sperm motility) of biological samples.

To evaluate post-processing, SEM images of SSCC were captured before and after removal of residual resin (Fig. 8a and b). One interesting observation was that post-processing revealed the channels between the grids, which were important for even filling and cellular distribution within the device.

In the final phase of post-processing, UV exposure was applied to the samples for 1 min, enhancing mechanical properties but sometimes introducing a curvature [35]. Various printing parameters including print time, single-layer height, post-curing UV intensity, and total thickness have been reported to play substantial roles in this curvature phenomenon [36]. Images of SSCC with and without post-processing (UV exposure) were captured with the profiler (Fig. 9a and b). Curling was evident in the UV-exposed sample. To mitigate this, an approach was developed allowing the sample to remain affixed to the build plate for approximately 24 h after UV exposure (data not shown). This served as an effective method to alleviate stress in the printed samples, contributing to the reduction of curvature induced by post-processing.

Figure 9. Profiled height of a SSCC device produced by the industrial printer, before curing (panel a), and after curing demonstrating curling (b) (UV exposure). The colour indicates the depth relative to a baseline of zero. Note the difference in scales. Orange indicates measurements equal to the reference plane (a). Reds indicate measurements above, the reference plane and greens and blues indicate measurements below the reference plane (a). Blue indicates measurements equal to the reference plane (b). Reds, oranges, and greens indicate measurements above the reference plane (upward curvature) (b). (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

3.4. Comparison of time and cost of microfabrication

Efficiency and cost-effectiveness are pivotal factors in selecting microfabrication techniques for creation of microdevices [31]. In terms of fabrication time, fabrication of a single SSCC with photolithography typically required around 2 d and cost US$555 (Table 1). However, utilizing industrial and consumer-grade 3-D resin printers significantly reduced time and material costs. For example, the industrial printer fabrication time was <38 min and cost as little as US$0.08 per unit (Table 1). The cost calculations (Supplementary Table 2) did not include salary, electrical, or other facilities and personnel costs because these vary by location. The time calculations did not take into consideration the new approach to mitigate post-UV exposure curvature because it may not be necessary for all device configurations.

4. Discussion

This study evaluated dimensional accuracy and precision, visual morphology, and squareness of depth and height features in devices fabricated by use of traditional photolithography and industrial and consumer-grade 3-D resin printers using opaque and clear resin. In addition, the time and cost requirements were evaluated for microfabrication among the methods. The findings of this study underscored the comprehensive capabilities of industrial-grade and consumer-grade 3-D printers, in relation to photolithography in meeting complex dimensional requirements for specific applications. For this evaluation, the SSCC provided a device with direct relevance to biological usage, and the IGS allowed evaluation of fabrication quality of 3-D resin printers across a range of features. In the selection of IGS features, square geometries were chosen due to their prevalence and significance in microfluidic applications which were the primary focus of this study. Depth and height of stepped features also hold significance in certain applications and pose challenges during fabrication and were thus also chosen for evaluation. Dimensional accuracy and precision and squareness of depth and height features are critical factors for the use of quality management devices for germplasm. Differences in fabrication quality translate to functional performance changes, affecting accuracy of metrics such as sperm concentration which requires accurate volumetric calculations or microfluidic mixing efficiency needing precise feature angles and placement.

The industrial 3-D printer consistently exhibited close accuracy and precision aligned with the photolithography-based SSCC for microchannel fabrication using clear resin, even with minimum feature sizes as small as 0.1 mm. Conversely, the consumer 3-D printer, although less accurate and precise for features smaller than 0.2 mm, demonstrated reliability for features above this threshold. The larger variations, especially for raised features, were likely attributable to the specific printer settings. Throughout preliminary preparation for this study, numerous settings were explored to establish a balance for the evaluation of positive and negative features in the same device. The settings outlined in Supplementary Table 1 were identified as being effective for the specific purposes of this study.

As with traditional fabrication approaches, 3-D printing has a trade-off between extensive optimization for accuracy and precision, and the need for rapid prototyping or production of parts that do not require high tolerances [37]. With targeted refinements it would be possible to identify specific print settings for the consumer-grade printer that would further enhance the quality of the positive or negative features, but this was not the intent of the study. Industrial printers require less adjustment of such settings as they are already optimized for specific applications (e.g., microfabrication in the present study). In fabricating opaque SSCCs using consumer-grade printers, we encountered instances where the devices exhibited high precision comparable to the industrial-grade printer but lacked in accuracy (Fig. 4). Through experimentation involving iterative prototyping and adjustments to factors such as resin types and print settings, achieving a practical balance between accuracy and precision appeared to be achievable.

Stepped features printed with an industrial printer, had positive features (using opaque and clear resins) within 6% of the target dimensions, and thus exhibited reliable accuracy. However, the 6th (1.2 mm diameter) and 7th (0.6 mm diameter) negative stepped features failed to print reliably. This could be attributed to several factors including the round shape of features with small diameters, or the print settings, which may pose challenges for printing. Surprisingly, this was less challenging with the consumer printer. Instead, the consumer printer had problems with the 1st (4.2 mm diameter) and 2nd (3.6 mm diameter) positive stepped features using opaque and clear resins. Due to the higher sensitivity of consumer machines to print settings, achieving better results may be possible through adjustments to these settings. Future evaluations of the roundness (X-Y orientation) of round features on the IGS will provide insight into the potential limitations of LCD-based resin 3-D printers to fabricate round features.

These results highlighted the capabilities of different fabrication methods in terms of accuracy and precision across different feature sizes and types. It established industrial 3-D resin printers as a strong option for applications requiring high-resolution microfabrication, while consumer printers remain a viable choice for less demanding applications where feature sizes are not as critical or where there is more time for optimization of settings and resin types. The rapid advancements being made in consumer 3-D resin printing open substantial opportunities for achieving reliable microfabrication in the future. With respect to aquatic organisms, even the consumer-level printers provided sufficient accuracy and precision for routine practical use with most species and germplasm types.

Apparatus Used

Clear Microfluidic Resin

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Master Mold for PDMS

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ProFluidics 285D

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The width resolution (not directly examined herein), is intricately linked to the X-Y resolution and is influenced by the size of the projected pixels. It operates in conjunction with depth resolution, which is closely tied to Z resolution, representing the thickness of each cured layer [38]. These interrelated factors collectively contributed to the overall accuracy, precision, and level of detail attainable in printed objects. In exploring the relationship between printing orientation and dimensional accuracy and precision, altering printing orientation by 90 degrees could potentially result in a reduction in the variance of depth dimensions compared to width [39,40]. Changing the print orientation may thus influence the dimensional accuracy and precision of features within devices like the SSCC. These considerations should be investigated further and offer another avenue for reducing differences and variations observed in the depth dimensions from the printers.

In terms of visual squareness, the industrial 3-D resin printer using clear resin produced sharper corners in channels compared to prints with opaque resin (Fig. 5). When assessing the final output, it was essential to consider the influence of the slicer settings on dimensions and printer resolution. The industrial printer produced channels of ≥0.1 mm with minimal defects. However, potential defects, particularly in the roundness of the edges, become noticeable for channels smaller than 0.1 mm, affecting positive and negative features under these conditions. The consumer 3-D resin printer using opaque resin produced sharper corners in channels compared to prints with clear resin but was able to produce smaller channels better with the clear resins (Fig. 5). These visual observations of squareness between the two printer types demonstrates the opportunities to advance their capabilities and could be helpful in deciding which printer type would be best suited for specific applications that require square-angle features in clear or opaque.

Surface morphology plays a crucial role in determining the functionality and performance of microdevices. For instance, in biomedical devices it can affect cell adhesion and proliferation [41]. The industrial 3-D printer produced visually smoother surfaces compared to prints with the consumer 3-D printer (Fig. 7b and c). This superior surface quality could contribute to enhanced functionality and reliability of microfluidic channels fabricated using industrial-grade 3-D printing, highlighting its potential for various applications requiring high-quality surface finishes. Comparatively, the photolithography-based SSCC exhibited a visually smoother surface (Fig. 7a) with fewer defects than devices created by the industrial 3-D resin printer. The effect of these differences in surface morphology on the functionality and performance of resin-printed devices requires further investigation and will vary across the range of devices and functionalities desired.

For stepped features, squareness and roundness of the edges were significant factors. These parameters appeared to be satisfactory for industrial 3D-printed samples. However, in the case of consumer 3D-printed samples, while the roundness appeared acceptable, there were noticeable issues with edge squareness. The CAD comparisons showed differences in depth or height of negative or positive features compared to the design. The industrial and consumer printers generally produced better surface morphology for positive stepped features compared to negative features.

The photolithography-based method, despite its time-intensive 2-day fabrication process and substantial cost of approximately US$555 per unit for SSCC fabrication, distinguished itself through accuracy, precision, and control. This makes it particularly well-suited for applications that prioritize exacting accuracy and precision, such as highly quantitative analysis of the smallest of aquatic germplasm types (e.g., zebrafish sperm). It should be noted that the unit cost associated with photolithography decreases once a finalized mold is generated because many devices can be cast from one mold [15]. Although, the unit cost could also increase drastically if customization or changes need to be made to a mold which would require repeating the mold creation process. Industrial resin 3-D printing was efficient, requiring <30 min for IGS and SSCC fabrication with material costs estimated at US$0.32 per unit for clear IGS and US$0.08 for clear SSCC. This method enhanced rapid prototyping and fabrication. On the other hand, consumer resin 3-D printing struck a balance between fabrication time and cost, providing relatively fast times (<150 min) for IGS and SSCC (clear and opaque), with costs estimated at US$0.03 per unit for clear IGS and US$0.01 for clear SSCC. This presents a cost-effective solution for open-hardware applications with budgetary constraints while providing satisfactory fabrication times across the size and resolution range needed for aquatic species. Overall, photolithography can provide accuracy and precision, industrial resin 3-D printing can be useful for rapid prototyping, and consumer resin 3-D printing offers a balance between efficiency and cost-effectiveness, with these differences operating along a gradient of scale.

Aquatic species are in great need for powerful and innovative solutions requiring rapid prototyping and, at a minimum, batch fabrication. Currently, the resolution for resin printing is sufficient for these applications, and eventually printers that can compete directly with soft lithography will become cheap enough to be accessible to the broader community. Moving forward, devices created by use of 3-D resin printing will require testing to ensure accuracy and functionality, and resins will need to be evaluated for cytotoxicity. Though it is important to note that resin contact with sperm is for a short duration (1–2 s) and devices can make use of a disposable sub-sample rather than the entire sample. Even with the current capabilities of resin printing, we can move seamlessly from micro- to milli- to macro- scales in the design process without changing materials or equipment. Overall, the dynamic range of resin printing demonstrated herein enables high precision and throughput that can extend into open hardware, promoting inclusive access to critical technology and fostering community-driven innovation for aquatic species.

In addition, all the architecture necessary for a single device (e.g., Luer locks and other connections) can be printed at one time and in one material enabling direct single-step production of devices. However, resin printers are not limited to direct production and, like photolithography, can also print device molds facilitating access, distribution, and community development. By adding 3-D resin printing to the roster, designers, fabricators, and users now have multiple options for developing and obtaining devices. The greatly broadened accessibility of resin 3-D printers compared to photolithography provides new opportunities for standardized designs and procedures. This approach empowers wider dissemination and adoption within research and aquaculture communities, accelerating the transition to open hardware and sustainable germplasm repository development. By cultivating an international community capable of independent fabrication and design, a collaborative system can emerge to enhance genetic resource protection and promote much-needed innovation in culture, breeding, conservation, and research of aquatic species.

5. Conclusions

This study provided an overall evaluation of the capabilities of representative industrial-grade and consumer-level 3-D resin printing compared to conventional photolithography in fabrication of microdevices with a specific focus on germplasm repository development for aquatic species. This provides a platform for improving critical QM strategies throughout genetic resource protection processes. Fabrication quality distinctions were highlighted through the assessment of various components in microdevices including positive and negative features, channels, and complex structures. Visual morphologic analysis revealed differences in squareness and roundness, emphasizing the importance of considering these factors in the design of devices and the selection of fabrication technologies.

Overall, this research contributes to the ongoing exploration of emerging technologies in microdevice development and prototyping. By understanding the strengths and limitations of 3-D resin printing technologies, researchers and industry professionals can make informed decisions when selecting fabrication methods for specific applications. As the field progresses, studies of this type can provide a solid foundation for future advancements in custom microdevice creation, particularly with essential germplasm repository technology for aquatic species. By pioneering a shift from traditional methods to 3-D resin printing, the stage can be set for more efficient and precise fabrication processes. In addition, insights into the trade-offs between consumer-grade and industrial-grade printers can guide technology selection facilitating broader accessibility and innovation. Such findings will fuel development of standardized protocols, open-hardware designs, and novel solutions, ultimately enhancing aquatic species conservation efforts and genetic resource preservation. Interdisciplinary approaches such as these integrating biology and engineering (e.g., [42]) in a real-world context offer powerful mechanisms for producing innovation to address future challenges including climate change.

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References

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Reversible electrochemical pH modulation in thin-layer compartments using poly(aniline-co-o-aminophenol)

January 16, 2026July 15, 2024 by CadWorks3DAdmin

Academic Article

Reversible electrochemical pH modulation in thin-layer compartments using poly(aniline-co-o-aminophenol)

by Alexander Wiorek, Chen Chen, María Cuartero and Gastón A. Crespo

Abstract: The analysis of many environmental and clinical samples requires the modification of the original pH, which is conventionally carried out by manual/automatic addition of acid, base, or buffering reagents. In the case of decentralized measurements, often, this approach is not plausible. Instead, reagentless alternatives, such as electrochemically activated in-situ pH adjustments, are suitable. Herein, we present a method for electrochemical, reversible pH modulation of thin-layer samples (<100 µm thickness) using the co-polymer poly(aniline-co-o-aminophenol) (PANOA). The PANOA’s electropolymerization strategy was optimized considering the proton exchange properties in the final material. Thus, limiting the maximum anodic potential to 0.85 V and with the number of cyclic scans being ≤150), the optimal pH modulation capabilities were observed. The reversible proton exchange properties of PANOA were quantified by monitoring the pH inside the thin-layer sample (volume of 0.6 µL), which was defined by a 3D-printed microfluidic cell and a pH-sensor placed in a face planar configuration to the PANOA film. A pH value in the range of 2–4 can repeatably be reached in the samples in 3 min, purely by an electrochemical means and without the addition of external reagents. The concept has been demonstrated to acidify samples at environmental pH (artificial samples and Seawater). The outcomes suggest that the family of polyaniline-co-polymers are interesting to be explored and utilized for electrochemically based pH modulation strategies, if careful considerations are taken regarding their electropolymerization process. Overall, such materials could contribute to the development of continuous, decentralized measuring devices requiring acidification for the formal detection of environmental markers, such as nutrients, carbon species speciation and alkalinity, among others.

Keywords: poly(aniline-co-o-aminophenol); polyaniline; PH-modulation; thin-layer electrochemistry; microfluidics

We kindly thank the researchers at KTH Royal Institute of Technology for this collaboration, and for sharing the results obtained with their system.

1. Introduction

The modulation of sample pH is essential in many applications, ranging from analysis and separation of aminoacids [1] to the potentiometric determination of water hardness [2]. In environmental analysis, the use of acid to lower sample pH is necessary before the detection of relevant markers. For example, the detection of phosphate is inherently reliant on the formation of a complex with molybdate (phosphomolybdate), which can be detected optically and/or electrochemically at pH 2 or lower [3], [4]. Another environmentally relevant parameter that requires acid addition (i.e., acid-base titration) for its quantification is alkalinity (typically a pH of 3–4.5 is needed) [5]. Overall, the requirement for acid addition restricts these measurements to centralized laboratories, although on-site or in-situ operation using automatic analyzers has become popular over recent years. While these have helped increasing the frequency of data acquisition for phosphate and alkalinity [6], [7], [8], [9], macronutrients [10] and formaldehyde detection [11], they require waste storage tanks and sometimes, sample dilution before/during the operation, which may cause additional uncertainties in the provided outcomes. To circumvent these drawbacks, light- or electrochemical-driven methodologies for pH modulations could be beneficial instead of reagents additions.

It is possible that the most explored method for pH modulation is the one based on water-splitting at an electrode surface, generating either protons or hydroxide ions [12]. Utilizing a constant applied current or potential, which tends to be very high (ca. 1 mA/cm² and 2 V), in a thin-layer sample (thickness <100 µm), the pH can be exhaustively shifted in the entire volume. The concept was demonstrated by Van der Schoot et al., showing titrations where the generated charge was used to calculate the moles of acid/base delivered to the sample [12], [13]. Later on Steininger et al. reported on the determination of the sample buffer capacity by measuring the dynamic pH change in the sample generated from water splitting at both the working and counter electrodes, using chemical imaging [14]. Overall, water splitting is indeed an efficient method for adjusting sample pH, but the drastic conditions it requires could lead to undesired side reactions at the electrode surface.

Solid materials presenting proton-coupled redox reactions have proven certain advantages over water splitting for acidification purposes because proton delivery to the sample is possible at low potentials. Balakrishnan et al. showed that 4-aminothiolphenol covalently attached to an electrode surface could shift the pH under electrochemical control in nL volumes for up to 100 reversible cycles [15]. The oxidation of the compound involves a proton exchange: amines are converted into imines in the potential window from 0.65 to 0.8 V. Yet, the proton release capacity shown by this approach is expected to be enough only for nL-volume samples, because of the finite amount of active compound that can be attached to the electrode’s surface. Our group has demonstrated that polyaniline (PANI) is an excellent material for electrochemical pH modulation at even softer potentials than amines (0.2–0.4 V) [16], [17]. This has been used for thin-layer samples acidification coupled to the detection of alkalinity and phosphate [17], [18], [19], as well as chemical imaging of buffer capacity [20], dissolved inorganic carbon (DIC), and carbonate alkalinity [21] in environmental samples. In these works PANI showed suitability for being used for several weeks as long as it is regenerated in acidic solution (10 mM H₂SO₄) between each acidification usage [22]. Notably, the redox activity and proton release from PANI is not reversible above pH 4–5.

Other PANI-like materials (i.e., co-polymers or polymers containing aniline backbone) could be also of interest, which may be electroactive at higher pH. For example, poly(aniline-co-o-aminophenol) (PANOA), a co-polymer of aniline and o-aminophenol, is an electrochemically active material presenting reversibility at environmental pH values. Mu and coworkers were pioneers investigating the PANOA electropolymerization [23], reporting the structure and redox mechanism as presented in Scheme 1a. The o-aminophenol unit in the PANOA structure allows for reversible redox and proton exchange in solutions up to a pH of 9–10 [23], [24]. In addition, it exhibits anion-exchange properties [25], [26]. The reversibility of PANOA has been attributed to the conversion between the phenolic group (reduced state) and the quinone group (oxidized state) in its backbone. Another suggestion of the PANOA structure and its redox mechanism found in the literature is presented in Scheme 1b, where each o-aminophenol unit is separated by larger PANI-like segments [24], [27]. Here the proton exchange is additionally associated to these segments in the co-polymer. However, because of the poor reversibility of the proton exchange from the amine-imine redox reaction, less efficient proton exchange reversibility at environmental pH is expected than that of the phenol-quinone reaction.

Interestingly, PANOA’s redox activity at physiological and environmental pH values has been crucial for its implementation as a transducer in biosensors and heavy metal sensors [28], [29], among others. In these cases, PANOA was claimed to be superior to PANI in terms of redox activity at physiological pH. However, to the best of our knowledge, the use of PANOA for pH modulation of samples has not been investigated yet, in contrast to PANI [16], [17], [18], [19], [20], [21]. Herein, the use PANOA for reversible proton exchange in thin-layer samples is investigated. PANOA was characterized with both spectroelectrochemistry and thin-layer electrochemistry coupled to in-situ pH sensing. Our experiments revealed the analytical potential regarding further sensing in artificial and real samples that needs for acidification prior to such a detection.

2. Experimental section

2.1. The microfluidic cell and experimental setup of pH modulation in thin-layer samples

The microfluidic thin-layer cell was designed in AutoCAD 2022 (Autodesk) and printed using a Profluidics 285D 3D-printer and Clear Microfluidics Resin V7.0a (CADworks3D). The electrode configuration is presented in Fig. 1a, with a cell schematic shown in Fig. 1b. The cell has an inlet and outlet to allow sample exchange. The outlet additionally contains a pseudo reference/counter electrode (Ag/AgCl wire, RE₁/CE₁) that is to be connected to the potentiostat. The cell includes a second reference electrode (Ag/AgCl wire, RE₂) connected to the potentiometer. Such electrode was inserted into a separate opening present in the cell (the hole with the wire inside was sealed with the 3D-printing resin by curing it with UV-light for 30 s). The center of the cell had a 10-mm-diameter hole to allocate the two electrodes functioning as the acidification actuator (WE₁: PANOA) and the pH sensor (WE₂: PANI), creating a thin-layer gap sandwiched between them (<100 µm in thickness). Thus, two Au electrodes with a diameter of 3 mm (model 6.09395.034, Metrohm Nordic) were differently modified with PANOA (the working electrode, WE₁, in the potentiostat) and PANI (the working electrode, WE₂, in the potentiometer), being positioned in such a way that their areas faced each other, being separated by a 90-µm-thick double adhesive tape (RS Online, stock no: 555–033) that was placed on the edges of the electrodes.

Apparatus Used

Clear Microfluidic Resin

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ProFluidics 285D

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As the PANOA never exceeded a thickness of 10 µm (lower limit of the caliber used for the measurement) this spacer was used for all experiments involving PANOA-based acidifications, providing a configuration with a sample volume of ca. 0.6 µL. The optimized PANOA (as described below; Table 1) was electropolymerized over three different potential windows in succession for cyclic voltammetry (CV); –0.2–1.1 V, –0.2–0.9 V and –0.2–0.8 V, all with a scan rate of 60 mV/s. The PANI-based pH sensor was prepared as optimized elsewhere (–0.05–1.05 V for 10 scans at 100 mV/s) [17]. The pH sensor was calibrated using standards of pH 9.0–1.8 (0.1 M NaCl as background electrolyte; details in the supporting information) inside the microfluidic cell. A typical calibration profile is shown in Figure S1.

Notably, the sample to be acidified is sandwiched between the two electrodes, being confined to a thin-layer domain. This guarantees no mass transport limitation along the sample thickness [30]. In this context, our group has published a model based on the finite element approach to describe the electrochemically controlled release of ions (e.g., H⁺) from a redox-active film (such as PANOA or PANI) into a sample confined to a thin-layer spatial domain [19]. Calculations were found to rather agree with the experimental results regarding the sample thickness influence on the mass transport regime. On the other hand, the pH achieved in the sample plug after the acidification (i.e., once the needed applied potential stops) may be affected by the lateral diffusion of the rest of the sample contained in the microfluidic system. To confirm that this was not the case, an extra step consisting of the pH recording for some time after acidification ceased was added to the experimental protocol (see below). It is here anticipated that we observed that the pH value achieved through the acidification was maintained.

2.2. Instrumentation

All the electrochemical experiments were performed using a PGSTAT204 Autolab potentiostat (Metrohm Nordic AB) and the Nova 2.1.6 software. The pH sensor was operated by measuring the electromotive force (emf) with a high input impedance (10¹⁵Ω), Lawson labs EMF16 Interface (Lawson Laboratories, Inc.). In the spectroelectrochemistry experiments, absorbance spectra were collected using an Avantes ULS2048CL spectrometer with AvaLight-DHc as light source (Avantes) coupled with fiber optics (M92L01, Thorlabs). The pH of the standards used for the calibration of the pH sensor were adjusted using 1 M HCl or 1 M NaOH and a 914 pH/Conductometer from Metrohm (6.0228.000).

3. Results and discussion

The concept and working mechanism herein investigated for PANOA-based acidification of thin-layer samples is illustrated in Fig. 2. The principle is based on a thin-layer sample sandwiched between the source of protons (PANOA) and a potentiometric pH sensor, everything configured in a microfluidic cell. The sample is introduced by means of a peristaltic pump. When the sample plug enters the thin-layer space between the PANOA and the pH sensor, the pump is stopped. The pH of the sample is monitored by the sensor, providing a value representing the initial sample pH. The pH is expected to be stable and determined by the buffer(s) concentration(s) (Fig. 2, left). Then, when PANOA is electrochemically activated by an applied potential, it converts into its higher oxidation state, which involves transforming the phenolic groups of the o-aminophenol units in the co-polymer backbone into quinones [23], [28]. Additionally, some conversion of amines into imines may also occur [24]. Both of these structural changes trigger a release of protons from the PANOA to the thin-layer sample, which converts any base (B^–) into its conjugated acid (HB), breaking first the buffer capacity and resulting later in the decrease of the sample pH (Fig. 2, right).

Because of the confined space for the sample, the protons will be largely retained as they can only laterally diffuse in the thin layer, consequently maintaining the lowered sample pH for extended times even after the potential step is finished. Then, by applying a negative potential step to the PANOA, protons in the sample are expected to be re-inserted into the polymer backbone based on its reversible redox mechanism. Thus, in an ideal case, proton exchange with the sample is achievable over numerous cycles. This process, which involves changes in the sample pH, can be followed by the pH sensor placed on the opposite side of the thin layer sample and facing the PANOA. Importantly, once the working mechanism underlying the reversible PANOA-based sample acidification is demonstrated, the pH sensor can be replaced with another sensor (i.e., electrochemical or optical) capable of measuring a pH sensitive analyte, such as a CO₂ optode for DIC detection [21], voltammetric sensor for phosphate detection [18], and potentiometric sensors for anions [31], among others.

According to previous findings by Mu et al. and Holze et al., PANOA’s final structure depends largely on the ratio of monomers (aniline and o-aminophenol) involved in its synthesis [23], [24], [32], [33]. As such, if the aniline:o-aminophenol ratio is too high, a more PANI-like structure is expected because of low accessibility of o-aminophenol in the monomer solution [32]. However, when the aniline:o-aminophenol concentration ratio becomes too low, it inhibits the growth of PANOA [23]. Herein, a ratio of 20:1 aniline:o-aminophenol (200:10 mM) in 0.6 M H₂SO₄ was used for the PANOA electropolymerization, which has been demonstrated to be an adequate condition for producing films that are electroactive at environmental pH values [23]. First, we set out to characterize PANOA using spectroelectrochemical studies, followed by tuning the voltammetric parameters according to its proton exchange properties in the thin-layer cell.

3.1. Spectroelectrochemistry investigation of PANOA

To verify the formation of the PANOA, this was electropolymerized on a transparent ITO electrode while simultaneously recording the absorbance. For this purpose, the experimental setup was based on the spectroelectrochemical cell used in our previous works [16], [34]. Initially, the electropolymerization was performed by CV (from –0.2–1.1 V at 60 mV s^–1 for 20 scans). Some selected scans are presented in Fig. 3a. Notably, the results are analogous to previous studies reporting PANOA formation at the same potential window [23], [35], implying the successful formation of the co-polymer.

Several waves can be observed in the anodic part. Two peaks at 0.25 and 0.38 V, which have been ascribed to the first oxidation state of the polymer chain during its growth [23], [36], including anion insertion into the film [26]. Then, a small peak is observed at ca 0.7 V during the first scan, which corresponds to the oxidation of the phenolic group in acidic conditions [23]. Also, two partly overlapping peaks are found at 0.8–0.9 V, which are ascribed to the second oxidation state of the polymer [26] as well as oxidations of the monomers [23], [26]. After eight scans, two peaks appeared at 0.55 and 0.63 V. Despite these being observed in previous works [23], [37], the origin is not clear yet, resulting in incomplete explanations. Notably, by analogy to PANI and considering that both polymers (PANI and PANOA) present a similar structure, this peak likely originates from degradation products in the hydrolysis of imines in the polymer backbone [38]. In the cathodic part, in the potential window from 0.8 to 0.9 V (i.e., in the region of the second oxidation state of the polymer), there is a small peak at approximately 0.65 V. Then, the first oxidation state relates to three peaks in the potential range from –0.1–0.3 V, instead of the two peaks presented in the anodic part.

The spectra connected to the anodic part of the final scan of the electropolymerization process are presented in Fig. 3b. Different absorbance bands are absorbed in the region from 380 to 530 nm, with small increases in magnitude with the applied potential. This effect is in accordance with previous results about PANOA electropolymerization [33], confirming the formation of the co-polymer. To further analyze the spectroelectrochemical results, the change in absorbance at the absorbance maximum (420 nm) during the anodic scans at PANOA’s reduced state (0 V) and its fully oxidized state (1.1 V) versus the number of scans are presented in Fig. 3c. It was observed that the absorbance at 420 nm increased until the 10th scan, whereafter it remained almost constant. The full spectra during the growth of the polymer are provided in Figure S2. Additionally for each individual scan, the oxidized state always presented a higher absorbance. This behavior contrasts with that found for the current in the voltammetric peaks, where all peaks gradually increased over the 20 scans. Overall, the result in the absorbance suggested that further growth of the molecular structure corresponding to the 420 nm band does not occur after the 10th scan. Interestingly, this ceased increase in absorbance coincides with the emergence of the anodic peak at 0.55 V.

3.2. Optimization of PANOA fabrication via electropolymerization

After the spectroelectrochemical measurements and for further experiments, the ITO electrode substrate was replaced by the Au electrode tip to improve the mechanical stability of the created film. The total number of scans of in the electropolymerization process was increased from 20 (for ITO) to 100–250 for the Au-electrodes. Thus, thicker films were expected in the Au than in the ITO substrate, aiming for a more efficient acidification strategy (i.e., the film will contain a higher number of protons to be delivered from the PANOA to the sample) considering the proof of concept in real water samples [16], [17]. Additionally, having identified in the spectroelectrochemistry results that there is a peak at 0.55 V surely related to the polymer degradation, an even more improved efficiency for the PANOA-sample proton exchange was expected by decreasing the maximum anodic potential used in the CV during electropolymerization. Effectively, thanks to preliminary experiments based on PANI electropolymerization by decreasing the upper limit of the CV potential window from 1.2 to 0.75 V (Figure S3a), it was found out that lowering the anodic potential below 0.9 V translated into the disappearance of the peak at 0.55 V with consecutive scans (Figure S3b).

Next, a systematic study was performed to understand if avoiding the degradation peak at 0.55 V led to an improved electrochemical performance for PANOA films. In essence, we investigated the effect of the upper potential in the growth window for PANOA electropolymerization while keeping constant the scan rate (60 mV/s) and the initial potential (–0.2 V) on the obtained CV (i.e., number of peaks and the related current). The experimental setup used was based on a three-electrode configuration in a beaker. The electropolymerization conditions are listed in Table 1 and the generated PANOA films were classified as PANOA types I, II and III. As justified below, the synthesis of PANOA type II included an initial nucleation step and that for PANOA type III an additional intermediate step that led to improved film growth. For PANOA type III, the number of scans in the growth part was changed, giving rise to the subclasses 1, 2 and 3. Overall, the CVs on Au shared similar peaks as those on the ITO-electrode (Fig. 4).

The trend over the first 45 scans of PANOA type I is illustrated in Fig. 4a. The following differences with the results observed for the ITO electrode. Were found. The first peak shifted to slightly lower potentials (0.23 V) and is initially lower in current magnitude than the second peak at 0.38 V. After 30 scans, the peak at 0.23 V becomes the most prominent. The second oxidation state associated to the two peaks at 0.63 V and 0.75 V, which also has been attributed to PANOA growth [23], exhibited a higher current than the first oxidation state (peaks at 0.23 and 0.38 V) until the 35th scan. The peak at 0.55 V did not appear until the 45th scan, indicating that no degradation occured before this point.

Fig. 4b presents the growth of PANOA type I from the 50th to the 200th scan. After the 65th scan the peaks at 0.23 and 0.38 V start to overlap and are no longer distinguishable, while the peaks at 0.63 and 0.75 V start to overlap with the peak at 0.55 V. Notably, PANOA of type I did not exhibit an increase in peak currents after 150 scans, whereafter the peaks shifted towards higher potentials. This can be likely scribed to two origins; i) an increase in film thickness providing additional resistance [17], and/or ii) the fact that the peak at 0.55 V becomes more pronounced between the 50th and 200th scans may result in film degradation and hence, impaired film conductivity [38], [39].

For PANOA of type II, the anodic limit was lowered to 0.9 V compared to type I, attempting to avoid the peak at 0.55 V. However, the peaks’ currents were found to increase very slowly (data not shown) using this potential window alone, indicating a slow film growth. Thus, a nucleation step of 20 scans between –0.2 and 1.1 V was implemented prior to the regular CV protocol. In such a case, the peak at 0.55 V was not observed (Figure S4a). Subsequently 180 scans between –0.2 and 0.9 V were adapted (Fig. 4c) for a total of 200 scans considering the entire procedure. This was still not sufficient to remove the peak at 0.55 V at the end of electropolymerization. However, PANOA II accumulated a final charge of 21.0 mC, which was more than a three-time-increase compared to PANOA Type I (6.1 mC). Thus, although the potential window was decreased, the amount of charge inserted into PANOA was increased.

Then, the potential window for the CV was fixed from –0.2–0.8 V for PANOA III-1, III-2, and III-3 after the established nucleation (from –0.2–1.1 V, 20 scans). Notably, preliminary tests applying this protocol provided a very slow growth of PANOA (i.e., slow current increase with subsequent scans). Thus, an intermediate step was implemented: from –0.2–0.9 V for 40 scans. Within the 40 scans, the peak at 0.55 V has not appeared yet (Figure S4b). Thus, the third strategy for the PANOA synthesis comprised three steps: i) nucleation step (CV from –0.2–1.1 V, 20 scans), ii) intermediate step (CV from –0.2–0.9 V, 40 scans), and iii) growth step (CV from –0.2–0.8 V for 190, 90 or 40 scans to obtain PANOA III-1, III-2, and III-3, respectively). The progression of the final step is presented in Fig. 4d. The main differences considering PANOA I and II (Fig. 4a-c) is that the peak for the second oxidation state (0.74 V) is still visible at the end of the electropolymerization.

This becomes more evident when comparing the last CV in the growth part for PANOA I, II and III (of any subclass), which are displayed in Fig. 4a-d and Figure S4c. It can be observed that PANOA III-1 (with the higher number of scans in the growth part) presented the peak at 0.74 V corresponding to the second oxidation state, and the peak at 0.33 V (Fig. 4d) did not shift as much as it does in PANOA I and II, which suggests a lower degree of degradation in PANOA III. Lowering the upper potential in the growth window further could perhaps be an option to avoid the peak at 0.55 V completely but would also decrease the rate of growth.

Comparing PANOA III-1, III-2 and III-3, the one that presented final current levels much closer to that displayed for PANOA I and II was PANOA III-1. Moreover, an extension in the number of scans from 200 to 250 for PANOA III-1 was considered because, unlike PANOA I and II, the voltammetric peaks were still increasing for each scan after 200 scans. This increase in current magnitude for each scan was suggesting that the film thickness was still growing. On the other hand, PANOA Type III-2 and III-3 presented lower peak currents at the end of their formation, but the shape of the CV are more similar to that claimed as characteristic for PANOA [23], [35], with the peak at 0.55 V being far less pronounced than in the case of all the other PANOA types.

Overall, it can be concluded that limiting the upper potential for the electropolymerization window avoids PANOA degradation to some extent but, at the same time, it restricts the rate of growth (considering the increase in peak currents). Accordingly, the optimal conditions to be selected are expected to be a compromise between degradation and growth effect providing the best proton exchange capacity that can be held by PANOA (i.e., sites to store protons in the co-polymer backbone).

3.3. Investigation of PANOA acidification capacity

To quantify the proton exchange properties of the different PANOA types and the reversibility of the process, we introduced the corresponding PANOA-Au electrode into the microfluidic thin-layer sample cell (Fig. 1), where the sample pH could be continuously monitored by the potentiometric pH sensor. The experimental protocol to induce electrochemical pH modulations in the sample together with the expected readout from the pH sensor are presented in Fig. 5a and b respectively. This consists of: (1) initial reading of the open circuit potential (OCP) by the potentiostat and the potentiometer with the pH sensor; (2) acidification step by applying the +0.4 V for 300 s to the PANOA electrode; (3) passive monitoring step at the OCP for 60 s; and (4) PANOA regeneration step at –0.2 V for 600 s. All these steps were performed in the same sample plug (i.e., with the pump turned off). Importantly, the acidification potential was selected to be 0.4 V to avoid being closer to potentials inducing secondary processes beyond proton release that may contribute to increase the charge released from PANOA and even its degradation. A similar strategy was followed in our previous papers involving PANI [16], [17].

Figure 5. Illustration of the protocol and outcomes for electrochemically modulated acidification and regeneration with the expected outcomes. (a) The protocol for the potentiostat. (b) The potential readout from the potentiometer. (c) The dynamic pH changes in the sample. In essence, the following steps and readouts apply to a general case: (Step 1, ca.60 s) OCP measurement with no change in the pH (i.e., constant EMF of the pH sensor). (Step 2, 300 s, acidification) Application of a constant positive potential with the simultaneous monitoring of the decreasing pH (i.e., increasing EMF in the pH sensor). (Step 3, 60 s, holding of the acidified pH in the solution) OCP measurement (ideally, the pH reached in step 2 is maintained). (Step 4, 600 s, regeneration) application of the regeneration negative potential for a double time of that in the acidification step, and with the simultaneous monitoring of increasing pH (i.e., decreasing EMF in the pH sensor), ideally increasing up to the initial pH of the sample.

Initially, when no potential is applied in step 1, a constant readout from the potentiometer was expected, which corresponds to the initial pH of the sample. Then in step 2, the PANOA is activated at the +0.4 V for 300 s, triggering the release of protons from the film to the sample. This causes a response from the pH sensor because of the pH shift in the thin-layer sample. Fig. 5c additionally illustrates the dynamic change in pH expected in the sample: from the initial pH to an acidified pH and finally coming back to the initial pH because of the regeneration step. In step 3, the applied potential was switched off and the pH readout was recorded in the thin-layer sample for 60 s, expecting the pH to be constant and equivalent to the level of acidification achieved by the actuator (always that there are not diffusion related uniformities in the process). In step 4, the PANOA is regenerated in the same sample plug: proton uptake from the acidified sample thanks to the application of –0.2 V for 600 s. This step causes the sample pH to return to its original value. Regarding the time of 600 s, according to the pH monitoring in numerous experiments, it was found that shorter times did not allow for a complete regeneration of the PANOA (meaning that the initial sample pH was not recovered), and longer times did not improve the regeneration efficiency. Then, after the regeneration, the peristaltic pump was turned on for 5 – 15 minutes to exchange the sample plug for further experiments.

The repeatability of the results provided by this protocol was first tested on PANOA type I in 0.1 M NaCl sample solution, accomplishing five consecutive cycles of pH modulation. Fig. 6a depicts the dynamic pH that was observed. The first three cycles reached an acidified pH of 3.11±0.11; whereafter, a decrease in the acidification capacity was observed (pH of 3.77 and 4.91 for the fourth and fifth acidifications respectively). Notably, this final pH was calculated as the average pH value shown during step 3 (i.e., no applied potential, just measuring the pH for 60 s after acidification, when the sample just holds the acidified pH). This criterion was used through the paper. The described behavior coincided with a progressive change in the current profiles associated to each proton release (Figure S5a, charge of 3.28±0.84 mC). Moreover, the regeneration step for taking up protons was also found to become less efficient in consecutive cycles (Figure S5b, charges of –3.84±0.95). These trends also manifested in an overall decrease in charge for both the delivery and regeneration steps (Figures S5c-d): for the second to fifth cycle of acidification, the charge was decreased from 4.25 mC to 1.80 mC and the decrease was 57.6 %; for the first to fifth cycles of proton uptake process, the charge was decreased from –4.82 mC to –2.2 mC, decrease in 54.3 %. Inspecting the pH acidification with the corresponding current profile for the first and fourth cycles, which are those displaying the biggest differences, some conclusions can be established. As observed in Fig. 6b, the first current transient displayed a Cottrell-like profile, while the fourth one displayed an initial fast decay and then the current slowly increased, therefore displaying a peak. For the first acidification, the decrease in pH was initiated within the first 15 s after activating the potential step. On the other hand, the fourth acidification displayed a considerable delay (ca. 100 s) before a decrease in pH was observed, which interestingly coincided with the peak in the current profile. This may imply that such a peak is closely related to the process of releasing protons from PANOA type I. However, because of the poor repeatability in both the acidification and charge delivery profile (i.e., electrochemical performance), we averted from further studies into this process, because PANOA type I was concluded not suitable for reversible pH modulations.

Figure 6. (a) Consecutive pH modulations using PANOA type I in 0.1 M NaCl solutions. The gray areas represent the times of acidification. (b) Chronoamperometric curves with overlapping pH-time profiles for the 1st and 4th acidification cycles. pH modulations were performed by applying +0.4 V for 300 s, followed by a 60 s waiting period where the pH was passively monitored and then, a regeneration step of –0.2 V for 600 s. The steps of the experimental protocol as described in Fig. 5 are indicated. Notably, the regeneration part has been shortened up for simplicity.

The results for the repeatability study of PANOA type II are presented in Fig. 7a, revealing ∆pH=2.82±0.06 for eight cycles (ΔpH=2.96±0.18 for the first 3 cycles). Effectively, the overall electrochemical performance was found to improve with respect to PANOA type I, but again showing some differences within increasing number of cycles (Figure S6). As observed in Figure S6a, the current for the first acidification is lower than subsequent pH modulations and displays no peak in the dynamic current profile. The increase in the current magnitude from the first acidification and the latter ones can be explained from a decrease observed in the OCP: 0.080 V for the first and –0.139±0.012 V for the subsequent cycles. In essence, because the potential step is larger from –0.139 V to 0.4 V than from 0.080, more charge is expected to be generated in the PANOA. Despite the mentioned differences in the current profiles, only small variations were found in the corresponding charges (4.69±0.13 mC, excluding the first acidification; Figure S6b). In addition, the pH measured in the regeneration step was found to always return to a pH very close to the initial sample pH, also displaying very similar current profiles and acceptable reproducibility in terms of charge (–4.89±0.20 mC, Figures S6c and S6d).

Figure 7. Successive cycles for sample acidification based on different types of PANOA. (a) PANOA type II in 0.1 M NaCl. (b) PANOA type III-1 in 0.1 M NaCl. (c) PANOA type III-2 in 0.5 mM NaHCO3 with 0.1 M NaCl as background electrolyte. pH modulations were performed by applying +0.4 V for 300 s, followed by a 60 s waiting period where the pH was passively monitored and then, a regeneration step of −0.2 V for 600 s. The gray areas represent the times of acidification.

With an acceptable electrochemical and pH modulating performance confirmed for 0.1 M NaCl solution, PANOA type II was further tested in a buffered solution (0.5 mM NaHCO₃/0.1 M NaCl). The operational performance in higher, buffered pH is interesting to be evaluated in terms of PANOA usability in environmental waters and physiological conditions. However, it was found that the pH modulation using PANOA type II was not reversible under these conditions (Figure S7). Triplicate measurements revealed a successful first pH modulation, shifting the pH from the initial value of 7.6 to below 4 at the end of the acidification. But, in subsequent pH modulations, the pH was unable to be shifted below 6.5. This motivated the development of the PANOA type III and its subclasses, to provide an electrochemically induced pH actuator that is reversible at higher pH values.

The repeatability of the pH modulation induced by PANOA type III-1 in 0.1 M NaCl was found to be higher and more efficient than PANOA type II when tested in unbuffered conditions. An acidification of ∆pH=3.12±0.19 over seven cycles (Fig. 7b), with charge deliveries of 6.43±0.53 mC and –6.82±0.49 mC for the acidifications and regenerations (Figure S8) were revealed. Moreover, this proper performance was additionally accompanied by an improved repeatability in 0.5 mM NaHCO₃ (with 0.1 M NaCl as background electrolyte), reaching final pH values of 3.4, 3.7 and 4.1 in consecutive acidifications (initial pH=7.5; Figure S9a). Yet, the decreasing trend within each subsequent acidification in unbuffered conditions motivated the development of the PANOA type III-2 and type III-3 subclasses, which showed excellent repeatability in buffered media (Fig. 7c and Figure S9b for type III-2 and type III-3, with average charges of 2.66±0.17 mC and 2.92±0.13 mC, respectively).

The overall improvement over all tested PANOA types is summarized in Fig. 8 for all tested samples; 0.1 M NaCl (blue), 0.5 mM NaCO₃^–, and seawater (discussed in detail in the next section). The corresponding pH values are provided in Table S1 in the Supporting Information. The horizontal lines indicate the average starting pH over all measurements for the corresponding samples, the bars extending from the starting pH give the magnitude of the acidification and their average final pH, and the error bars provided the standard deviations for the measurements. Indeed, the subclasses of both PANOA type III-2 and III-3 behaved roughly the same, where both provided improved acidification-capacities and repeatability compared to types I, II and III-1 for both unbuffered (Fig. 8, blue bars) and buffered samples (Fig. 8, orange bars). By comparing the preparation protocols (Table 1) and the CVs in Fig. 4 with the acidification results, the following can be concluded. By limiting the formation of the degradation peak at 0.55 V, the acidification capacity (i.e., decrease in pH) increases, and the repeatability (standard deviation) decreases indicating an improvement in reversibility of the proton release from the PANOA film.

3.4. pH modulation of seawater samples using PANOA as an electrochemically driven actuator

Considering the superior efficiency and reversibility of the proton exchange from the PANOA Type III-2 and Type III-3 compared to the other PANOA types, we further tested their performance in a seawater sample (collected at Torrevieja, Spain, Supporting Information). Three subsequent acidifications/regenerations were tested. Notably, the applied potential was changed to 0.45 V for acidification and –0.15 V for regeneration to adjust for the higher chloride concentration (ca. 0.6 M) in seawater, which shifts the reference potential by approximately 50 mV compared to the artificial samples containing 0.1 M NaCl as the background electrolyte (with or without buffer). The sample’s pHs measured before and after acidification are presented in Fig. 9. The dynamic pH-time profiles are additionally provided in Figure S10. As observed, the acidified sample presented a pH value that increased with the number of cycles, while the pH obtained after the regeneration decreased. Averages values of 3.19±0.67 and 3.67±0.35 were respectively found for PANOA Type III-2 and PANOA Type III-3 (yellow bars Fig. 8), indicating that PANOA III-2 has a slightly higher capacity for acidification than PANOA III-3. Overall, the proton exchange efficiency was mitigated with the number of cycles, an effect that was not noticed in the buffered samples used in the previous section. The higher complexity of the sample matrix together with the higher buffer capacity (alkalinity=2.47±0.04 mM, details in the Supporting Information) may indeed affect the PANOA’s proton exchange properties.

To extend the number of uses of the PANOA film, a more drastic regeneration procedure was investigated. Thus, after the three consecutive pulses, an acid solution (10 mM H₂SO₄/0.1 M NaCl) was pumped into the cell and a potential of –0.2 V was applied for 600 s. Thereafter, the seawater sample was re-introduced in the microfluidic cell, and four consecutive acidification-regeneration cycles were performed. The regeneration step in acid solution was found to significantly increase the acidification capacity of the PANOA films, which was more pronounced for PANOA Type III-2 than PANOA Type III-3, with final pHs of 2.2, 2.6, 2.9 and 3.2 versus 3.1, 3.5, 3.7 and 4.1.

These results are indeed relevant in view of the further application of the PANOA as an acidification actuator for environmental monitoring purposes. When acid-based regenerations are possible to implement, the use of PANOA Type III-2 is preferred over PANOA III-3 because of its higher acidification capacity. Moreover, it is possible to acidify the sample, run a sensor-based measurement (i.e., with the microfluidic cell integrating an analytical sensor instead of the pH one, which only means to monitoring the acidification-regeneration process in this study), and a regeneration step using the same sample for many successive cycles (at least 4). This option drastically reduces the need for acid solutions compared to traditional manual/automatized acid additions, empowering the greener perspective of the developed concept.

The frequency selected for introducing the acid for regeneration will then depend on the pH threshold required for the analytical application. Other option, which could be adopted depending on the final pH desired in the sample after acidification, is the sole use of the acidified sample for the regeneration. Some pH values to be considered as examples would be 4.5 to detect dissolved inorganic carbon [21], and 4.8 for the total sulfide detection [40], both attainable without using acids in the regeneration step. Although PANOA Type III-2 was found to be capable of lowering the pH more than PANOA Type III-3, the latter generates more charge, as obtained in the integration of the current-time curves (Figure S11). The higher charge output is likely because of that the thinner film avoids the degradation peak (0.55 V), which allows the polymer to maintain its conductivity and capacitance compared to thicker films. Additionally, it is likely that all charge generated does not correspond to protons, but also other processes such as anion-insertion into the PANOA [25], and different relaxation processes of the polymer [41].

3.5. Performance comparison between PANOA- and PANI-based acidification

The use of PANI has been recently demonstrated for the successful reagentless acidification of environmental samples. Thus, we performed a series of additional experiments to compare the performance of PANOA and PANI, investigating the reversibility and efficiency of the proton delivery/uptake from PANI. The PANI film was prepared with previously optimized voltammetric parameters (1.1 V for 10 s, followed by –0.35–0.85 V at 100 mV/s) [17], [18], [19], [20], [21], with 200 scans of electropolymerization (Figure S3b) resulting in a film thickness of ca. 350 µm. The spacer in the electrochemical cell was adjusted to assure that the thin-layer thickness would remain approximately constant and like that used for the PANOA films (details in Section 3 in the Supporting Information). Then, compared to already published investigations with PANI, the acid-based regeneration step normally conducted in 10 mM H₂SO₄ [17], [18], [19], [20], [21], was substituted using the acidified sample plug, to be comparable with the experimental conditions herein established for PANOA.

The results for 5 acidification-regeneration cycles are displayed in Fig. 10. A poor reversibility of the proton exchange was observed in 0.1 M NaCl sample solution, with a dramatic decrease in the acidification capacity over the five scans (final pH values of 3.3, 4.4, 4.8, 5.0 and 5.2). Accordingly, PANI exhibited excellent reversibility when regenerated in an acidic solution with a pH lower than 2 (10 mM H₂SO₄ solution) [16], [17]. The regeneration pH significantly influences the conversion of PANI to its protonated state. In this experiment, using a non-acid-based regeneration step, the lowest achieved pH was 3.3. This pH level was not sufficient to fully convert PANI to its protonated state, demonstrating that non-acid-based regeneration is not suitable to ensure successive acidification. On the other hand, the charge delivered by PANI was found to be ca. 10 times higher than for PANOA, and quite constant over all the pH modulation cycles (26.8±1.4 mC for the acidifications and –32.2±0.35 mC for the regenerations), as observed in Figure S12. This suggested that PANI would indeed be capable of delivering a superior charge compared to PANOA, although all of this charge is not expected to be correlated to the release of protons but also anion-exchange processes [17], [42]. But, if more protons are needed for the specific application, PANI can be grown thicker by increasing the number of scans or subsequently adjusting the potential window during its electropolymerization without observing the degradation peak observed for PANOA (0.55 V) [17], [21]. However, all these strategies will always accompanied by an acid-based regeneration step in contrast to PANOA.

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4. Conclusion

An electrochemical method for reversible pH modulations in thin layer samples (<100 µm thickness) was herein presented using the electropolymerized copolymer between o-aminophenol and aniline PANOA. The outcomes demonstrated the relevance of the electropolymerization strategy towards achieving optimal proton-coupled redox properties from the material. Specifically, by limiting the maximum anodic potential to 0.85 V and number of cyclic scans to ≤150, optimal pH modulation capabilities were observed, as quantified by in-situ potentiometric measurements of the pH inside the thin-layer sample (volume of 0.6 µL; defined by a 3D-printed microfluidic cell). It was found that the optimized PANOA film can consistently acidify samples (artificial and real seawater) to pH 2–4 within 3 min by purely electrochemical means and without addition of reagents to the sample. Such a pH is indeed suitable for the sensing of certain environmental markers, such as dissolved inorganic carbon and dissolved inorganic phosphate.

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References

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C. Chen, A. Wiorek, A. Gomis-Berenguer, G.A. Crespo, M. Cuartero, Portable all-inone electrochemical actuator-sensor system for the detection of dissolved inorganic phosphorus in seawater, Anal. Chem. 95 (8) (2023) 4180–4189, https://doi.org/10.1021/acs.analchem.2c05307.
A.F. Molina-Osorio, A. Wiorek, G. Hussain, M. Cuartero, G.A. Crespo, Modelling electrochemical modulation of ion release in thin-layer samples, J. Electroanal. Chem. 903 (2021) 115851, https://doi.org/10.1016/j.jelechem.2021.115851.
F. Steininger, A. Wiorek, G.A. Crespo, K. Koren, M. Cuartero, Imaging sample acidification triggered by electrochemically activated polyaniline, Anal. Chem. 94 (40) (2022) 13647–13651, https://doi.org/10.1021/acs.analchem.2c03409.
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3D printing paves the way for epifluidic devices with a skin-interfaced microfluidic device for sweat capture

August 13, 2025April 17, 2024 by CadWorks3DAdmin

3D printed epifluidic devices called the Sweatainer. Developed by the Ray Research Group.

The Tyler Ray team at the University of Hawai’i at Manoa harnesses the CADworks3D Pr110-385 printer and Clear Microfluidic Resin to establish a unqiue class of epidermal microfluidic device, called a ‘sweatainer.’ This device represents a groundbreaking advancement in the collection and analysis of sweat samples.

3D printing paves the way for epifluidic devices with a skin-interfaced microfluidic device for sweat capture and analysis

Wu et al. (2023) capitalizes on the recent advances in additive manufacturing to fabricate an epidermal microfluidic device (or epifluidic device), incorporating complex designs that were previously inaccessible.

The team has produced the sweatainer, a skin-interfaced wearable system with integrated microfluidic structures, and sensing capabilities to monitor signals arising from natural physiological processes. It enables a new mode of sweat collection termed multidraw. Multidraw facilitates the collection of several independent and pristine sweat samples during a single collection period. The realization of multidraw sweat collection, enabled by customizable design through 3D printing, represents a major step forward in the field of sweat-based analysis.

HOW WAS THE CADWORKS3D SYSTEM USED?

Clear Microfluidic Resin

Pr110-385 3D Printer

Professional CureZone

The complete sweatainer system is made up of two primary components: the 3D printed sweatainer device and the epidermal port interface.

The 3D printed sweatainer was fabricated with the CADworks3D Pr110-385 printer and Clear Microfluidic Resin material. This portion of the device was produced in a single print job. It consists of a microfluidic network of internal channels and valves, as well as unsealed reservoirs with integrated ventilation holes.

Other structural components of the complete device, independent from the 3D printing process, include a layer of PDMS to cover and seal the reservoir, and a biomedical adhesive gasket to bond the the printed device and PDMS layer together.

Together, they form a complete and closed microfluidic structure. Sweat enters the device by a central inlet and flows through a microfluidic channels leading to a series of capillary burst valves (CBVs) and corresponding reservoirs. The CBV at the ingress of each reservoir permits fluid flow only after exceeding a set pressure, thereby enabling time-sequential sweat collection. Integrated ventilation holes (width: 100µm and height: 200µm) on the reservoir eliminates the back pressure that would evolve from trapped air and impede flow. The high-barrier properties of the Clear Microfluidic Resin supports a low sweat evaporation rate with minimal mass loss over a 24-hour period. More details about the fabrication of the sweatainer can be found in the full article.

KEY TAKEAWAYS

Building Complex 3D Geometries

Typical epifluidic devices use soft lithography techniques to build microfluidic components and complex geometries. It requires high-precision molds to form patterned layers of an elastomeric material, commonly PDMS, that when bonded to a substrate yields a complete sealed device.

However, producing such molds with sufficient feature resolution is an expensive and time-consuming process that requires access to specialized environments like clean rooms. Moreover, soft lithography restricts the design space of devices to planar (2D) channel configurations. Although lamination of multiple channel layers can yield elaborate 3D microfluidic networks, each component layer is inherently a planar geometry. Aligning these layers are both time- and labor-intensive. Such requirements result in an elongated iterative design cycle, inequitable access to necessary equipment, and additional challenges for commercial deployment due to incompatibilities with large-scale manufacturing.

3D printing emerges as an attractive alternative to conventional planar (2D) fabrication methods. It is a rapid and cost-effective process, offering powerful capabilities for producing monolithic devices with fully encapsulated 3D structures and spatially graded geometries. As aforementioned, the study show cases this with their sweatainer that incorporates several features including channels, CBVs, reservoirs and ventilation holes.

Wu et al. (2023) identified a number of key benefits as a result of the 3D printing process. For example, the printed CBVs demonstrated finer control over resultant burst pressure in comparison to planar CBVs. In a similar manner, the ability to create spatially graded geometries improved sweat collection efficiency by permitting a continuous transition between the microfluidic channel and reservoir.

Optimization of Print Parameters

The detailed optimization of print parameters of the Pr110-385 3D printer and Clear Microfluidic Resin, played a pivotal role in achieving the key outcomes of this innovative platform.

The software provided with every CADwork3D printer offers direct control over a number of print parameters which can be altered for each file. The print parameters can include layer curing times, layer height, dose, and lamp power just to name a few. In the study, the research team systematically optimized the layer cure times and layer height to achieve; robust and accurate channel dimensions, feature sizes below 100µm, and effective mechanical performance.

Moreover, certain CADworks3D printers, including the Pr110-3855 supports variable slicing. Variable slicing enables users to change curing time depending on the layer being printed. This allowed the team to make the most of the Clear Microfluidic Resin, achieving enhanced optical transparency in channels. This transparency was vital for supporting colorimetric analysis using chemical reagents.

CONCLUSION

With the realization of multidraw sweat collection, the sweatainer platform represents a pivotal advancement in the field of sweat-based analytics. Utilizing 3D printing as their key fabrication technology nurtured novel, highly customized geometries and streamlined integration into clinical workflows with it’s rapid iterative design cycles.

Controlling bead and cell mobility in a recirculating hanging-drop network

January 16, 2026November 12, 2023 by CadWorks3DAdmin

Controlling bead and cell mobility in a recirculating hanging-drop network

Nassim Rousset , Martina de Geus , Vittoria Chimisso , Alicia J. Kaestli , Andreas Hierlemann and Christian Lohasz

Integrating flowing cells, such as immune cells or circulating tumour cells, within a microphysiological system is crucial for body-on-a-chip applications. However, ensuring unimpeded recirculation of cells is a significant challenge. Closed microfluidic devices have a no-slip boundary condition along channel walls and a defined chip geometry (laminar flow) that hinders the ability to freely control cell flow. Open microfluidic devices, where the bottom device boundary is an air–liquid interface (ALI), e.g., hanging drop networks (HDNs), offer the advantage of an easily-actuatable fluid-phase geometry, where cells can either flow or stagnate. In this paper, we optimized a hanging-drop-integrated pneumatic-pump system for closed-loop recirculation of particles (i.e., beads or cells). Experiments with both beads and cells in cell culture medium initially resulted in particle stagnation, which was suggestive of a pseudo-no-slip boundary condition at the ALI. Transmission electron microscopy and dynamic light scattering measurements of the ALI suggested that aggregation of submicron-scale cell-culture-medium components is the cause of the pseudo-no-slip boundary condition. We used the finite element method to study the forces on particles at the ALI and to optimize HDN design (drop aperture) and operation (drop height) parameters. Based on this analysis, we report a phase diagram delineating the conditions for free flow or stagnation of particles at the ALI of hanging drops. Using our experimental setup with 3.5 mm drop apertures, we conducted particle flow experiments while actuating drop heights. We confirmed the ability to control the flow or stagnation of particles by actuating the height of hanging drops: a drop height over 300 μm led to particle stagnation and a drop height under 300 μm allowed for particle flow. This particle-flow control, combined with the ease of integrating scaffold-free organ models (microtissues or organoids) in HDNs, constitutes the basis for an experimental setup enabling the control of the residence time of single cells around 3D organ models.

We kindly thank the researchers at ETH Zürich for this collaboration, and for sharing the results obtained with their system.

Introduction

Designing microfluidic devices for cell culturing, especially multi-tissue cultures, has led to approaches that interconnect 2D or 3D cultures of different cell types (tumour, brain, liver, heart, etc.) through microchannels in a physiologically relevant combination and ratio.1 These microphysiological systems (MPSs) are often considered the next step in preclinical research toward more comprehensive and physiologically relevant in vitro testing systems.2,3 The interest in MPSs is mainly based on their potential to better predict the effect of compounds on processes in the human body4,5 and to better understand – in a more systemic way – how different healthy and diseased organs interact with each other3,6,7 when compared to traditional preclinical in vitro models. The potential applications of MPSs include pharmaceutical research and compound testing,8 basic research on tissue and cell interaction,9 and disease progression studies.10

One of the current challenges for MPS applications is the interaction between solid tissues and suspended cells, e.g., circulating tumour cells or immune cells. Such interaction studies are particularly interesting to, for example, mimic immunotherapeutic approaches,9 and recapitulate the interaction dynamics of circulating tumour cells11 and immune cells12 with other organs. Some strategies rely on a static interaction between cell suspensions surrounding solid tissues,13 ignoring the physiological behaviour of immune cells that migrate toward and around their target.14 Hydrogel-based approaches can generate stable signalling gradients that may guide the migration of immune or tumour cells.15 However, these approaches ignore the circulatory nature of immune cells that move around due to blood flow.

To enable the interaction between suspension cells and a series of immobilized tissue constructs, a liquid-phase transport system is needed. However, emulating a circulatory system with microfluidics is not trivial, as it requires flowing single cells that interact with a static organotypic tissue model over several days. Furthermore, a closed-loop recirculation of cells is crucial for the build-up of relevant concentrations of signalling molecules, e.g., cytokines and chemokines, and appropriate tissue/suspension cell interaction.9 Recent advances in achieving cell recirculation have been demonstrated,9,16 but have yet to meet the requirement of maintaining stable and long-term cell recirculation. The requirements of efficient cell recirculation are (i) minimizing cell/microfluidic structure interactions, (ii) minimizing cell stagnation, and (iii) minimizing cell agglomeration in larger chambers that are used to host tissue models.

Open microfluidic systems – such as hanging-drop networks (HDNs) – are particularly suited to meet the requirements detailed above.17 HDNs feature hanging drops, interconnected through microfluidic channels (Fig. 1a). Tissue models can be immobilized and cultivated within the individual drops, while fluid flow through the channels is used to establish inter-tissue communication through various signalling molecules. A key feature of such open systems is an air–liquid interface (ALI). ALI in this manuscript does not refer to epithelial cells exposed to air but to the interface between an air and a liquid phase. The ALI largely reduces the interaction between cells and microfluidic channel structures – e.g., SU-8 or polydimethylsiloxane (PDMS) – and that allows for direct optical access to the tissue and cell models with an inverted microscope (Fig. 1b). Additionally, the ALI in open microfluidic systems provides ample oxygenation, which reduces the risk of hypoxia-related cytolytic and migratory activity of immune cells, as well as cell death.18 An open microfluidic system also enables free liquid flow, where no stress is present at the ALI. The no-stress ALI boundary gives full control over the drop height (Fig. 1b) during an experiment. Free liquid flow also ensures continuous cell flow through the system due to the slip boundary condition (Fig. 1c) at the ALI. In contrast, free cell flow is not guaranteed within closed microfluidic systems, where the no-slip boundary condition at channel walls and rigid structures reduces the flow velocity (flow velocity is null at the walls), which gives only little freedom with chip operation and causes cell aggregation upon recirculating cells (Fig. 1d).

Fig. 1 Cell-mobility control scheme. (a) Schematic representation of a hanging-drop network (HDN) featuring four hanging-drop structures with in- and outlet drops at either end. (b) Colinear-to-flow cross-section of a typical hanging-drop compartment unit of an HDN. A hanging drop is connected to the network through microfluidic channels. The aperture (2a) of the drop is a design-defined constant. The height (h) of the drop can be controlled during an experiment. The air–liquid interface (ALI) is the key feature of HDNs, giving a slip boundary condition. (c) Visualization of the flow-velocity profile through an open microfluidic system. No stress is present at the ALI, which results in a slip boundary condition, where the flow velocity is maximal at the ALI. The slip boundary condition allows for unimpeded cell (orange) flow over time, even as cells settle due to gravity. (d) Visualization of the flow velocity profile through a closed microfluidic system. The no-slip boundary condition, caused by stiction of the outermost liquid-phase layers to the channel boundaries, sets the flow speed to zero. This may cause cells to stagnate and stick to the channel wall surface, particularly at the bottom where they settle due to gravity.

An HDN enabling closed-loop recirculation of fluids has been developed and validated in our laboratory.19 A unidirectional flow was achieved with an integrated-pump concept developed specifically for microfluidic HDNs. Here, we show a novel iteration of the device, which is aimed at flowing cells in a closed loop and controlling their interaction time with microtissues.

Preliminary tests with beads showed an unexpected behaviour. The slip boundary condition allowed for successful bead recirculation within de-ionized water. However, we observed a no-slip-like stagnation of particles (cells and beads) during recirculation within cell culture medium.

Mathematical modelling of the ALI as a slip or no-slip boundary with the finite element method (FEM) helped to explain this unexpected no-slip-like stagnation. The FEM is a widely used tool to model, predict, and characterize fluid dynamics within microfluidic chips. This modelling technique allows for computing hydrodynamic forces on spherical objects.20–22 We computed the forces on particles at the ALI, while varying operational parameters – e.g., drop height – and design parameters – e.g., drop aperture – for a set of defined experimental conditions.

The aim of this study was to investigate the forces on and behaviour of beads at the ALI as a surrogate for cell behaviour, which we thereafter confirmed experimentally with cells. Our goal was twofold: on the one hand, we wanted to find conditions where particles can freely recirculate within our device, despite the unexpected stagnation; on the other hand, we wanted to control particle stagnation in order to modify particle residence time in the hanging drop at will. Our theoretical and experimental findings suggest that, although the no-slip behaviour of liquid at the ALI is anomalous in cell culture media, careful experimental design can still enable unimpeded particle flow.

Experimental

Flowing particles

The flowing beads were 8.0 ± 0.1 μm-diameter and 1.05 g cm−3-density polystyrene beads (Sigma-Aldrich, Buchs, Switzerland). They were suspended in de-ionized water or cell culture medium depending on the experiment.

The flowing-cell model used here was THP-1 (TIB-202; ATCC, Manassas, VA, USA), a human acute monocytic leukaemia cell line. THP-1 cells were cultured according to ATCC protocols and maintained in RPMI-1640 (PAN-Biotech GmbH, Aidenbach, Germany), supplemented with 10% foetal bovine serum (Sigma-Aldrich, Buchs, Switzerland) and 1% penicillin and streptomycin (Sigma-Aldrich, Buchs, Switzerland). The cell culture medium was filtered through a 0.2 μm-pore-sized filter (Thermo Fisher Scientific, Waltham, MA, USA) to ensure fibre-, aggregate-, and contaminant-free culture and microfluidic HDN operation. Cells were cultured in non-adherent flasks (Greiner Bio-One, Frickenhausen, Germany) at 37 °C, 5% CO2, and 95% humidity. Cells were subcultured every 2 to 3 days at a ratio of 1[thin space (1/6-em)]:[thin space (1/6-em)]5 to maintain a density of 0.2–1 × 106 cells per mL. Cell-culturing density was kept at these levels to ensure spherical cell morphology, because higher densities were shown to alter cell morphology.23

Device fabrication

The fabrication process of the microfluidic device was identical to that of our previously published device19 with two PDMS (Sylgard 184, Dow Corning GmbH, Wiesbaden, Germany) layers – a microfluidic and a pneumatic layer – and a glass substrate to ensure device stability. A micrograph of the fabricated device is shown in Fig. 2a and b. A schematic illustration of the chip layout is shown in Fig. 2c–e.

Fig. 2 Hanging-drop network microphysiological system with on-chip pump drops for particle recirculation.

Picture of the recirculating hanging-drop network (HDN) filled with blue ink showing (a) the air–liquid interface and (b) the transparent slide with inlets and a digitally inserted highlight of pneumatic chambers. The fabricated chip consists of 2 PDMS layers: (c) a 750 μm-thick microfluidic network layer and (d) a 5 mm-thick pneumatic channel layer. (c) Schematic of the microfluidic layer of the recirculating HDN. A 2 × 3 on-chip pump drop setup, highlighted in orange at the top, increased the flow rate within the device. Four culture drops, highlighted in green at the bottom, enabled flowing-cell analysis and could accommodate tissue co-culturing. The sample inlet enabled the introduction of a cell suspension to the device with minimal chip handling. The height-control inlet enabled the in- and outflow of liquid with a syringe pump to maintain the drop height or actuate it to the desired value. (d) Schematic of the pneumatic layer of the recirculating HDN. The heigh-control, sample, and pneumatic inlets are 0.75 mm-diameter holes. The height-control and sample inlets were punched through to the microfluidic layer. Three pneumatic inlets control three separate pairs of on-chip pump drops (highlighted in white and red in b and in orange in c). (e) Side-view cross-section A (dashed line in c and d) of the device with a hanging drop (dimensions in μm). The side view shows that a 250 μm-thick PDMS layer (part of the microfluidic layer) seals the pneumatic layer. The microfluidic and pneumatic layers were plasma-bonded together (A-labelled dashed line in e). The pneumatic layer was bonded onto a transparent slide (not shown on cross-section) to ensure chip rigidity and optical access to the drops. Upon pressurizing the pneumatic chambers (red-labelled height), the 250 μm thick PDMS layer (black-labelled height) expands into the volume of the drop below. The red-coloured pneumatic chambers were actuated simultaneously and in an alternating pattern with the white-coloured pneumatic chambers. Combined with the integrated valves (yellow structures in c and e), the pumping produced a unidirectional flow (blue arrows in c). The positions of the integrated valves defined the flow direction. All interconnecting channels were 300 μm wide. All microfluidic structures were 500 μm high (blue-labelled height in e).

For the microfluidic layer (Fig. 2c), two masks were used to generate an SU-8 (Microchem Corp., Newton, MA, USA) microfluidic-channel master mould on a silicon wafer. We used a 7[thin space (1/6-em)]:[thin space (1/6-em)]1 PDMS-to-curing agent ratio to ensure stiff and reliable valve operation. For the pneumatic layer (Fig. 2d), one mask was used to generate the cavity master mould on a silicon wafer. We used a normal 10[thin space (1/6-em)]:[thin space (1/6-em)]1 PDMS-to-curing agent ratio for the pneumatic layer. Alternatively, with the aim to simplify the fabrication process, we 3D-printed a mould design identical to the one previously fabricated by photolithographic processes. We used a 3D printer designed for microfluidics (PR110-385, CADWorks3D, Toronto, Canada) with the dedicated “PDMS Mastermold” resin (CADWorks3D, Toronto, Canada) to 3D-print the mould. We used a high-intensity UV post-curing solution (Professional CureZone, Creative CADWorks, Concord, ON, Canada) to ensure proper curing of the resin.

For chip assembly, 0.75 mm diameter inlets were first punched in the pneumatic layer. After aligning and bonding both PDMS layers, 0.75 mm diameter inlets were punched for the sample and height-control drops through to the microfluidic layer. One of two processes was used to bond the resulting PDMS chip onto a supporting slide with 1.2 mm-diameter holes matching the chip inlets, which provided a stiff substrate to suspend the chip in a hanging-drop configuration. Process 1: following plasma activation, we aligned and bonded the PDMS chip onto a glass slide with drilled holes. Process 2: using double-sided tape, we bonded the PDMS chip onto an acrylic slide with laser-cut holes.

Design changes with respect to our previously published device19 included (i) the reduced pitch between culture drops to minimize travel time of the cells and (ii) the addition of height-monitoring drops (Fig. 2c). Two parallel and 3-pumping-drop configurations were designed to increase the flow rate in the device.

Materials

Clear Microfluidics Resin V7.0a

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Pr Series

Flow-rate measurement

Measuring the flow rate was done by imaging the circulating beads in the channel between the height-monitoring drops and the height-control-inlet. Videos were taken at 5 frames per second, and particles were traced manually. The flow rate was calculated by multiplying the average velocity of particles in the channel by the channel cross-section of 0.3 × 0.5 mm2. All experimental images, time lapses and videos were acquired using an inverted wide-field microscope (Leica DMI6000B, Leica Microsystems, Switzerland) with a 10× lens.

Mathematical models

The finite-element method software, COMSOL Multiphysics® v. 5.4 (COMSOL AB, Stockholm, Sweden) was used to model a single hanging drop (Fig. 1b). A full 3D model of the liquid phase of a hanging drop was established using the laminar-flow module to solve the Navier–Stokes equation. The built-in physical properties of water were used for the liquid phase. The boundary conditions were set to “no slip” for the PDMS-water interfaces, constant “inflow” for the channel inlet, constant null “pressure” for the channel outlet, and “slip” (Fig. 1c) or “no slip” (Fig. 1d) for the ALI. We placed and moved, via a parameter sweep, a small particle at the ALI. Parametric sweeps were used to find the flow velocities and pressures for every modelled condition. We elaborate on the sweeping strategy in the “Particle-flow modelling strategy” section of the results. The hydrodynamic force on spherical particles at the ALI was computed by using the built-in reaction force (reacf) operator within COMSOL and summing it over the surface area of the spherical particle.

Transmission electron microscopy

Transmission electron microscopy (TEM) was used to image the nanostructures present at the ALI and in the medium. TEM images were acquired with a Philips Morgagni 268D microscope. Each sample was deposited on a carbon-coated copper grid by gently touching the ALI with the flat side of the TEM grid. The samples were blotted, washed with MilliQ water and negatively stained with 1% phosphotungstic acid (PTA). TEM images were acquired with an acceleration of 90 kV, and each grid was imaged at three different sites.

Dynamic light scattering

Dynamic light scattering (DLS) was used to determine the hydrodynamic radius (DH) of the particles present in the cell medium. The DH was calculated from scattering data collected using the Zetasizer Nano ZSP DLS measurement system (Malvern Panalytical, Volketswil, Switzerland).

The samples were prepared by transferring the content of four hanging drops to 100 μl of MilliQ water, and then analysed. Measurements were performed at 20 °C with non-invasive backscattering (NIBS) technology. Results were directly processed and displayed by the built-in software (Zetasizer software).

Results

Particle-flow characterization

To achieve free flow of suspended particles through an open microfluidic system, we used an HDN composed of a sequence of drops, connected by channels, where each drop acted as a potential tissue compartment (Fig. 2a and b). Perfusion in a closed-loop system was induced by pneumatically actuating integrated on-chip pump drops (Fig. 2c–e) developed in our laboratory.19 Unidirectionality of the flow was achieved with integrated valves actuated through pneumatic inlets (Fig. 2c). This strategy reduced the large dead volume of – and prevented repeated squeezing of cells by – the peristaltic pump mechanism. Such integrated pneumatic pumps have a maximum possible flow rate that is defined by the microfluidic network design.19 A bead or cell suspension can be loaded into the system through the sample inlet in Fig. 2c to be recirculated within the HDN. The drop height and device level can be precisely monitored through height-monitoring drops (Fig. 2c) that were loaded with thin rings.24,25 Height-monitoring drops are positioned at the periphery of the device and fluidic system, thereby allowing to fine-tune the drop height at micrometre-precision prior to and during an experiment. Continuous drop-height control was achieved with an open-source “Droplet Based Microfluidics” software package implemented in YouScope,26 where the focal position of the aforementioned thin ring was kept constant by infusing or removing medium through the height-control inlet (Fig. 2c).

The chip shown in Fig. 2 was used to assess bead and cell mobility in the HDN. The experiments were conducted on an inverted microscope with an incubation box keeping the setup at 37 °C, 5% CO2, and 95% humidity. The chip was prefilled with either de-ionized water or culture medium. The pneumatic lines, set to an air pressure of 40 kPa, were connected to the pneumatic inlets (Fig. 2d) actuating the on-chip pump drops (Fig. 2c). The pump actuation protocol consisted of alternatively actuating the pneumatic inlets, highlighted in red and white (Fig. 2d), and was run for the duration of the experiment. The timing of the pump actuation protocol is ton = 200 ms, toff = 200 ms with a 200 ms delay between the red and white pneumatic valves. This scheme was previously optimized to achieve the highest flow rate possible of 1 μL min−1.19 The drop height of the height-monitoring drops was maintained at 550 μm, per previous protocols,19 by connecting a syringe of de-ionized water to the height-control inlet and by using our feedback controller26 as previously described.24 De-ionized water instead of cell culture medium for height-control was used to avoid changes in medium osmolality through evaporation of water and up-concentration of salts, proteins, and other molecules in the medium. At the start of every experiment, 10 μL of either polystyrene beads or THP-1 acute monocytic leukaemia cells were added to the sample inlet (Fig. 2c) with a seeding density of 0.7–7 × 106 particles mL−1. The effective flow rate of 1 μL min−1 was determined by measuring the average speed of single beads or cells through the channel connecting the height-monitoring drop and the height-control inlet.

First results shown in Fig. 3a indicated that beads in de-ionized water circulated continuously over the course of the experiment. The slip boundary condition at the ALI (Fig. 1b) allowed for rapid recirculation. However, cells and beads in cell culture medium settled to the bottom of the drop and stagnated within a few hours (Fig. 3b). This observed stagnation would be typical of a no-slip boundary condition (Fig. 1c). This behaviour was unexpected, considering that the density and viscosity of our cell culture medium did not deviate significantly from that of de-ionized water.27 This observed stagnation led to the hypothesis that the complex cell culture medium formulation (containing RPMI 1640 and 10% Foetal Bovine Serum – FBS), which includes various salts, amino acids, vitamins, nutrients, and other additives, may change the boundary conditions at the ALI to exhibit a behaviour featuring aspects of a no-slip boundary condition, i.e., a pseudo-no-slip boundary condition. As ALIs have been shown to accelerate protein crystallisation,28 we hypothesized that protein denaturation due to shear and the ALI29 may have caused this unusual hydrodynamic behaviour.

Fig. 3 Observation of cells and beads within the microfluidic hanging drops at a recirculating flow rate of 1 μL min−1.

The drop aperture diameter was 3.5 mm, and the drop height was 550 μm. We highlight 4 particles in each snapshot (red, green, blue, and yellow dots) with their displacement over one frame marked up with arrows. (a) De-ionized water featured rapid bead movement at the ALI over 6 seconds. The snapshots of the bead flow were taken from a 16 h time lapse video. (b) and (c) Cell culture medium featured comparatively slow particle movement over 5 minutes as well as cell (b) and bead (c) stagnation at the bottom of the hanging drop. The snapshots of cell and bead stagnation were taken a few hours into a 19 h time lapse video, which suggested a significantly different hydrodynamic behaviour within the cell culture medium when compared to that in de-ionized water. The time difference between the first and second row was chosen to highlight a comparable displacement. The time difference of 6 seconds for the de-ionized water condition compared to 5 minutes for the cell culture medium condition indicates that particles at the bottom of the hanging drop have a slower movement, and a stronger tendency to form stagnation areas in cell culture medium than in de-ionized water, despite operating the chip with the same recirculating flow rate.

Particle-flow modelling strategy

To investigate the pseudo-no-slip boundary condition, we modelled the forces acting on spherical particles (i.e., cells or beads) at the ALI. Hydrodynamic forces are the only ones that vary between flow in de-ionized water vs. cell culture medium. Therefore, computing the hydrodynamic forces on particles was key to studying cell and bead stagnation. To do so, we computed the flow in the hanging drop with a particle at a given location (Fig. 4a). We used the solution on the particle surface (Fig. 4b) to compute the hydrodynamic force.

Fig. 4 Particle-flow modelling strategy. (a) and (b) show COMSOL simulation results with a slip boundary condition at the ALI. (a) Flow velocity profile (surface plot) and streamline solutions of the flow in the colinear-to-flow middle cut plane of the hanging drop. (b) Zoomed-in view of the square box in figure (a) showing a modelled particle of 8 μm diameter at the ALI. The hydrodynamic force is computed by summing the reaction forces of the flow on the surface (computed with the built-in reacf operator in COMSOL). (c) Schematic of the forces acting on particles at the ALI and (d) superimposition of the modelled net tangential force (white vector field) and its magnitude (coloured contour map) on the experimentally observed stagnation of beads at the bottom of the drop from Fig. 3c. The diameter of the drop in the image is 3.5 mm. The experimental drop height is 550 μm. The experimental flow rate is 1 μL min−1.

Particle free-body diagram. The free-body diagram of a particle (Fig. 4c) shows the forces that come into play when analysing free flow of particles at the ALI of a hanging drop. The externally acting forces are hydrodynamic, gravitational, and normal forces. The hydrodynamic force (Fhyd, green dashed vector in Fig. 4c) is caused by differentials in fluid pressure around the particle caused by the moving flow. The gravitational force (Fg, orange dashed vector in Fig. 4c) includes the weight of the particle and the buoyant force in medium. The normal force (F⊥, purple dashed vector in Fig. 4c) is derived from Newton's third law of motion and is the normal force of the ALI acting on the particle, stopping it from crossing the ALI.

We modelled Fhyd numerically by assuming a worst-case no-slip ALI boundary condition for the experimental results and conditions displayed in Fig. 3b and c. Fg was computed using the density of the particle and the density of the medium. The normal force of the particle on the ALI was computed by projecting the sum of hydrodynamic and gravitational forces on the normal vector of the particle-ALI contact point. F⊥ of the ALI on the particle is the negative of the previously computed force. F⊥ only exists if forces push the particle toward the ALI and is due to surface tension exceeding hydrodynamic forces. The net tangential force (F∥, black vector in Fig. 4c) is computed by adding all three external forces acting on the particle and is the force translating the particle along the hanging-drop surface.

The resulting net tangential force vectors (F∥, white vector field in Fig. 4d) and their magnitudes (coloured contour map in Fig. 4d) were superimposed on an experimental snapshot of the stagnation area observed for the case of polystyrene beads in cell culture medium within a hanging drop (Fig. 3c).

We estimated the minimum net tangential force required to ensure free flow of beads when assuming a no-slip boundary condition at the ALI (minimum F∥ for flow). To do this, we modelled higher flow rates, where a stagnation area is no longer present (ESI† Fig. S1, no-slip boundary condition). With a flow rate of 6 μL min−1, we estimated the minimum F∥ for flow at ∼100 fN.

Alternatively, we modelled a slip boundary condition at the ALI. This alternative did not yield a condition in which particles would stagnate, except for flow rates 20-fold lower than what was experimentally measured (ESI† Fig. S1, slip boundary condition). The use of a slip boundary condition did not yield the observed experimental result in Fig. 3b and c and 4d.

Therefore, with F∥ magnitudes under 100 fN, Fig. 4d supports our hypothesis that modelling a no-slip boundary condition at the ALI is a successful approach to predict the experimental stagnation area.

Parametric sweep. The numerical model, supported by the experimental observation of stagnation in Fig. 4d, allowed us to perform a broad parametric sweep on design (drop aperture) and operation (bead position and drop height) parameters of hanging drops for a working flow rate of 1 μL min−1.

The upper limit for the size of a hanging drop for the parametric sweep was found by the capillary length (l) in eqn (2).30 This size was found via the Eötvös or Bond number, which establishes the ratio of gravitational forces, pulling the drop down, to capillary forces, hanging the drop up.

Here, γ is the water surface tension, 0.0727 N m−1 at 20 °C or 0.0709 N m−1 at 37 °C,31ρ is the water density, 998.2 kg m−3 at 20 °C or 993.3 kg m−3 at 37 °C,32 and g is the gravitational acceleration, 9.8 m s−2. These values yield a capillary length of 2.73 mm at 20 °C or 2.70 at 37 °C. This capillary length is calculated for the case where the surface tension is highest, i.e., with de-ionized water, which gives a maximum size value. A hanging drop with a radius equal to the capillary length (5.4 mm in diameter) will have a perfect equilibrium between its weight and surface tension. However, designing such a drop in a microfluidic network would be very unstable, since any hydrodynamic force on the interface would cause it to burst.33 Through previous experiments (data not shown), we have established that the practical upper limit for the diameter of a hanging drop within an HDN is 4 mm. In practice, the smaller the diameter of the hanging drop, the more stable it is.

Ultimately, modifying the design is laborious and requires optimizing the microfluidic network, device fabrication, and validating its functionality. On the other hand, modifying the drop height is doable during device operation by simply adding or removing liquid from one of the inlets of the system (Fig. 2c). Hence, for the purpose of this work, we wanted to find an aperture that enabled both, particle stagnation and flow.

Therefore, we carried out a parametric sweep on the drop aperture diameter (2a) from 0.5 mm, which is approximately twice the width of our channels (Fig. 2c), to 4 mm, which is the practical upper limit. A scheme of varying drop aperture radii (a) is shown in Fig. 5a. We also carried out a parametric sweep on the drop height (h) as seen in Fig. 1b relative to the drop aperture radius (Fig. 5b). The h/a parametric sweep varied from a flat drop at h/a = 0 to a hemispherical drop at h/a = 1.

Fig. 5 Parameter sweep results. (a–c) Schematics showing the parametric sweep methodology. (a) Schematic of the parametric sweep over the drop aperture radius (a) for a constant drop-height-over-aperture (h/a) ratio. (b) Schematic of the parametric sweep over the drop height (a), varying the h/a ratio for a constant drop aperture. A schematic representation of a bed of particles, constituting the stagnation area, is shown in green at the ALI. (c) Schematic of the parametric sweep over the particle's x position relative to the drop aperture radius, taken at the worst-case symmetry plane of the ALI. A schematic representation of particles (green circles) at various positions is shown at the ALI. (d) Plot of the h/a ratio required to expel a bead from a hanging drop at each bead position for various drop apertures. The stagnation area is delineated for a given h/a ratio of 0.6 (dashed red line) and a drop aperture diameter (2a) of 1 mm. This stagnation area implies that, if a particle settles at the ALI between x/a = 0.2 and 0.9, it will stagnate. The minimal h/a ratio (dash-dotted red line) is referred to as the “critical h/a ratio” under which no stagnation area is present. (e) Phase diagram showing the critical h/a ratio under which free bead or cell flow is allowed. Over a h/a ratio of 0.6, potential HDN instability can be observed and is further described in the discussion. The actual drop height in mm is shown for the given critical h/a ratio (dashed red line). The apparent local extrema in the dashed red line are numerical artefacts due to the parameter sweep steps of the critical h/a ratio.

Modelling particles at various positions (x) on the symmetry axis of the hanging drop (Fig. 5c) with a parametric sweep pointed out the worst-case scenario for particle stagnation. Since upstream particles (x/a < 0) are inevitably dragged down to the ALI due to gravity, it is sufficient to only model particles at positions from the bottom of the ALI to its apex downstream, as the particles need to be pushed out of the hanging-drop compartment by the hydrodynamic flow. Therefore, we modelled particle positions from x/a = 0 to x/a = 1.

Modelling results

Our model provided an h/a ratio that is required to ensure that particles flow at each position in Fig. 5d for drop aperture diameters of 1, 2, 3 and 4 mm assuming a no-slip boundary condition at the ALI. Fig. 5d confirms that the centroid of the stagnation area is downstream of the hanging drop, as shown experimentally in Fig. 4d. As expected, larger drop apertures require smaller h/a ratios to ensure free flow of particles. In other words, the critical h/a ratio is inversely proportional to the drop aperture. For example, for a diameter of 1 mm, Fig. 5d shows that an h/a ratio under ∼0.43 allows for free flow of particles at the ALI. This data point and the absolute drop height (215 μm) were thereafter transferred to Fig. 5e. This process was repeated for every drop aperture, generating the black and red dashed lines of the phase diagram (Fig. 5e).

The phase diagram of Fig. 5e shows the critical h/a ratio to enable free particle flow in HDNs for a wide range of drop apertures. Fig. 5e essentially compares the operational parameter (drop height) on its y-axis to the design parameter (drop aperture) on its x-axis. The critical drop height in mm appears to plateau at 0.3 mm for drop aperture diameters larger than 2 mm. The optimal drop aperture then depends on the application and will be elaborated further in the discussion.

For our experiments, we used the existing on-chip pump and HDN design, which featured drop aperture diameters of 3.5 mm and still allowed for particle flow control.19 The model's findings are summarized in Fig. 6a for our 3.5 mm HDs and the particles of interest. The model predicts free particle flow for a drop height under 300 μm, i.e., at an h/a ratio under 0.17.

Fig. 6 Experimental validation of the phase diagram of Fig. 5e. a) Schematics of the various drop heights show the control over the h/a ratio. b) Images of the bead stagnation area (orange) for various drop heights. After waiting a few hours for bead stagnation, the drop height was actuated. The results show that, as expected, the stagnation area shrank before disappearing completely. ESI† Video S1 shows the videos from which the frames were taken. c) Images of the cell stagnation area (orange) and floating clusters (blue) for various drop heights. The noise in the background is due to the double-sided tape (process 2 described in the “device fabrication” section) used to bond the chip to the transparent slide support and does not affect the results otherwise. This double-sided tape was not used for the experiments in subpanel b. After waiting a few hours for cell stagnation, the drop height was actuated. The results show that, as expected, the stagnation area shrank before disappearing completely. ESI† Video S2 shows the videos from which the frames were taken.

In practice, since we are looking at phase diagrams, the h/a ratios in this study are rather indicative than decisive. There are two clear particle behaviours (phases) and a general transition (line) between these phases that is highly dependent on particle size, the effect of a stagnating pellet, static friction, adhesion, etc.

Experimental particle-flow control

Using the same methodology as for the experiments in Fig. 3, we tested the model's findings (Fig. 6a) experimentally by flowing polystyrene beads in cell culture medium around the closed-loop HDN.

After a few hours of recirculation, bead stagnation was apparent, and we started actuating the drop height over several hours. With our existing drop aperture diameters of 3.5 mm and an experimentally measured flow rate of 1 μL min−1, the flow or stagnation of beads in cell culture medium could be successfully controlled by actuating the drop height (Fig. 6b).

With these findings for beads in cell culture medium, we repeated the experiment with THP-1 cells in cell culture medium. We found similar results for cells (Fig. 6c) when compared to beads flowing in cell culture medium. We noted that the visible background noise in Fig. 6c was caused by the double-sided tape used to bond the chip to its support slide in this experiment and did not affect flow results otherwise. We observed that the transition from a small stagnating particle bed (stagnation reduction in Fig. 6b and c) to unimpeded particle flow (particle flow in Fig. 6b and c) required gentle percussion, i.e., tapping the setup.

Microscopic investigation of the air–liquid interface

To investigate the changes that occur at the ALI and that generate the pseudo no-slip boundary condition, we performed transmission electron microscopy (TEM). Therefore, cell culture medium was recirculated through our HDN and was sampled after 0 h, 3 h, and 24 h (Fig. 7). The images obtained by TEM of stock cell culture medium (Fig. 7; first row) showed an abundance of micelles and small self-assembled structures (DH ∼ 20 nm and 100 nm respectively) and the presence of few large aggregates (>1 μm). TEM of the ALI after 3 h (Fig. 7; second row) showed an overall decrease in the number of single micelles on the grid, displaced by worm-like micelle aggregates, and larger aggregates resulting from them. TEM of the ALI after 24 hours (Fig. 7; third row) showed an abundance of the same micelle chains and structures deriving from their uncontrolled aggregation, as well as some salt precipitates. These results suggest that there is an induced aggregation of some medium components into larger aggregates, which could have an influence on the ALI's properties. Hence, the no-slip-like behaviour could be linked to the formation of aggregates over time.

Fig. 7 Transmission electron microscopy (TEM) and dynamic light scattering (DLS) results. Results are shown for stock cell culture medium (first row) and hanging-drop ALI after 3 (second row) and 24 (third row) hours. TEM images show several scales, from 5 μm down to 200 nm.TEM overview shows the increased prevalence of larger aggregates over time. TEM detail of larger nanostructures reveals the aggregation process. TEM detail of smaller nanostructures shows circular micelles. DLS results show the relative preponderance of nanostructures of scales from 10 to 10[thin space (1/6-em)]000 nm. The DLS measurements are qualitative, since the samples are heterogeneous and polydisperse. DLS curves are shown in triplicates, where the most representative data is drawn as a black line. 13° forward scatter DLS measurements: larger nanostructures primarily scatter light at forward angles. Therefore, we see the relative increase in micron-scale aggregates with time. 173° non-invasive back scatter DLS measurements: back scatter detection is less sensitive to the presence of large nanostructures. Therefore, we see a relatively constant signal from micelles and small self-assemblies over time. Repeating the TEM measurements by removing FBS from the cell culture medium showed a blank TEM image, where no large aggregates and mostly micelles could be seen.

To support these results, we performed dynamic light scattering (DLS) to qualify the change of the hydrodynamic radii of nanostructures at the ALI (Fig. 7; second and third columns). With the stochastic movement of aggregates in the polydisperse ALI samples and with the built-in DLS software peak smoothing, repeated measurements could not systematically find large aggregates and, therefore, DLS results should be considered qualitative. The highlighted DLS measurements confirmed an increased likelihood of uncontrolled aggregation (>1 μm) at the ALI (Fig. 7; second column) over longer periods of time and the presence of ∼20 nm nanostructures (Fig. 7; third column) throughout the experiment.

Discussion

With the experimental results displayed in Fig. 6, we validated a mathematical model of forces on polystyrene beads and cells settled at the ALI of a recirculating HDN. Here, we will elaborate on our insights in the fabrication and operation of HDNs designed for cell recirculation. We will also discuss how our results can be transferred to various applications. Finally, we will lay out the implications of our experimental observations and models on ALI modelling strategies.

Insights on fabrication and operation

The phase diagram of Fig. 5e can be used to guide system design based on the application requirements (flow or stagnation of cells). However, even for a non-optimal system, the experimental conditions can be modulated by fine-tuning the operational parameters within specific boundaries.

If cell stagnation is desired through most of the operation of the HDN, a drop aperture of 3 mm or higher is a good choice. Choosing this aperture is preferable due to stagnation being present for h/a ratios above 0.2.

If free cell flow is desired through most of the operation of the HDN, a drop aperture of 1 mm or lower is preferable. Choosing this aperture is preferable due to free flow being present for h/a ratios under 0.4.

For a precise control over cell flow or stagnation, a drop aperture around 2 mm is preferable. This aperture will offer the maximum dynamic range for cell mobility control: working with an h/a ratio between 0 and 0.3 will allow for free cell flow, and an h/a ratio between 0.3 and 0.6 will entail cell stagnation.

Our model provides valuable aids in making design considerations before the fabrication of dedicated HDNs. Careful planning along these guidelines will save time and efforts by reducing the fabrication iterations needed to finalize chip designs through trial and error.

However, even when considering all these parameters, there are challenges that apply to HDNs in general.33 From a practical standpoint, potential fabrication inconsistencies and imperfect experimental chip levelling will have effects on hanging-drop stability. First, fabrication inconsistencies, especially when aligning and bonding multiple layers, could cause drop aperture variations throughout the device. Drop aperture variations could result in a “weak link” within the network, meaning that a misshaped hanging-drop compartment with a higher drop aperture diameter could cause the corresponding liquid drop to crash down. Second, an imperfect levelling could cause a variation in the hydrostatic pressure through the chip. Since the drops are fluidically interconnected within an HDN, pressure equilibrates through all drops. The drop at the lowest level will systematically crash if its h/a ratio reaches 1. Because of such experimental considerations, we recommend limiting the maximal prescribed h/a ratio to 0.6 (black dashed line in Fig. 5e).

Impact on experimental applications

While the above listed recommendations hold for specific, established experimental conditions (8 μm diameter and 1.05 g cm−3-density particles recirculating at 1 μL min−1), our analysis can be repeated for particles of different diameters (d) and volumetric mass densities (ρ), or for different flow rates (Q). Larger particles would have a larger cross-section, leading to higher hydrodynamic forces proportional to their surface area (∝d2), increasing the force that pushes them out of the hanging drop. Larger particles, e.g., large cell aggregates or microtissues, would also have a larger volume, leading to higher gravitational forces proportional to their volumes (∝d3), pushing them to the bottom of the hanging drop. A cubic increase of gravitational forces trumps a quadratic increase of hydrodynamic forces. Therefore, an increase in particle size (for a particle with negative buoyancy) would lead to an increase in stagnation. The downstream location of the stagnation zone is constant for particles of a given size and density, subjected to a given flow rate, in a microfluidic chip of a given drop aperture (see Fig. 5d). However, increasing stagnation (Table 1 first row) would move the stagnation zone down, closer to the bottom of the hanging drop. Conversely, increasing circulation (Table 1 second row) would move the stagnation zone up, downstream in the hanging drop. Ultimately, increasing particle stagnation can be achieved by increasing particle size, particle volumetric mass density, drop height, or drop aperture, or by reducing the flow rate.

Table 1 summarizes how these various parameters affect particle stagnation and circulation. We also comment on the effort needed to change these parameters.

The preceding analysis can also be applied to particles with positive buoyancy, i.e., floating particles, by simply considering an inverted HDN, or standing-drop network.34,35 Neutrally buoyant particles, however, would only be affected by hydrodynamic forces.

Usage in the context of microtissue and immune cell co-culture

During typical experiments, the stagnation area, as evidenced by Fig. 4d and ESI† Video S1, will steadily grow to its maximum steady-state size, as more particles are added into the system. The maximum size is highlighted for a h/a ratio of 0.6 and an aperture diameter of 1 mm in Fig. 5d. Once the stagnation area reaches its maximum size, particles will flow around the stagnation area and through the hanging-drop compartment, which effectively imposes a cap on the number of particles that can reside within the stagnation area. This cap on the number of particles enables simultaneous flow and stagnation of particles. Applying this knowledge to biological applications would allow for a precise control over the size of a stagnating-cell bed at the bottom of hanging-drop compartments. For example, by adding a microtissue in the system to study microtissue–immune cell interaction, the methodology outlined in this paper will enable to dynamically control the ratio of immune cells per microtissue in the system throughout the experiment.

However, our results do not directly translate to microtissue and immune cell co-cultures. The presence of a microtissue in the drop will reduce the flow speed near the bottom of the microtissue. In turn, this flow speed reduction will entail an increase of the stagnation area. Nevertheless, our modelling strategy provides a robust framework to recreate a flow-stagnation phase diagram (Fig. 5e) in the presence of microtissues and cells of various sizes. Such analysis was not conducted, as it was outside the scope of this publication.

Interpretation and context of pseudo-no slip boundaries

The no-slip-like fluidic behaviour observed in this study, as opposed to the expected slip behaviour (ESI† Fig. S1), suggests a fundamental change in how ALIs should be modeled.17,36,37 A medium-dependent boundary condition was not previously considered. The wrong boundary condition can lead to miscalculating flow rates by a factor of two to eight, which, in turn, can cause a large discrepancy between design and experimental operation of microfluidic chips. For microfluidic HDNs that are designed to be operated with cell culture medium, our results suggest verifying that there is a no-slip boundary condition at the ALI to ensure normal chip operation.

Although we show medium dependence of particle behaviour (Fig. 3), we show that particle circulation behaviour at the ALI does not significantly depend on whether the particles are cells or beads (Fig. 6). The similar performance is due to physical interactions (e.g., adsorption, aggregation, rolling, hydrodynamic push) prevailing over biological interactions (e.g., cell–wall interactions, etc.).

Effect of pseudo-no slip boundary on particles

Our TEM and particle flow results (Fig. 7) suggest that the pseudo-no-slip boundary is caused by the complex medium formulation of RPMI-1640, mixed with 10% FBS necessary for the culturing of our cell model. The composition of FBS is difficult to establish and, as our TEM measurements show, it contains several molecules that will aggregate and change ALI behaviour. Simpler medium formulations without a preponderance of micelles should, in principle, help to obviate the pseudo-no-slip boundary, if a slip boundary is required for the biological application.

Additionally, we observed a certain “stickiness” of beads at the ALI with cell culture medium. Combined with our TEM measurements, this observation suggests that, when beads stagnate at the ALI for a long time, they interact with proteins, molecular assemblies, and salts. This interaction leads to a stronger adhesion of beads to the ALI than if they were simply resting at the ALI. However, light tapping breaks this interaction, allowing beads and cells to simply rest at the ALI and follow the expected flow patterns.

Prevalence of the Marangoni effect

Surface tension gradients at an ALI will induce an interfacial flow from regions of low surface tension to regions of high surface tension; this is the so-called Marangoni effect. This interfacial flow can entrain a bulk liquid phase, leading to the more eye-catching examples of the Marangoni effect, e.g., tears of wine,38 or the reversal of coffee-ring deposition.39

Here, we estimate the scale of the Marangoni effect on particle displacement in our device.40 At 37 °C, the surface tension of de-ionized water is 70 mN m−1, whereas that of cell culture medium containing serum (e.g., 10% FBS) is 52 mN m−1.41 We examine the extreme case, where de-ionized water is inserted at the interface of a drop neighbouring a drop of cell culture medium (4.5 mm pitch). In this case, the surface tension gradient would generate a maximum and rapidly decreasing interfacial flow of 0.4 m s−1 from the culture medium to the de-ionized water interfaces.40 However, since we do not directly interact with the interface in the way described by this extreme case, this interfacial velocity is not possible in our system.

Surface tension gradients in our system can arise in two ways: (1) evaporation of the solvent (water) causing localized surfactant (e.g., micelles) upconcentration; and (2) advection and diffusion of surfactants. (1) Solvent evaporation is significantly mitigated by our experimental setup, which reduces the evaporation to less than 10 μL per hour while our system contains 100 to 300 μL. Additionally, solvent evaporation is uniform across the ALI surface. Therefore, evaporation does not induce surface tension gradients. (2) The hanging drop (at most 800 μm height) is hanging from a comparatively thick (500 μm height) bulk of liquid phase. Therefore, any local increase of surfactant concentration on the ALI surface is mitigated by the recirculating bulk of the liquid phase. Due to these mitigating factors, we can determine that surface tension gradients, i.e., the Marangoni effect, in our system are negligible.

Conclusion

We show that a judicious drop-height control is a viable way to counteract the unexpected effect of bead and cell stagnation when attempting particle recirculation in an HDN. However, the change of the ALI boundary condition from a slip to a no-slip condition is poorly defined. In this study, we achieved the transition from a slip to a no-slip condition by recirculating the medium in the HDN over several hours until a stagnating particle bed formed. Waiting for a particle bed to form ensures the ALI boundary reaches its steady-state and, therefore, a more predictable hydrodynamic behaviour within the recirculating HDN.

In practice, if the no-slip boundary condition can be reliably reproduced at the ALI in a sterile environment, the technique highlighted in this study will allow for a more precise prediction of and control over the flow and stagnation of cells than existing techniques.9 For a microtissue in such a system, a precise control over the residence time of flowing cells near the microtissue could be achieved simply by modifying the drop height. Such an approach would constitute an MPS that allows for studying the interaction between recirculating immune cells and various tissue or organ models without the need for tedious coating protocols as required for standard microfluidic devices.

Skin-interfaced microfluidic systems with spatially engineered 3D fluidics for sweat capture and analysis

March 12, 2026May 3, 2023 by CadWorks3DAdmin

A 3D printed epifluidic device called a "sweatainer" used for sweat capture and analysis

Skin-interfaced microfluidic systems with spatially engineered 3D fluidics for sweat capture and analysis

by Chung-Han Wu, Howin Jian Hing Ma, Paul Baessler, Roxanne Kate Balanay and Tyler Ray

Abstract: Skin-interfaced wearable systems with integrated microfluidic structures and sensing capabilities offer powerful platforms for monitoring the signals arising from natural physiological processes. This paper introduces a set of strategies, processing approaches, and microfluidic designs that harness recent advances in additive manufacturing [three-dimensional (3D) printing] to establish a unique class of epidermal microfluidic (“epifluidic”) devices. A 3D printed epifluidic platform, called a “sweatainer,” demonstrates the potential of a true 3D design space for microfluidics through the fabrication of fluidic components with previously inaccessible complex architectures. These concepts support integration of colorimetric assays to facilitate in situ biomarker analysis operating in a mode analogous to traditional epifluidic systems. The sweatainer system enables a new mode of sweat collection, termed multidraw, which facilitates the collection of multiple, independent sweat samples for either on-body or external analysis. Field studies of the sweatainer system demonstrate the practical potential of these concepts.

We kindly thank the researchers at University of Hawai'i at Mānoa for this collaboration, and for sharing the results obtained with their CADworks3D system.

Introduction

Eccrine sweat is an attractive class of biofluid suitable for the noninvasive monitoring of body chemistry. Sweat contains a rich composition of biomarkers relevant to physiological health status including electrolytes (1), metabolites (2–4), hormones (5, 6), proteins (7), and exogenous agents (8). Studies demonstrate the intermittent or continuous assessment of these, and other sweat biomarkers offer time dynamic insight into the metabolic processes of the body relevant to applications ranging from athletic performance (9–11) to medical diagnostics (2, 12–14).

Recent advances in soft microfluidics, sensing technologies, and electronics establish the foundations for a unique class of skin-like epidermal microfluidic (“epifluidic”) systems. Adapting concepts from traditional lab-on-chip technologies, these wearable microfluidic platforms comprise sophisticated networks of channels, valves, and reservoirs embedded in elastomeric substrates (15–20). The thin, flexible device construct facilitates a conformal, fluid-tight skin interface by virtue of skin-compatible adhesives to collect sweat directly from sweat glands. The integration of colorimetric, fluorometric, and electrochemical measurement techniques enable such platforms to measure sweat constituents in situ across a wide array of applications and environments (21).

Traditional approaches for sweat collection use absorbent pads (22) or microbore tubes (23) pressed against the epidermis by virtue of bands or straps to capture sweat as it emerges from the skin. Requiring trained personnel, special handling, and costly laboratory equipment, such methods are incompatible with real-time sweat analysis and prone to sample contamination or loss (24). Epifluidic devices eliminate external sample contamination by virtue of the intrinsic encapsulation of the microfluidic network and conformal skin interface. Such systems are vulnerable to surface contamination from exogenous agents present on the epidermis, such as cosmetics or natural oils, without careful preparation of the skin surface before device attachment. Furthermore, the dependence on an adhesive interface for skin attachment limits these devices to single-use applications. Upon removal, the risk of contamination, potential sample loss, and active sweat response of previously covered glands pose substantial challenges to reapplication and continued sweat collection.—Traditional approaches for sweat collection use absorbent pads (22) or microbore tubes (23) pressed against the epidermis by virtue of bands or straps to capture sweat as it emerges from the skin. Requiring trained personnel, special handling, and costly laboratory equipment, such methods are incompatible with real-time sweat analysis and prone to sample contamination or loss (24). Epifluidic devices eliminate external sample contamination by virtue of the intrinsic encapsulation of the microfluidic network and conformal skin interface. Such systems are vulnerable to surface contamination from exogenous agents present on the epidermis, such as cosmetics or natural oils, without careful preparation of the skin surface before device attachment. Furthermore, the dependence on an adhesive interface for skin attachment limits these devices to single-use applications. Upon removal, the risk of contamination, potential sample loss, and active sweat response of previously covered glands pose substantial challenges to reapplication and continued sweat collection.

The typical epifluidic fabrication pathway uses soft lithography techniques (25) to produce devices with microfluidic components and complex geometries. A common, well-established process for fabricating lab-on-chip microfluidic devices (26), soft lithography, requires high-precision molds to form discrete, patterned layers of an elastomeric material [e.g., poly(dimethylsiloxane) (PDMS)] that when bonded together yield a sealed device. Traditionally, producing molds with sufficient feature resolution (>20 μm) requires expensive, time-consuming processing methods [micromachining (27) and micromilling (28)] and access to specialized environments (cleanroom). Such requirements result in elongated device design cycles, inequitable access to equipment necessary for innovation, and additional challenges for commercial deployment due to incompatibilities with large-scale manufacturing.

Additive manufacturing (AM), or three-dimensional (3D) printing, represents an attractive alternative to conventional planar (2D) fabrication methods. AM offers powerful capabilities for producing structurally complex objects with true 3D architectures through a rapidly expanding library of printing methods. In general, these methods create solid objects in a sequential, layer-by-layer manner directly from a digital computer-aided design (CAD) file. In the context of microfluidics, the use of 3D printing is well established (29) for the rapid, cost-effective fabrication of high-resolution templates for soft lithography. In particular, vat photopolymerization techniques [e.g., resin-based printing, stereolithography, digital light processing (DLP), and continuous liquid interface polymerization] (30) enable rapid production of microscale features (>100 μm) over large areas (>600 mm²) with high precision (31). Innovations in printer hardware, software processing, and materials chemistry further extend these 3D printing capabilities to enable the direct production of enclosed microfluidic channels for lab-on-chip applications. Although manufacturers advertise printers with high resolution (xy resolution: >50 μm and z-resolution: >5 μm), in practice, the obtainable channel dimensions and device complexity are typically limited to millifluidic features (>250 μm) (29). Printer specifications represent only one key constraint to printing devices with micron-scale internal fluidic features (<100 μm). Successful fabrication requires optimization of other critical factors including printing technology (e.g., vat photopolymerization versus extrusion), feature design and spatial location, and printer-dependent parameters. AM process optimization, particularly for vat photopolymerization, demands careful attention to the chemistry of printed materials (30, 32). Resin formulations must simultaneously satisfy application specific requirements, such as biocompatibility or optical clarity, while preserving printability. Recent reports (32, 33) leverage specialized DLP-based printers and customized resins to fabricate devices containing microfluidic components with <50-μm dimensions.

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In general, wearable system designs must address the inherent mismatch between the mechanical properties of skin and rigid, planar device components. The most advanced platforms fabricated by conventional (non-AM) methods exploit sophisticated strategies, combining complex device geometries and soft (low modulus) materials to establish a seamless, nonirritating epidermal interface. Recent advances in soft materials chemistry support 3D printing approaches to fabricating wearable devices for applications spanning biophysical (34), biochemical (35, 36), and environmental (37) monitoring. However, such capabilities remain limited for the 3D fabrication of epifluidic devices as a result of the high Young’s moduli of the primary material chemistries (i.e., methacrylate-based resins) (38) suitable for printing high-resolution microfluidics. Current efforts to fabricate skin-interfaced 3D printed microfluidics use alternative printing methods [e.g., fused deposition modeling (34) and direct ink writing (39)] that support fabrication with low modulus materials at the expense of printer resolution (>200 μm). In the context of epifluidics, the ideal fabrication scheme would use resin-based printing to fabricate devices with feature sizes comparable to conventional methods with biologically compliant form factors. Such an approach would transform the fluidic design space with truly 3D device architectures while enabling a rapid, iterative design process, facilitating individual-specific device customization, and reducing the cost for low-volume production.

This paper introduces a set of strategies, processing approaches, and microfluidic designs that support such fabrication capabilities using a commercial DLP 3D printer in a simple manner of operation. A modular 3D printed epifluidic platform, termed a “sweatainer,” demonstrates several unique aspects of an AM approach to fabricating epifluidic systems. This platform, to our knowledge, represents the first 3D printed epifluidic platform with true microfluidic dimensions. Specifically, the results highlight the potential of a true 3D design space for microfluidics through the fabrication of fluidic components (channels and valves) with previously inaccessible complex architectures. Printer optimization strategies and systematic experiments enable realization of micron-scale feature sizes (<100 μm) and enhancement of optical transparency of 3D printed channels. In combination, these concepts support integration of colorimetric assays to facilitate in situ biomarker analysis operating in a mode analogous to traditional epifluidic systems. Drawing inspiration from the vacutainer blood collection tube, the sweatainer system introduces a novel mode of sweat collection, termed “multidraw.” This method overcomes the inherent limitations of single-use devices by enabling the collection of multiple, independent pristine sweat samples during a single collection period. Field studies of the sweatainer system demonstrate the practical potential of these concepts.

Results

Sweatainer system design

Figure 1A shows a schematic illustration of the two primary modules of the sweatainer system: (i) the sweatainer device and (ii) an epidermal port interface. The sweatainer consists of a 3D printed microfluidic network of enclosed channels and unsealed reservoirs, a reservoir capping layer of PDMS (thickness: 200 μm), and a gasket formed from ultrathin biomedical adhesive (3M 1524; thickness: 60 μm). The bonded 3D printed photocurable resin structure and PDMS capping layer, as presented in Materials and Methods, define a closed microfluidic structure. Introduction of either dye or colorimetric assay before bonding enables sweat visualization or chloride concentration analysis, respectively. The cross-sectional width and thickness of the filleted serpentine channels presented here are 1200 and 1000 μm, respectively. The width and height of the rectangular-shaped internal microfluidic channels are 600 and 400 μm, respectively. The filamentary design of the rigid 3D printed structure (Young’s modulus: ~975 MPa) follows from the well-established principles of stretchable electronics (40) to impart sufficient stretchability to form a mechanically robust conformal interface. The gasket establishes a temporary, fluid-tight seal with the epidermal port interface permitting facile sweatainer application and removal via reversible adhesion to the PDMS surface.

Figure 1. Schematic illustrations and optical images of the 3D printed epidermal microfluidic devices for the collection and analysis of sweat. (A) An exploded render highlights key components of the sweatainer system and epidermal interface (port). PDMS, poly(dimethylsiloxane). (B) A photograph of the sweatainer mounted on the ventral forearm of an individual before the onset of sweat collection. (C) The construct of the sweatainer eliminates uncontrolled fluid transport under mechanical loading (e.g., finger pressure and device removal). (D) Illustration of the sweatainer highlighting key device aspects including the inlet, capillary burst valves (CBVs; blue and red dashed area), collection reservoir, and ventilation holes to eliminate backpressure. (E) Renders of three-dimensional (3D) CBV designs enabled by 3D printing with diverging angles of 90° (top) and 135° (bottom). (F) 3D printing enables fabrication of device geometries in a true 3D space as shown by the computer-aided design (CAD) render (top) and photograph of actual device (bottom). Location of sweat appears in blue. (G) Photographic sequence highlighting the complete filling of a sweat collection reservoir.

The epidermal port interface comprises a thin film of pigmented PDMS (white, thickness: 400 μm) and a medical-grade adhesive layer (3M 1524) with laser-patterned openings. The adhesive layer facilitates a biocompatible, fluid-tight interface with the epidermis in which the patterned opening defines the sweat collection region (~180 mm²). An aligned access point on the backside of the sweatainer allows sweat to enter the system directly from the skin with flow driven by the natural pressures created by the sweat glands. The sweatainer design can support collection of 50.8 μl of sweat (10.8 μl per reservoir and 18.4 μl of channel network). A fully assembled representative system appears in Fig. 1B, where it is shown worn on the ventral forearm. Figure 1C demonstrates the insensitivity of the sweatainer to mechanical deformation through the absence of uncontrolled fluid flow during physical handling (finger pressure). The schematic illustration in Fig. 1D shows the microfluidic network within the 3D printed sweatainer. Sweat enters the device by the central inlet and flows through a microfluidic channel leading to a series of capillary burst valves (CBVs) and corresponding reservoirs. The CBV at the ingress of each reservoir permits fluid flow only after exceeding a set pressure, thereby enabling time-sequential sweat collection (20). Integrated ventilation holes (width: 100 μm and height: 200 μm) on the reservoir eliminate the backpressure that would evolve from trapped air and impede flow. The high-barrier properties of the photocurable resin support a low sweat evaporation rate with minimal mass loss over a 24-hour period (fig. S1 and table S1).

A key feature of this system is the use of AM to enable fully 3D, monolithic microfluidic designs comprising sophisticated nonplanar internal channel structures, spatially graded geometries, and 3D CBVs. Representative examples of 3D CBVs and the spatially graded, nonplanar geometries enabled by this fabrication method appear in Fig. 1 (E and F, respectively). By comparison, soft lithography fabrication methods restrict the design space of traditional lab-on-chip and epifluidic devices to planar (2D) channel configurations. Although lamination of multiple channel layers can yield elaborate 3D microfluidic networks, each component layer is inherently a planar geometry. As detailed in the sections that follow, the 3D fabrication expands the design space for CBVs with finer control over resultant burst pressure in comparison to planar CBVs. In a similar manner, spatially graded geometries improve sweat collection efficiency by permitting a continuous transition between the microfluidic channel and reservoir (Fig. 1F). This engineered interface, in combination with ventilation holes, ensures a uniform fluid front during reservoir filling (Fig. 1G, blue dye for visualization), thereby eliminating trapped air bubbles that result from a rapid expansion.

Design and DLP printing considerations for optimized fabrication of 3D printed epifluidic devices

Successful fabrication of a fully enclosed microfluidic channel with feature sizes at the xy plane resolution limit of current DLP printers (~30 to 50 μm) depends on several related factors including: design aspects (e.g., channel vertical position), print process parameters [e.g., layer height, layer cure time (LCT), and print speed], and printer hardware (e.g., projector light power and wavelength). Optimization of user-adjustable factors results in a robust print process suitable for producing microfluidic devices with sufficient optical clarity, dimensional fidelity, and mechanical performance for use in epifluidic applications.

As expected, epifluidic device performance is dependent on the dimensional accuracy of a fabrication process. If not quantified, then unintended deviation from designed dimensions can adversely affect component performance (i.e., CBV burst pressure) or measurement accuracy (i.e., sweat volume, sweat rate). Fabrication of test structures (Fig. 2A) comprising a sequence of square channels (width and height range: 100 to 900 μm, 100-μm increments; length: 5 mm) embedded in a square base (width and height: 1 mm) facilitate determination of the minimum printable channel dimensions and sidewall thickness (minimum of 50 μm). The asymmetric vertical position of the channels establishes a uniform capping layer (100 μm) across all dimensions tested. Because the DLP printer fabricates the structure in an inverse manner (Fig. 2A, base prints first), the channel position minimizes photopolymerizing resin trapped in the channel during the printing process.

Figure 2. Optimized design strategy for fabricating 3D printed epifluidic devices with prescribed channel geometries. (A) Photograph of 3D printed test channels [100 to 900 μm, square; 2-s layer cure time (LCT)]. (B) Plot of variation of printed channel height from designed dimensions as a function of LCT. (C) Plot of variation of printed channel width from designed dimensions as a function of LCT. (D) Plot highlighting the printable region of the digital light processing (DLP) printer used in this work for various channel dimensions relevant to epifluidic devices.

Experimental studies reveal the similarly strong influence of LCT on print success and device quality. The LCT defines the energy dose used to cross-link the photopolymer given in time (seconds). The projector wavelength is hardware defined (385 nm for this work), and varying the power is not typically user accessible. Systematic studies of four LCT settings—selected starting from the minimum (0.54 s) to maximum values (2.0 s; 0.6-s interval) beyond which channels could not be fabricated successfully—establish a relationship among print performance (i.e., channel printed successfully), dimensional accuracy, and optical clarity. Measurement results from optical microscope images, shown in Fig. 2B for channel height and Fig. 2C for channel width, highlight the relationship between LCT and printed channel dimensions. The proportional relationship between increasing LCT and light propagation into the z dimension (thickness) of the masked regions (i.e., channels) results in smaller than designed channel heights. By comparison, the dimensional accuracy for a given channel width depends primarily on the size of the DLP printer pixels (xy plane resolution) rather than LCT. The observed positive channel width variation with decreasing LCT indicates incomplete photopolymerization. Subsequent postprocessing removal of uncured resin yields channels with dimensions greater than designed. In combination, these results establish the printable region for an epifluidic design as a function of LCT. As shown in Fig. 2 (B and C), successful fabrication of a 100-μm square channel requires a short LCT (i.e., 0.54 and 0.8 s), whereas a longer LCT results in photopolymerization of the otherwise unreacted resin. Conversely, for large dimensions (>700 μm square channels), a short LCT produces channels too fragile to survive printing and postprocessing due to incomplete photopolymerization. These results establish an LCT of 0.8 s as the optimal setting for balancing printability with dimensional accuracy for the printed epifluidic devices described in subsequent sections.

Additional systematic experiments establish the DLP-printable design space for epifluidic-relevant dimensions (100 to 600 μm). Evaluation of print success as a function of channel dimensions (width and height) for an enclosed microfluidic channel (length: 30 mm) identifies the printable region (Fig. 2D). An encapsulated microfluidic channel capable of supporting unrestricted fluid flow, in contrast to a sealed or partially restricted channel, defines a successful print. Intuitively, print failure rate increases as the enclosed channel dimensions approach the printer xy plane resolution limit (~32-μm x 32-µm square pixel). Results show a channel dimension of 100 μm (either width or height) corresponds to the lower limit for a successful printed device.

Print process optimization to support colorimetric analysis in 3D printed epifluidic systems

The optical transparency of a 3D printed microfluidic device depends on several factors including material selection, printer hardware (e.g., build plate and vat surface material), postprocessing, and surface roughness. In contrast to the typical surface roughness feature size necessary for optical transparency (<10 nm) (41), DLP printers produce parts with microscale surface roughness, resulting in a semi-translucent appearance (32).

As mentioned previously, the digital micromirror device (DMD) pixel size governs the xy plane resolution of a DLP printer. Minute gaps between individual DMD elements locally reduce reflected light intensity, yielding a surface roughness with features corresponding to DMD pixel size and layer height. While specialized printing methods (grayscale) (42) or printer hardware (oscillating lenses) (43) offer sophisticated strategies to reduce aliasing and improve surface roughness, the fundamental approach to eliminating this defect mode is enhancing the uniformity of projected light to ensure complete photopolymerization. Figure 3A illustrates that increasing the exposure dose by lengthening the LCT eliminates the observed grid pattern defects (from DMD element gaps) and improves optical transparency. Ultraviolet-visible (UV-Vis) spectroscopy experiments examine the transmission properties of 3D printed microcuvettes in comparison to a commercial plastic cuvette (Fig. 3B). While results show substantial modulation of light transmission with increasing LCT, ranging from ~20 (LCT: 0.54 s) to ~60% (LCT: 2 s), the reference commercial plastic cuvette offers higher light transmission (~80%). Intuitively, there is no observed wavelength dependence for light transmission within the Vis spectrum (400 to 1100 nm) beyond the anticipated strong absorbance within the UV region (<400 nm, necessary for photopolymerization) for the 3D printed samples. As a consequence of the presence of both the UV absorber and photoinitiator in the resin, green parts (i.e., before curing) have a light yellow hue. As presented in Materials and Methods, completion of the postprocessing sequence eliminates part coloring (fig. S2).

Figure 3. Optimized design strategy for enabling colorimetric analysis in 3D-printed epifluidic systems. (A) Optical micrographs of the surface of parts printed with different LCT settings. (B) Plot of light transmission of commercial and resin-printed cuvettes measured with ultraviolet-visible (UV-Vis) spectrometer. (C) Photographs of epifluidic reservoirs fabricated using static (0.54 s, 2-s LCT) and adaptive (AP1 and AP2) printing processes illustrating differences in optical transparency. (D) Calibration curves as a function of LCT highlighting improvement in optical transparency (and thus colorimetric performance) with increasing LCT. A.U., arbitrary units.

In addition to LCT, layer height affects both overall device quality (e.g., vertical resolution, optical clarity, and channel roughness) and print time, which corresponds to device yield. Conventional approaches to vat photopolymerization use constant values for a given print run (i.e., fixed layer height and LCT). At present, only one manufacturer [Formlabs (44)] supports an adaptive layer height process to increase print speed by adjusting layer height as a function of model detail (i.e., small layers for fine features and thick layers for coarse features). Adaptive printing is an attractive process for obtaining expanded design flexibility for 3D printed epifluidic systems. Although not supported by default, a combination of custom software and manual geometric code programming in this work enables definition of both layer height and LCT as a function of model dimensions. The representative example shown in fig. S3 illustrates the capabilities of this adaptive printing process to fabricate a cube (all dimensions: 2 mm) using four layer heights (5, 10, 30, and 50 μm) in an arbitrary order. By comparison to a constant LCT and layer height setting printing process, this approach enables successful, time-efficient fabrication of epifluidic systems with complex geometries and superior device quality.

Colorimetric assays facilitate passive, battery-free in situ quantitative measurement of sweat biomarkers. A chemical reagent reacts with a target species to generate an optical signal proportional to analyte concentration (45). Accurate colorimetric analysis requires channels with uniform height (i.e., path length), a high degree of optical transparency, and integrated color reference markers to support reliable image processing under variable ambient lighting conditions (46). The layer-by-layer control over LCT and layer height parameters enabled by an adaptive printing process is critical for fabricating microfluidic devices with the requisite surface finish and optical transparency to support colorimetric analysis. Figure 3C illustrates the influence of an adaptive LCT print process on the optical transparency of microfluidic channels. The optical clarity for two representative sweatainer reservoirs manufactured using a layer-constant LCT (0.54 and 2 s) increases with longer LCT (Fig 3C). While beneficial for reducing nonuniform illumination, the increased UV dose results in undesirable curing of resin in enclosed features (channels and CBVs). By comparison, an adaptive printing process (AP 1) using an LCT of 0.54 s for the reservoir surface and an LCT of 2 s for subsequent layers facilitates fabrication of a sweatainer with a translucent imaging plane, a transparent device, and preservation of internal channel features. An inverse adaptive printing process (AP 2; base LCT: 2 s and subsequent layer LCT: 0.54 s) results in an optically transparent imaging plane and a translucent device.

Systematic benchtop experiments evaluate the suitability of devices fabricated by adaptive printing for colorimetric analysis. The colorimetric assay silver chloranilate produces a dark violet color response proportional to chloride concentration. Imaging the device with a smartphone camera enables color extraction and subsequent quantification of color response. The inclusion of a color balance chart facilitates color calibration for each image. As in previous reports (47, 48), converting images from native red, green, blue (RGB) color space to CIELAB color space—which expresses color as lightness (L), amount of green to red (a^*), and amount of yellow to blue (b^*)—ensures device-independent color sampling. Conversion of the a* and b* components to chroma (C^*) by the relation

yields a calibration curve with chloride concentration by a power-law relation (fig. S4). Figure 3D shows calibration charts created from 3D printed sweatainers with different LCT parameters and reference colorimetric assay solutions. This plot reveals that the improvement in optical clarity with increasing LCT provides a corresponding enhancement in the range of detectable color measurements. As these findings indicate, an adaptive printing process is essential for fabricating epifluidic devices with an optical transparency sufficient to support colorimetric analysis.

3D CBV designs for sequential sweat analysis

CBVs are a key component for the sequential analysis of sweat biomarkers in many epifluidic platforms. The time dynamic variations in sweat rate arising from physical (e.g., sweat gland density), physiological (e.g., exertion and emotion), and external factors (e.g., temperature and pH) result in corresponding changes in analyte concentration. As previously described, CBVs prevent flow for fluid pressure conditions below a designed threshold [bursting pressure (BP)]; when the fluid pressure exceeds the BP, the CBV immediately bursts. Operating without use of actuation or moving components, CBV BP is governed by valve geometry.

The Young-Laplace equation describes the BP for a CBV (rectangular channel) as (49)

where σ is the fluid surface tension, θ_A is the critical advancing contact angle for the channel (material dependent, θ_A = 120° for PDMS) (50), θ*_I is the minimum of either θ_A + β or 180°, β is the channel diverging angle, and b and h are the diverging channel width and height, respectively. As the second term of Eq. 2 is constant for a planar (2D) CBV, channel width and diverging angle govern the BP for a given CBV. In practice, epifluidic device designs use geometric restrictions (i.e., modifications to channel width) to control valve BP.

The 3D printing concept for epifluidic devices presented here expands CBV capabilities by enabling a full 3D CBV design. As a consequence, Eq. 2 can be written as

for a 3D CBV, where θ*J is the minimum of either θ_A + γ or 180° and γ is the channel diverging angle (z axis). It follows that for a microfluidic channel with fixed dimensions, the CBV BP becomes a function of the channel diverging angles (β and γ). Computational predictions of four representative CBV designs, presented as a schematic in Fig. 4A with parameters specified in Table 1, illustrate this relationship. Figure 4B shows the theoretical BP versus channel size (square channel) for the four CBV designs with σ = 0.072 N/m (surface tension of water) and θ_A = 120° (PDMS) for the 2D CBV (type 1) and θ_A = 60° for the 3D CBVs (resin, types 2 to 4). It is shown that BP is inversely proportional to channel size. As expected, the analytical model reveals that for a given channel size BP increases for 3D CBV designs (resin) in comparison to a 2D CBV (PDMS). Within the subset of 3D CBV designs, the channel diverging angles (β and γ) dictate the valve BP (BP_Type4 > BP_Type3 > BP_Type2).

Figure 4. 3D CBV designs for sequential sweat analysis. (A) Schematic renders highlighting four design types of CBVs used in this work. Areas highlighted in blue indicate differences between CBV designs. (B) Plot of the theoretical maximum bursting pressures (BPs) calculated from the Young-Laplace equation as a function of channel size for a square geometry. (C) Sequence of photographs illustrating the performance of different CBV designs (labels 1 to 8). Use of backside illumination for the overview photograph facilitates visualization of valves and channels. (D) A sequence of photographs shows a 3D printed H channel with one central inlet and four CBVs (color indicates CBV design and fixed channel geometry) filling sequentially, highlighting the fluid control enabled by a true 3D CBV. (E) Plot of the theoretical BP as a function of diverging angle β for a channel with a fixed geometry (width: 600 μm and height: 400 μm). The CBV designs are identical to (B). (F) A sequence of photographs highlighting performance of the 3D printed sweatainer design used in human participant testing.

Benchtop experiments yield measurements of CBV BPs by means of a positive pressure displacement pump apparatus that perfuses water (dyed blue for visualization) into the microfluidic network at defined pressures. Figure 4C shows a representative test of the sequential filling performance of a network of 2D and 3D CBV-gated reservoirs, labeled chronologically in order of increasing BP. Table 2 and fig. S5 detail the CBV design parameters, theoretical CBV BPs, and effective theoretical BPs, which consider the theoretical CBV BP and fluidic resistance of the microfluidic channel network. Imperfections resulting from the 3D printing process result in experimental BP values below theoretical limits.

The 3D design space provides attractive capabilities for fine-scale control over CBV performance to enable compact fluid control features within epifluidic devices. Varying the diverging angle design parameters (β and γ) for a 3D CBV results in substantial differences in BP for valves with similar dimensions and form factors. Systematic experiments performed in similar manner as described previously verify the correlation between diverging angle and BP for the 3D CBV architectures illustrated in Fig. 4A with identical channel dimensions. Figure 4D shows a representative test of 3D CBV performance via a 3D printed microfluidic device with channels arrayed in an H configuration (channel dimensions: 600-μm width and 400-μm height). As Fig. 4E highlights, BP increases with β for a resin-based 3D CBV in contrast to a PDMS-based 2D CBV baseline reference. Material properties limit the valve design space on account of the BP dependence on contact angle. For hydrophobic materials such as PDMS (i.e., contact angle >120°), β values greater than 60° reduce to 180°, resulting in BP value dependent only on channel width (b). By comparison, the expanded design range, in which β governs valve BP, results from the smaller contact angle of hydrophilic materials (i.e., resin). The experimental results support these trends predicted by the analytical model with the variation between measured and predicted values attributed to geometric imperfections inherent to the fabrication process (i.e., slight rounding of corners) (51). A similar trend occurs for valve designs in which γ varies with respect to a fixed β.

Additional studies demonstrate 3D CBV performance in a device architecture relevant to practical use. Robust operation requires CBV designs with BP within the physiologically relevant range of sweat secretory pressure (0.5 to 2 kPa) (51). Tests of the sweatainer design shown in Fig. 4F proceed in the same manner whereby water enters the device through a central inlet. Reservoirs fill sequentially in the order indicated as the CBVs at entrance of reservoirs no. 2 and no. 3 prevent fluid flow until reservoir no. 1 fills completely. Variation of CBV diverging angle defines the BP for CBV no. 1 (blue, 0.66 kPa) and CBV no. 2 (red, 0.86 kPa). These results validate the design of the sweatainer for use in on-body testing.

Field studies of the sweatainer

A pilot study comprising healthy adult volunteers (N = 8) exercising on a stationary bike explores the on-body performance of the sweatainer system. Following the protocol detailed in Materials and Methods, the sweatainer intimately couples to the ventral forearm of a participant by means of the epidermal port (PDMS/skin-safe adhesive). Participants cycled at moderate intensity for a period of 50 min under controlled environmental conditions [22°C, 59% relative humidity (RH)]. Upon entering the device from the skin, sweat proceeds to sequentially fill the microfluidic reservoirs. The addition of chloride-free dye at the sweatainer inlet aids in visualization. Periodic imaging with a smartphone camera during exercise facilitates monitoring fill performance. The sweatainer typically fills within 40 min from the initiation of exercise; after filling, the device is exchanged mid-exercise with a new sweatainer in a seamless manner. Figure 5A highlights this event sequence with sweatainers distinguished by distinct visualization dyes (device no. 1: blue and device no. 2: orange). The simplicity of the exchange facilitates a rapid replacement time (<30 s), thereby minimizing potential interruption to the sweat collection process. In all tests, the adhesive gasket maintains a robust, water-tight interface between the sweatainer and epidermal port evidenced by the absence of observed leaks. The 3D printed sweatainer resists mechanical deformation during detachment, thereby eliminating unconstrained fluid flow. In combination, these features support the multidraw collection of pristine sweat samples and reduce the risk of sample contamination during collection process.

Figure 5. Sweatainer field studies. (A) Sequence of photographs highlighting operation of the sweatainer system. A sweatainer (device no. 1) collects sweat during an active exercise period, which, upon filling, is rapidly exchanged (<30 s) for a second sweatainer (device no. 2) facilitating multidraw sweat collection. (B) Photograph of sweatainer position during exercise trials (blue box). (C) A magnified view of the same sweatainer devices shown in (B) before the onset of sweating. The sweatainer shown on left is for collection (control) with the device on the right for colorimetric analysis. (D and E) respectively show the collection and colorimetric sweatainers at the conclusion of the exercise period. (F) Plot showing the concentration of sweat chloride from the collection (chloridometer) and colorimetric sweatainers for three independent exercise trials for a single participant (stationary cycling, 50 min, constant power). (G) Plot of showing sweat chloride concentration from two different colorimetric sweatainers worn sequentially (i.e., replaced during trial) during a predefined exercise period (stationary cycling, 50 min, constant power). The total sweat volume lost by a given individual during this exercise period corresponds to the total number of filled sweatainer chambers. Scale bars, 5 mm.

A second set of exercise tests focuses on the in situ measurement of the concentration of sweat chloride by colorimetric analysis. A sweatainer configured with an integrated colorimetric assay (replacing visualization dye) enables measurement of chloride concentration in collected sweat during exercise. Figure 5B shows the sweatainer mounted on the ventral forearm of a volunteer participant. Simultaneous deployment of a collection sweatainer (orange dye alone) in close spatial proximity of a colorimetric sweatainer (Fig. 5C) facilitates comparison of colorimetric chloride measurements with gold standard clinical methods for chloride analysis (chloridometer). The collection sweatainer operates in a similar mode to microbore tubes (i.e., Macroduct) traditionally used in clinical settings for collecting sweat for chemical analysis. Representative photographs of the colorimetric and collection sweatainers at the conclusion of an exercise period appear in Fig. 5 (D and E, respectively). As shown in Fig. 5F, for a representative participant, chloride concentrations measured using colorimetric sweatainers correlate well for given individual (Fig. 5F reports three independent exercise trials), within experimental uncertainties, to values determined using coulometry and are within the normal physiological range (48). The chronological sampling capabilities of the sweatainer enable monitoring of the time dynamic variation of sweat biomarkers. Figure 5G demonstrates the multidraw sweatainer operation for three participants (field study data for remaining five participants shown in table S2) during a fixed exercise period (stationary cycling, 50 min, constant power). In both sets of trials, the observed increase in sweat chloride concentration during exercise is consistent with results from previous studies (52). Here, an inverse relationship exists between the sweat duct efficiency in reabsorbing chloride and rate of sweat loss, resulting in a corresponding increase in sweat chloride. Factors such as fitness level, training status, and heat acclimation affect this relationship for a given individual. These findings demonstrate the sweatainer system as a viable platform for colorimetric-based biomarker analysis with reported values comparable to established clinical methods.

Discussion

The sweatainer system reported here introduces an AM approach to fabricating epidermal microfluidic devices to collect and analyze sweat. AM enables true 3D design of microfluidic channels and fluid control components, such as valves, with architectures typically inaccessible to planar (2D) fabrication methods. The detailed characterization and optimization of print parameters provides a pathway to fabricate microfluidic devices with enhanced optical transparency and feature sizes below 100 μm. Field studies using stationary cycling provide a practical demonstration of key concepts of the sweatainer platform including multidraw sample collection scheme and in situ colorimetric analysis of chloride concentration. Future studies will seek to investigate the generalizability of the sweatainer platform beyond clinical applications to sweat collection during more vigorous and dynamic physical activities through the development of optimized designs capable of supporting a broader spectrum of physical exertion.

The sweatainer platform represents a pivotal advancement in the collection and analysis of sweat samples. Inspired by the versatility of the vacutainer for blood collection, the sweatainer allows for the acquisition of multiple, independent aliquots of sweat from a single collection period. This collection mode enables an array of possibilities for sweat-based studies, including remote and at-home diagnostics, biobanking for future clinical research, and the integration of sweat analysis into existing clinical chemistry methods. Moreover, the utilization of AM for fabricating the sweatainer allows for customized geometries and streamlined integration into clinical workflows, further enhancing the potential of the platform for facilitating the quantification of ultralow concentration sweat biomarkers. The realization of multidraw sweat collection, enabled by the sophisticated sample collection strategies and customizable designs reported here, represents a major step forward in the field of sweat-based analysis.

Materials and Methods

Fabrication of 3D printed epifluidic devices

Each epifluidic device design (3D) was created using CAD software (AutoCAD 2019, Autodesk, CA, USA). Subsequent export to a stereolithography file format (.stl) yielded a file suitable for direct use by the DLP resin printer (Prime 110, 385 nm, MiiCraft, Taiwan and Creative CADworks, ON, Canada). The included printer control software (Utility, version 6.3.0.t3) provided direct control over print parameters for each file including layer height (5 to 50 μm), dose, and lamp power. High-fidelity printing was achieved by application of a removable Kapton polyimide tape over the surface of the polished aluminum build plate. The applied tape was free of bubbles/wrinkles to ensure a smooth build surface free of defects.

Devices were printed using transparent resin (MiiCraft BV-007A, Creative CADworks, ON, Canada) and a 10-μm layer height (six devices per build plate, ~20 min total print time). Gentle removal of printed parts from the build plate, soaking in 1% detergent solution (Alconox-1232-1, Alconox, NY, USA) under sonication (CPX2800, Fisher Scientific, PA, USA) for 10 min, drying of device using clean dry air (CDA), postprint UV cure for 10 min (CureZone, MiiCraft, Taiwan), and postcure bake at 70°C for 30 min (Model 40E Lab Oven, Quincy Lab Inc., IL, USA) yielded a 3D printed epifluidic device suitable for direct use or integration with PDMS.

A three-step process (fig. S6) facilitated printing fully enclosed 3D printed devices. Printing epifluidic devices with open reservoirs (step 1) and postprint removal of uncured liquid resin by CDA (step 2) enabled enclosure of the devices with a thin capping layer (30 μm) by means of a second print process (step 3). The printed device remains fixed to the build plate during the printing process to ensure feature alignment. Following the previously described postprocessing steps yielded a fully enclosed epifluidic device.

Apparatus Used

Clear Microfluidic Resin

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Curezone

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PR110
3D Printer

Legacy

Fabrication of ultrathin capping layer for microfluidic channels in hybrid devices

Pouring liquid PDMS (10:1 base:curing agent; Sylgard 184, Dow Inc., MI, USA) with white pigment (3% w/w; Ignite White, Smooth-On Inc., PA, USA) onto a sacrificial mylar film (2 mil thickness), spin coating for 30 s [400 revolutions per minute (rpm) for reservoir capping layer and 200 rpm for epidermal interface layer], and curing in an oven (70°C, 2 hours) formed films with thicknesses of 200 and 400 μm, respectively. A CO₂ laser cutter (30 W Epilog Mini 24, Epilog Laser, CO, USA) patterned the PDMS films into the final geometries used in the epifluidic devices. A medical-grade adhesive (1524, 3M Inc., MN, USA) is patterned in the same manner and bonded to the PDMS interfacial layer, established the epidermal interface for the device.

Hybrid 3D printed epifluidic devices use bonded PDMS capping layers to enclose 3D printed microfluidic reservoirs. Modification of a previously reported method (53) facilitated a strong bond between PDMS and the printed device. Specifically, rinsing with isopropyl alcohol (2-propanol, A416, Fisher Scientific, MA, USA), soaking in deionized (DI) water (Direct-Q 3 UV Water Purification System, MilliporeSigma, MO, USA) for 30 min, corona treating with air plasma (BD-20, Electro-Technic, IL, USA) for 30 s followed by immediate immersion in a 12% v/v solution of (3-aminopropyl)triethoxysilane (APTES; 440140, MilliporeSigma, MO, USA) for at least 20 min, rinsing in DI water, and drying with CDA prepared the oven-baked 3D printed device for bonding to PDMS. Pipetting colorimetric reagents or flow visualization dye (Soft Gel Paste, AmeriColor Corp., CA, USA) into predetermined regions occurred before sealing of the 3D printed device. After a 30-s corona treatment, laminating the PDMS capping layer to the APTES-modified printed surface sealed the epifluidic device. Heat treating the assembled device on a hotplate (70°C) under applied weight (3 kg) for 30 min formed a permanent bond. Removal of the sacrificial mylar layer, release from excess PDMS via laser cutting, and opening the central sweat ingress points using a 1.5-mm diameter circular punch (reusable biopsy punch, World Precision Instruments) yielded a final hybrid epifluidic device.

Measurement of evaporation rate for 3D printed microfluidic networks

3D printed microfluidic devices (N = 7) with theoretical capacity (~101 ml) facilitated the measurement of the rate of evaporation. Sealing of the inlet and outlet of a device with parafilm after filling with DI water (dyed blue for visualization) formed the complete device for testing. Measurement of the initial sealed device mass (inclusive of water, film, and printed microfluidic system) using a microbalance (Sartorius Quintix 224-1S, Germany) enabled recording of mass loss at 2 and 24 hours. Devices were maintained at room temperature in a controlled laboratory environment reflective of anticipated use environment (22°C, 55% RH). An optical camera (Canon 90D, Canon EF 100 mm f/2.8L USM lens) facilitated observation of visual changes to fluid levels at each measurement interval.

Characterization of 3D CBVs

A digital microscope (VHX-7100, Keyence Corp., Japan) produced micrographs of the devices. An optical camera (Canon 90D, Canon EF 100 mm f/2.8L USM lens) provided video capture capabilities (30 frames per second) for device analysis. Measurement of the CBV burst pressure consisted of a “fill test” in which water (dyed blue for visualization) entered a device until flow stopped the CBV. A modular, calibrated pressure displacement flow system (Flow EZ, Fluigent, France) controlled the fluid pressure and permitted near-instantaneous stepwise increase in pressure (0.1-mbar interval, 10-s dwell time). Video observation identified the pressure threshold for fluid to burst the valve.

Measurements of transmission properties of 3D printed devices

A UV-Vis spectrophotometer (UV-1900i, Shimadzu, Japan) enabled quantification of the optical transmission properties of the printed devices (300 to 1000 nm, 0.5-nm interval). A commercial plastic cuvette (path length: 10 mm; Shimadzu) served as a reference (control). Four sets of 3D printed cuvettes (N = 3 per set) using a different LCT setting (0.54, 0.8, 1.4, and 2 s) enable quantification of the relationship between LCT and optical transmission (dimensions: height, 50 mm; width, 8 mm; path length, 1 mm; and volume, ~21 μl).

Colorimetric assay for chloride

The chloride colorimetric assay solution resulted from thoroughly vortexing 50 mg of silver chloranilate (MP Biomedicals, CA, USA) in 200 μl of a solution of 2% (w/v) polyhydroxyethylmethacrylate (529265, MilliporeSigma, MO, USA) in methanol (A412, Fisher Scientific, MA, USA) to yield a homogenous suspension. Spotting 2 μl of this solution via laboratory pipette onto the 3D printed device near the central sweat ingress point, followed by drying in an oven for 30 min before encapsulation, prepared the epifluidic device for colorimetric chloride measurements.

Standard color development and color reference marker preparation

Mixing sodium chloride (S271, Fisher Scientific, MA, USA) in DI water produced standard test solutions (0, 10, 20, 30, 50, 75, 90, 110, 130, and 150 mM). Clinical-grade chloridometer measurements (ChloroChek, ELITech Group Inc.) yielded validated test solution concentrations. Digital imaging and analysis of sample reservoirs (N = 7) containing one standard solution reacted with the silver chloranilate assay under uniform illumination formed a set of reference images. The sample reservoirs were of the same depth as the epifluidic channels to ensure accurate color representation.

Digital image analysis for the evaluation of sweat chloride concentrations

A smartphone camera (iPhone 11 Pro Max, Apple, CA, USA) captured images during on-body field tests. A color calibration card (ColorChecker Classic, X-Rite, MI, USA) in the frame of each image facilitated accurate color extraction under various illumination conditions. An open-source photography software package (Darktable 3.0.0, Darktable.org) served as the platform for calibrating images using the color reference card. Analysis of calibrated images using MATLAB (R2019b, MathWorks Inc., MA, USA) enabled cropping multiple regions of interest (N = 3) from images and extraction of CIELAB color values (L, a*, and b*) for chroma analysis. Mapping of chroma values from colorimetric samples of known reference chloride solutions yielded colorimetric calibration charts with a power-law relationship. This calibration chart supported quantification of the sweat chloride concentration in on-body field testing.

Human participant sweat analysis

The purpose of this pilot study was to evaluate the performance of the 3D printed epifluidic device and use in collecting and analyzing sweat. Testing involved healthy young adults (N = 8, six male and two female) as volunteers during normal physical activity (stationary cycling) with no additional human participant risk. The study was International Review Board (IRB) approved through the University of Hawaiʻi (IRB no. 2018-1440). Informed consent was obtained after explanation of the nature and possible consequences of study participation.

Cleaning of the forearm of each individual with an alcohol wipe prepared the skin for robust adhesion to the device. The exercise regime comprised stationary cycling under approximately constant working load for 50 min in a controlled laboratory environment (22°C, 55% RH).

Evaluation of the colorimetric sweatainer performance required individual participants (N = 3) to wear two separate sweatainers, one colorimetric and one collection (as a control), located in close proximity on the same arm. Before device removal, a photograph of the colorimetric sweatainer was recorded at the conclusion of the collection period for image processing and chloride analysis. Extraction of sweat from the individual reservoirs of the collection sweatainer at the conclusion of the exercise period facilitated chloride measurements using a ChloroChek Chloridometer.

Evaluation of sequential generation of aliquots of sweat required periodic monitoring the filling of the epifluidic device (N = 8). Once all reservoirs filled, as determined by visual observation, the initial device (attached at the start of the exercise period) was removed from the interfacial layer and replaced with a new device while simultaneously continuing to exercise.

3D-Printed Microinjection Needle Arrays via a Hybrid DLP-Direct Laser Writing Strategy

January 16, 2026February 5, 2023 by CadWorks3DAdmin

3D-Printed Microinjection Needle Arrays via a Hybrid DLP-Direct Laser Writing Strategy

Sunandita Sarker, Adira Colton, Ziteng Wen, Xin Xu, Metecan Erdi, Anthony Jones, Peter Kofinas, Eleonora Tubaldi, Piotr Walczak, Miroslaw Janowski, Yajie Liang, Ryan D. Sochol

Microinjection protocols are ubiquitous throughout biomedical fields, with hollow microneedle arrays (MNAs) offering distinctive benefits in both research and clinical settings. Unfortunately, manufacturing-associated barriers remain a critical impediment to emerging applications that demand high-density arrays of hollow, high-aspect-ratio microneedles. To address such challenges, here, a hybrid additive manufacturing approach that combines digital light processing (DLP) 3D printing with “ex situ direct laser writing (esDLW)” is presented to enable new classes of MNAs for fluidic microinjections. Experimental results for esDLW-based 3D printing of arrays of high-aspect-ratio microneedles—with 30 µm inner diameters, 50 µm outer diameters, and 550 µm heights, and arrayed with 100 µm needle-to-needle spacing—directly onto DLP-printed capillaries reveal uncompromised fluidic integrity at the MNA-capillary interface during microfluidic cyclic burst-pressure testing for input pressures in excess of 250 kPa (n = 100 cycles). Ex vivo experiments perform using excised mouse brains reveal that the MNAs not only physically withstand penetration into and retraction from brain tissue but also yield effective and distributed microinjection of surrogate fluids and nanoparticle suspensions directly into the brains. In combination, the results suggest that the presented strategy for fabricating high-aspect-ratio, high-density, hollow MNAs could hold unique promise for biomedical microinjection applications.

We kindly thank the researchers at University of Maryland for this collaboration, and for sharing the results obtained with their system.

Introduction

Microinjection technologies underlie a diversity of biomedical applications, such as in vitro fertilization, intraocular injection, therapeutic drug and vaccine delivery, developmental biology, and transgenics.[1-4] Historically, microinjection protocols have relied on using a single hollow microneedle to deliver target substances (e.g., cells, DNA, RNA, micro/nanoparticles) to a singular location of interest.[5-7] Recently, however, alternatives in the form of microneedle arrays (MNAs) have garnered increasing interest due to a wide range of benefits over their single-needle counterparts, including the ability to rapidly deliver target material over a large, distributed area, which has proven to be particularly beneficial for transdermal and intradermal drug delivery.[8-11] Despite the significant potential of MNAs for microinjection applications, the majority of current MNA developments are founded on solid (e.g., coated and/or dissolvable) microneedles that are inherently incompatible with active fluidic microinjection protocols.[12-14] This focus on solid MNAs is, in part, due to the considerable challenges associated with manufacturing arrays comprising hollow microneedles at small scales. Specifically, although researchers have demonstrated that conventional clean room-based micromachining approaches can be adapted to fabricate arrays of hollow microneedles,[15-17] such protocols can be exceedingly time-, cost-, and labor-intensive, while restricting the architectures of the microneedles to low-aspect-ratio “2.5D” geometries.[18-20] The geometric limitations, in particular, represent a significant barrier to extending the benefits of MNAs to emerging microinjection applications, such as for treatments of neurological conditions.

One example of such a treatment in which MNAs could potentially offer benefits over single-needle injection strategies is stem cell therapy (SCT). A crucial obstacle to the clinical efficacy of SCT is the poor viability of stem cells following delivery into the brain.[21-23] One challenge associated with conventional needles is cell crowding at the injection site due to the high concentrations of donor cells (e.g., up to 100 000 cells µL−1),[24, 25] which can lead to large cell spheroids with undesirable conditions (e.g., decreased access to O2 and nutrients for interior cells) that contribute to the low survival rates of implanted stem cells.[26-29] It is possible that simultaneous, distributed cell delivery via MNAs could provide novel means to improve cell survival rates by reducing cell crowding; however, no MNA yet exists to enable such studies. For instance, even in the case of mice—a widely used disease model[30] with a relatively shallow (≈1 mm) cerebral cortex compared to other animal models[31]—the ability to penetrate into the cerebral cortex for therapeutics delivery would necessitate hollow microneedles that not only comprise outer diameters (ODs) on the order of tens of micrometers but also include heights in excess of 500 µm. Consequently, new strategies for manufacturing MNAs composed of such high-aspect-ratio, hollow microneedles are in critical demand.

Additive manufacturing (or colloquially, “3D printing”) technologies offer distinctive benefits for applications that require a high degree of geometric control in component fabrication.[32-34] Previously, researchers have demonstrated a wide range of 3D printing techniques for the fabrication of needle arrays at various scales. For example, at larger scales, Derakhshandeh et al. used extrusion-based 3D printing (e.g., “direct ink writing”) to manufacture arrays of hollow, millimeter-scale needles for drug delivery,[35] which facilitated enhanced wound healing.[36] For mesoscale needles, however, the print speed and geometric limitations of extrusion-based methods at smaller scales[37-39] have motivated investigators to instead focus on fabricating MNAs via vat photopolymerization approaches, such as stereolithography and digital light processing (DLP) 3D printing.[40-42] Unfortunately, these printing techniques are poorly suited for printing hollow MNAs that comprise needles with sub-100 µm ODs, which has led to increasing interest in the use of “direct laser writing (DLW)” for such cases.

DLW entails scanning a femtosecond pulsed IR laser in a point-by-point, layer-by-layer manner to selectively crosslink a photocurable material in target locations via two-photon (or multiphoton) polymerization to ultimately produce 3D objects comprising cured photomaterial with feature resolutions down to the 100 nm range.[43-46] Previously, researchers have demonstrated the utility of using DLW to print MNA master molds, which can then be used to replicate solid MNAs with drug coatings[47-50] or solid MNAs that are fully dissolvable.[51, 52] Additionally, Rad et al. reported the use of DLW to print molds and MNAs directly that include open (i.e., unenclosed) side channels.[53-55] For realizing hollow microneedles that are a requisite for microinjection applications, one key challenge inherent to the submicrometer-scale resolution of the DLW-printing volume element (i.e., “voxel”) is that it is ill suited for constructing the larger macro-to-microinterfaces (e.g., input ports) required for delivering fluids to the needles.[56, 57, 92] To avoid the undesirable costs and time associated with fabricating macro-to-microinterfaces in their entirety via DLW,[58] researchers have instead DLW-printed hollow singular microneedles (aspect ratios ≈4–5)[59] and MNAs (aspect ratios ≈2–5)[60] as isolated entities, and then used adhesives (e.g., glue) to manually connect the printed components to macroscale fluidic interfaces. Trautmann et al. bypassed such protocols by employing a fabrication methodology that combines femtosecond laser irradiation, annealing, grinding, and polishing to produce microchips with external openings, and then DLW-printing truncated cone-shaped MNAs (aspect ratios ≈1.3–3) directly onto the chips.[61] In contrast to the aforementioned approaches, printing MNAs directly onto fluidic connectors (e.g., at the end of capillaries) would overcome many of the current interface-associated barriers to MNA utility. Furthermore, to our knowledge, no report yet exists (for conventional or additive manufacturing-based approaches) in which MNAs are fabricated with hollow, high-aspect-ratio (e.g., ≥10) microneedles with microscale ODs (e.g., <100 µm) and high array densities (e.g., ≤100 µm needle-to-needle spacing) relevant to emerging microinjection applications, such as the delivery of therapeutic fluidic payloads directly into brain tissue.

In this work, we introduce a novel hybrid additive manufacturing strategy that entails using DLP 3D printing to fabricate batches of capillaries in set positions (Figure 1a,b), and then employing an “ex situ DLW (esDLW)” approach to DLW-print hollow, high-aspect-ratio, high-density MNAs directly onto—and notably, fluidically sealed to—the DLP-printed capillaries (Figure 1c,d). Thereafter, individual MNA-capillary assemblies can be selectively released by disrupting the connections to the batch (Figure 1e, arrows) and then interfaced with injector systems for microinjection applications. As an exemplar, we investigate the utility of the MNAs for performing microinjections into brain tissue (Figure 1f) by using excised mouse brains to not only evaluate MNA penetration into and retraction from the tissue with respect to microneedle integrity but also explore the efficacy of MNA-mediated delivery of microfluidic cargo (e.g., aqueous fluids and nanoparticle suspensions) into brain tissue ex vivo.

Conceptual illustrations of the hybrid additive manufacturing strategy for 3D microprinting hollow, high-aspect-ratio microneedle arrays (MNAs) for microinjection applications. a,b) Digital light processing (DLP)-based 3D printing of batch capillaries. a) A liquid-phase photocurable material is UV-crosslinked in designated locations in a layer-by-layer manner to produce a batch of arrayed capillaries comprising cured photomaterial. b) The DLP-printed batch of prealigned capillaries following the development process. c–e) “Ex situ direct laser writing (esDLW)” of MNAs directly atop—and fluidically sealed to—each DLP-printed capillary. c) A femtosecond pulsed IR laser is scanned to selectively initiate two-photon polymerization of a liquid-phase photocurable material in a point-by-point, layer-by-layer manner to produce MNAs comprising cured photomaterial. d) A batch array of MNA-capillary assemblies following the DLW-associated development process. e) Individual MNA-capillary assemblies within the array can be released on demand by manually severing the supporting structures (arrows). f) Example application of integrating MNA-capillary assemblies with nanoinjector systems to facilitate MNA-mediated simultaneous, distributed microinjections of target fluidic substances/suspensions into brain tissue.

Materials

Clear Microfluidics Resin V7.0a

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M50

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2 Results and Discussion

Hybrid Additive Manufacturing of Hollow MNAs

The presented hybrid additive manufacturing strategy consists of two fundamental stages: i) DLP 3D printing of batch arrays of capillaries and ii) esDLW-based printing of the MNAs directly atop each capillary. DLP 3D printing is a vat photopolymerization approach in which a DLP projector is used to UV-crosslink a liquid-phase photocurable material in designated locations in a layer-by-layer manner to ultimately produce 3D objects composed of cured photomaterial.[62] Here, we leveraged DLP 3D printing to fabricate batches of arrayed capillaries in a single print run to overcome several drawbacks of recent esDLW approaches for printing 3D micro/nanostructured objects onto mesoscale fluidic components, such as micropiston-based microgrippers[63] and liquid biopsy systems[64] onto fluidic capillaries. First, the geometric control afforded by DLP 3D printing allows for each capillary to be designed with a variable OD to match the dimensions of the capillary base to those of the desired injector system. This capillary-specific geometric customization capability obviates the need for additional fluidic adapters and/or sealants (e.g., glues) often required to couple the mesoscale capillaries to macroscale fluidic equipment (e.g., injector systems).[63-65] Second, the outer dimensions of the batch array can be designed to support facile loading into the DLW 3D printer, which eliminates the time, labor, and costs associated with manufacturing and employing custom-built capillary holders typically needed for esDLW approaches.[63-65] Lastly, the ability to print all of the capillaries in predefined array locations—with uniform surface positions and rotational orientations—addresses critical deficits associated with the use of custom-built capillary holders that rely on undesired manual (e.g., by hand and/or eye) alignment protocols for each individual capillary.[65]

For DLP 3D printing of the batch capillary arrays, we used a Miicraft M50 microfluidics DLP 3D printer (CADworks3D, Toronto, ON, Canada) to fabricate two batches (i.e., 18 capillaries in total) per print run, which corresponded to a total print time of less than 45 min (Movie S1, Supporting Information). To enable direct integration with the nanoinjector system (MO-10, Narishige International USA, Inc., Amityville, NY), we designed each capillary with a consistent inner diameter (ID) of 650 µm, but with a variable OD that was set at 1.2 mm for the top 1.5 mm and then gradually increased to 2.4 mm for the remainder of the 10 mm length of the capillary (Figure S1, Supporting Information). Fabrication results revealed effective construction of the arrayed capillaries—each attached to the batch via five connecting structures (400 µm in width and depth; 1.5 mm in length) (Figure 2a,b). In addition, the outer dimensions of the overall batch resolved such that the print could be readily loaded into the multi-DiLL holder of the DLW system (Photonic Professional GT2, Nanoscribe GmbH, Germany) (Figure S2, Supporting Information) to facilitate esDLW-based 3D printing.

Fabrication results for DLP 3D printing of batch arrays of capillaries and esDLW-based printing of MNAs. a,b) DLP prints of batch arrays of capillaries. a) Photograph of a complete batch with nine arrayed capillaries. Scale bar = 5 mm. Inset shows two batches attached to the build plate directly after DLP 3D printing (see Movie S1 in the Supporting Information). b) Low-vacuum scanning electron microscopy (SEM) images of a representative DLP-printed capillary attached to the batch via five connecting structures. Scale bars = 500 µm. c,d) The esDLW approach for printing MNAs directly onto DLP-printed capillaries in a single print run. c) Computer-aided manufacturing (CAM) simulations and d) corresponding images of the esDLW printing process. Scale bar = 250 µm (see Movie 2 in the Supporting Information). e–g) Low-vacuum SEM images of representative fabrication results showing: e) an esDLW-printed MNA atop a DLP-printed capillary following release from the batch array (see Movie S3 in the Supporting Information); f) a magnified view of the MNA; and g) a magnified view of a single microneedle tip in the array. Scale bars = e) 250 µm, f) 100 µm, and g) 25 µm.

We designed the MNAs to include identical hollow microneedles—each with an ID of 30 µm, an OD of 50 µm, and a height of 550 µm—with needle-to-needle spacing of 100 µm (Figure S3, Supporting Information). For the esDLW printing process, we initiated the print with 50 µm of overlap with the top surface of the capillary to ensure bonding at the interface. Computer-aided manufacturing (CAM) simulations and brightfield images of a corresponding esDLW process for printing the MNA directly onto a DLP-printed capillary are presented in Figure 2c,d, respectively (see also Movie S2, Supporting Information). The total esDLW printing process was completed in ≈10 min. Following development, we retrieved target MNA-capillary assemblies from the batch by manually severing the five connecting structures (Movie S3, Supporting Information). Images of the released MNA-capillary assemblies captured using low-vacuum scanning electron microscopy (SEM) revealed effective alignment and integration of the esDLW-printed MNAs with the DLP-printed capillaries, without any visible signs of physical defects along the MNA-capillary interface (Figure 2e). In addition, images of the esDLW-printed MNA and needle tips suggest that the manual release process did not appear to affect MNA integrity (Figure 2f,g).

In Silico and In Vitro Investigations of MNA Mechanical Performance

The critical first steps of MNA-based microinjection protocols involve the effective puncture and penetration into a target medium (e.g., biological tissue), which can impart significant mechanical forces on the microneedles.[66] Thus, the potential utility of MNAs is predicated on their ability to successfully withstand such mechanical loading conditions. To evaluate this capability for the esDLW-printed high-aspect-ratio MNAs, we employed both numerical and experimental approaches to elucidate the mechanical performance of the MNAs. We performed finite element analyses (FEA) to provide insight into the mechanical failure behavior of the MNAs when subjected to a compressive load applied longitudinally with respect to the needles. The simulation results revealed that each arrayed microneedle exhibited a buckling-like deformation with the largest displacements observed around the midpoint of the heights; however, needles positioned in the outer region (i.e., the needles radially arrayed farthest from the center of the MNA) displayed larger deformations compared to those located in the more central array positions (Figure 3a). This behavior arises from the load distribution caused by the disc-like base of the MNA, which deforms more in its central region than its peripherical region, thereby allowing the centrally located microneedles to rigidly displace more in the axial direction than their outer-region counterparts. According to the stress–strain curve generated from the FEA compressive loading simulations (Figure 3b), the overall MNA exhibited an effective Young's Modulus (E) of 4.31 MPa and yield strength (σy) of 135 kPa. We also numerically modeled MNA mechanics associated with puncture into the brain tissue. By characterizing the nonlinear response at the interface between the tips of the microneedles and the brain substrate, we found that the forces associated with the needles located in the outer region were larger than those in the central regions (Figure S4, Supporting Information), which is in agreement with the compressive loading analyses (Figure 3a).

Numerical and experimental results for MNA mechanical characterizations. a,b) Finite element analysis (FEA) results for a) microneedle deformations and b) stress–strain curve corresponding to MNA mechanics under compressive loading conditions. c,d) Experimental results for MNA compression testing. c) Sequential images of the MNA during axial compression test. Inset shows an SEM image of an MNA following compressive failure. Scale bars = 250 µm (see Movie S4 in the Supporting Information). d) Stress–strain curve generated from compressive loading experiments (n = 3 MNAs). e–g) Sequential images of representative MNA penetration and retraction operations corresponding to hydrogels with agarose concentrations of: e) 2.4%, f) 5%, and g) 10%. Scale bars = 500 µm (see Movie S5 in the Supporting Information).

To experimentally examine the mechanical performance of the esDLW-printed MNA, we conducted two sets of puncture and penetration-associated studies. First, we performed axial compression tests with esDLW-printed MNAs (n = 3), which revealed buckling-type deformations of the microneedles with increasing loading until complete mechanical failure (Figure 3c and Movie S4, Supporting Information). From SEM images of MNAs following compressive testing, we observed several cases of complete fracture, but the majority of the arrayed microneedles remained intact with the caveat that the tips and the overall shapes of the needles exhibited plastic deformation (Figure 3c, inset). Quantified results for the stress–strain relationships for the esDLW-printed MNAs revealed an average E of 2.12 ± 0.35 MPa and σy of 155 ± 30 kPa (Figure 3d). Although these results provide insight into the upper boundaries of mechanical loading, compression testing using an impenetrable plate is limited in its direct relevance to microinjection applications that rely on microneedle penetration into a target medium. Thus, we also investigated the capacity for the esDLW-printed MNAs to puncture and penetrate into surrogate hydrogels with increasing concentrations of agarose that correspond to varying degrees of biologically relevant stiffness. In particular, we performed experiments with agarose concentrations of: i) 1.2% (E = 12.8 ± 1.1 kPa), which would support penetration into liver and breast tissue; ii) 2.4% (E = 27.5 ± 1.0 kPa), which is relevant to brain, heart, kidney, arterial, and prostate tissue; and iii) both 5% (E = 223 ± 14 kPa) and 10% (E = 268 ± 31 kPa), which are relevant to cartilage tissues (Figure S5, Supporting Information).[67-70] Experimental results revealed that the MNA successfully penetrated into the 1.2%, 2.4%, and 5% agarose gels; however, we observed buckling of the microneedles and failure to penetrate into the 10% agarose gel (Figure 3e–g and Movie S5, Supporting Information). These results suggest that the esDLW-printed MNA is sufficient for penetration into brain tissue as well as a variety of other tissues (e.g., liver, breast, heart, kidney, arterial, and prostate tissues), but alternative photomaterials (with stronger mechanical properties) and/or microneedles with geometrically enhanced strength (e.g., by increasing the OD) would be needed for microinjection applications involving target mediums with E in excess of 250 kPa.

In Vitro Microfluidic Interrogations of MNA-Capillary Interface Integrity

One of the most catastrophic failure modes for esDLW-based prints—whether for optical,[71] photonic,[72] mechanical,[73] or fluidic[63-65] structures—is the potential for the DLW-printed objects to detach from the meso/macroscale components on which they are additively manufactured. For biomedical MNA applications, the consequences of this type of failure could be particularly serious, such as an MNA detaching from the capillary while embedded in brain tissue following microinjection. To investigate the potential for this failure mode and, in turn, provide insight into the mechanofluidic integrity of the interface between the esDLW-printed MNAs and the DLP-printed capillaries, we performed microfluidic cyclic burst-pressure tests with the MNA-capillary assemblies. Initially, using an applied pressure set at 5 kPa, we gradually infused blue-dyed deionized (DI) water into the MNA-capillary assembly via the opposing end of the capillary (i.e., the side without the printed MNA) until the fluid began exiting the tips of the arrayed microneedles (Figure 4a and Movie S6, Supporting Information). Thereafter, we performed separate sets of cyclic burst-pressure experiments (n = 100 cycles per experiment) corresponding to applied pressures set at 100, 200, and 300 kPa (Figure 4b–d). Throughout the burst-pressure testing, we monitored the MNA-capillary interface under brightfield microscopy for visible signs of undesired leakage phenomena (e.g., fluid exiting at any point along the interface rather than out of the tops of the microneedle tips); however, we did not observe any instances of such flow behavior. Similarly, quantified results of fluid flow through the MNA-capillary assembly recorded during the burst-pressure tests did not exhibit any indications of burst events—i.e., large increases in flow rates after a certain point, despite the applied pressure remaining constant—nor signs of gradual leakage phenomena associated with the flow rates increasing from pressure cycle to pressure cycle over the course of the experiment. Rather, the flow rate magnitudes corresponding to the applied input pressures remained consistent throughout the burst-pressure experiments (Figure 4b–d), suggesting uncompromised fluidic integrity of the MNA-capillary interface for all cases examined.

Experimental results for MNA microfluidic investigations. a) Sequential images during fluidic infusion. Scale bar = 500 µm (see Movie S6 in the Supporting Information). b–d) Quantified results for representative cyclic burst-pressure experiments (n = 100 cycles) corresponding to input pressures targeting: b) 100 kPa, c) 200 kPa, and d) 300 kPa.

Ex Vivo Mouse Brain Studies of MNA Penetration, Microinjection, and Retraction Functionalities

As an exemplar with which to interrogate the penetration, microinjection, and retraction capabilities of the esDLW-printed MNAs, we excised brains with intact dura mater from euthanized 6-month-old male mice (Wildtype C57BL/6 J, Jackson Laboratory) for experimentation ex vivo (Figure 5a). We performed three sets of experiments to elucidate these fundamental MNA functionalities. First, we investigated the ability to execute penetration and retraction operations (but not fluidic microinjections) with the MNAs as critical measures of performance with respect to three potential failure modes that would critically limit the efficacy of the esDLW-printed MNAs: i) the sharpness of the tips of the microneedles—governed by the resolution of the DLW 3D printer—is insufficient to puncture the brain tissue without inducing significant deformation of the brain; ii) the mechanical properties of the high-aspect-ratio microneedles lead to buckling and/or fracture of the microneedles prior to effective penetration into the brain tissue; and/or iii) the forces during the penetration or retraction processes fracture the microneedles, causing microneedles (or fragments of microneedles) to remain embedded in the brain tissue after retraction completion. To facilitate the penetration and retraction studies, we interfaced each MNA-capillary assembly examined with a nanoinjector system fixed to a stereotactic frame as a means to enable precise position control while optically monitoring the MNA-brain tissue interactions. Experiments performed with three distinct MNA-capillary assemblies (n = 3 penetration and retraction operations for each distinct MNA-capillary assembly) revealed that the MNAs could successfully puncture the brain tissue within 1 mm of total displacement from initial contact and, importantly, without any visible signs of mechanical failure during any of the penetration or retraction operations (Figure 5b and Movie S7, Supporting Information). Images of the MNAs (captured after completion of the retraction process) corroborated these results, without any indications of microneedle-associated failure modes (e.g., buckling or fracture) or MNA detachment from the capillary (Figure 5c).

Experimental results for ex vivo MNA penetration, microinjection, and retraction operations using an excised mouse brain. a) Experimental setup including the MNA-capillary assembly interfaced with a custom-built nanoinjector and an excised mouse brain on ice. b,c) Brain tissue puncture and retraction results. b) Sequential images of MNA insertion into (≤20 s) and retraction from (≥20 s) the brain tissue. Scale bar = 1 mm (see Movie S7 in the Supporting Information). c) SEM image of the MNA after retraction from the brain tissue. Scale bar = 250 µm. d–f) MNA-mediated microinjection results. d) Sequential images of a representative MNA penetration, microinjection, and retraction process for a surrogate fluid (blue-dyed DI water) injected into brain tissue. Scale bar = 1 mm (see Movie S8, Supporting Information). e) Magnified view of the postinjection site. Scale bar = 250 µm. f) SEM image of the MNA following microinjection into the brain tissue. Scale bar = 250 µm.

After validating the penetration and retraction capabilities, we then initially investigated the microinjection functionality of the MNAs based on the ability to deliver a surrogate microfluidic payload into the brain tissue. In this case, we preloaded the MNA-capillary assembly with blue-dyed (1.5% Evan's Blue) DI water, and then interfaced the assembly with the nanoinjector (Figure 5a, expanded view) for control of both the MNA position and fluidic microinjection dynamics. Although the results for the cyclic microfluidic burst-pressure experiments performed in vitro (Figure 4b–d) suggested that the MNA-capillary interface should withstand the forces associated with microinjections into the brain tissue, we optically monitored the overall MNA-capillary assembly during the microinjection process for potential signs of undesired leakage via the interface. Akin to the tissue penetration and retraction studies, we used the stereotaxic frame to guide the descent of the MNA into the brain tissue (Figure 5d, top and Movie S8, Supporting Information). Following completion of the penetration process, we then used the pneumatically controlled nanoinjector to dispense the surrogate dyed fluid through the MNA-capillary assembly and, in turn, deliver the fluid into the brain tissue. Thereafter, we retracted the MNA from the brain (Figure 5d, bottom and Movie S8, Supporting Information), and then washed the surface of the injection site with phosphate buffered saline (PBS) to eliminate any residual surrogate fluid from the surface, such that the only remaining fluid was located beneath the tissue surface (Figure 5e). Throughout the microinjection process, we did not observe any undesired leakage phenomena (Movie S8, Supporting Information), with optical characterizations of the postinjection site indicating effective, distributed MNA-mediated delivery of the surrogate fluid well below the surface of the excised brain (Figure 5e). Furthermore, SEM images of the MNA-capillary assembly following tissue penetration, fluidic microinjection, and retraction revealed uncompromised structural integrity (Figure 5f).

Lastly, we evaluated the microinjection performance of the esDLW-printed MNA compared to a conventional needle (Hamilton 33G) widely used for delivering therapeutics into brain tissue.[74] In this case, we used a suspension of fluorescently labeled nanoparticles (100 nm in diameter) as the surrogate microfluidic payload. As an initial positive experimental control for the esDLW-printed MNA, we performed microinjections (n = 3 MNAs) of the nanoparticle suspension into 0.6% agarose gel in vitro (Figure 6a and Movie S9, Supporting Information) and visualized the particle distributions using two-photon (Figure 6b S10) and widefield fluorescence microscopy (Figure 6c). We observed injected nanoparticles corresponding to each microneedle in the array—which included one microneedle in the center of the array, six needles arrayed radially in a middle region (150 µm from the center), and six needles arrayed radially in an outer region (260 µm from the center)—but to determine if microneedle array position influenced injection behavior, we analyzed the fluorescence intensities associated with each arrayed needle. Quantified results revealed that the fluorescence intensities were statistically indistinguishable, with no discernable difference for the microneedle injection sites between the center and either the middle (p = 0.66) or outer regions (p = 0.61), nor between the middle and outer regions (p = 0.72) (Figure 6d). Thereafter, we performed microinjections of the nanoparticle suspension into excised mouse brains using both the conventional needle and the esDLW-printed MNA (Figure 6e and Movie S10, Supporting Information). Two-photon fluorescence images of the injection sites revealed stark differences in the nanoparticle distributions associated with each needle system. In the conventional needle case, the nanoparticles accumulated tightly within the single needle track (Figure 6f,g). For example, quantified fluorescence intensity results revealed that the majority of the fluorescence signal was detected within an ≈150 µm region (Figure 6h). In contrast, MNA-associated microinjection sites exhibited a more homogeneous distribution of injected nanoparticles over a larger area (Figure 6i,j)—with particles detected at sites corresponding to each arrayed microneedle—resulting in a more consistent fluorescence signal along the length of the injection site (Figure 6k). These results suggest that MNAs offer an effective means to distribute fluidic payloads more uniformly over a larger area compared to conventional single-needle systems. In combination, these experimental results for MNA penetration, surrogate fluid/suspension delivery, and retraction functionalities using an ex vivo mouse brain provide an important foundation for the utility of the presented hybrid DLP-DLW-enabled MNAs for microinjection applications.

Experimental results for microinjections of fluorescent nanoparticles a–d) in vitro in 0.6% agarose gels and e–k) ex vivo using excised mouse brains. a) Sequential images of nanoparticle microinjection and retraction. Scale bar = 250 µm (see Movie S9 in the Supporting Information). b,c) Fluorescence images of the postinjection site captured using b) two-photon and c) widefield fluorescence microscopy. Scale bars = 250 µm. d) Mean fluorescence intensities of injection sites corresponding to microneedles in distinct array regions (n = 3 MNAs). Error bars = S.D. e) Sequential images of a representative MNA penetration, microinjection, and retraction process for a suspension of fluorescent nanoparticles injected into brain tissue. Scale bar = 1 mm (see Movie S10 in the Supporting Information). f–k) Postinjection results for fluorescent nanoparticles delivered via f–h) a conventional Hamilton 33G needle, and i–k) an esDLW-printed MNA. f,g,i,j) Fluorescence images of the postinjection site captured using two-photon fluorescence microscopy visualized in f,i) side and g,j) cross-sectional views. Scale bars = 250 µm. h,k) Quantified fluorescence intensities along the length of the corresponding cross-sectional views of the postinjection sites.

3.Conclusion

Microneedle-based microinjection protocols are essential to wide-ranging fundamental research and clinical applications across biological and biomedical fields, with MNAs providing numerous benefits over their single-needle counterparts in many scenarios.[75-77] Unfortunately, manufacturing-associated limitations have heretofore impeded researchers from leveraging the potential benefits of high-density MNAs comprising hollow, high-aspect-ratio microneedles at small length scales.[78-80] In this work, we introduced the concept of using esDLW to 3D print MNAs directly atop DLP-printed capillaries in batch arrays and demonstrated this approach by fabricating arrays of 50 µm OD, 30 µm ID, 550 µm tall hollow microneedles with 100 µm needle-to-needle spacing. Because the presented strategy is founded on two additive manufacturing technologies, the inherent geometric versatility can be harnessed to tailor both the DLP-printed capillaries and the esDLW-based MNAs to target experimental setups and applications. For the DLP-printed capillary, the shape and size need not be uniform along the length of the capillary as is the predominant case for conventional and/or commercially available fluidic capillaries. Here, for instance, we designed the OD of the base of the capillary to yield facile, direct integration with the nanoinjector, thereby circumventing the need for additional fluidic adapters or sealants. Similarly, although the presented design for the esDLW-printed MNAs included identical microneedles with dimensions based on a specific exemplar—i.e., fluidic microinjection into the cerebral cortex of a mouse brain—the high architectural control and submicrometer-scale resolution of DLW can be leveraged to customize the size, shape, and position of each individual microneedle in an array as desired (Figure S4, Supporting Information). For example, future efforts could increase the microneedle heights substantially to target different regions of the brain and/or additional animal models. Conversely, while this work centered on printing hollow microneedles (with 30 µm IDs) to support fluidic delivery operations, given the recent developments for the utility of solid MNAs in other cases, the presented strategy could also be extended to print MNAs composed of solid microneedles, such as those fabricated using DLW-compatible biodegradable materials,[81, 82] or potentially hybrid MNAs that comprise both hollow and solid microneedles.

The presented strategy also provides an important foundation for future academic and industrial translation through four pathways. First, in contrast to prior esDLW efforts, DLP-printing of the batch arrays of fluidic capillaries allows for facile loading into the DLW 3D printer, obviating the need for custom-built capillary holders as well as the time- and labor-intensive protocols required to manually load each individual capillary into such holders. Furthermore, because each capillary is printed in a designated array position with specified orientations, the setup for initiation of the esDLW-printing process is minimized, which could provide a promising avenue to scalable and automated production. Second, although we employed a layer-by-layer DLP printer to manufacture the batch arrays of fluidic capillaries, numerous vat photopolymerization approaches could be used instead to increase production speed, including continuous liquid interface production to print parts in minutes[83] and various volumetric 3D printing strategies to fabricate parts in tens of seconds.[84-86] Third, for esDLW-based printing of the MNAs, while the voxel size remained constant throughout the printing process with a scan speed of ≈120 mm s−1, future efforts can harness recent advancements for state-of-the-art DLW printers that can not only dynamically tailor the size of the voxel to target features but also allow for scan speeds up to 1,250 mm s−1 (e.g., with 5× objective lens configurations) in order to dramatically enhance print efficiency and speed. Lastly, recent improvements in the available build area for commercial DLW printers could be extended to print multiple MNAs simultaneously in a single pass (in contrast to the serial MNA printing strategy reported here), which would further increase the attainable production volume.

The numerical and experimental mechanical characterizations of the esDLW-printed MNA suggest that, in addition to brain tissue, the MNA described in this work could be used to facilitate microinjections for a wide range of additional biological tissues, including those associated with the liver, breast, heart, kidney, veins, arteries, and prostate.[67-70] For future efforts based on different injection targets with higher stiffness (e.g., E > 250 kPa), however, the inability of the presented MNA to successfully penetrate into the 10% agarose gel indicates that, for the current design, alternative photomaterials should be used for esDLW-based printing. In particular, researchers have reported DLW-compatible fused silica glass-based photomaterials,[87] which are now available commercially and would provide an order of magnitude increase in E of the fabricated MNAs. Alternatively, while we designed each microneedle with 10-µm-thick walls and 50 µm ODs, both dimensions could be readily increased to improve the mechanical strength. For excised mouse brains specifically, the ex vivo investigations in the current study revealed effective MNA-mediated penetration, microinjection, and retraction operations without any instances of microneedle-associated mechanical failures (e.g., buckling or fracture). In addition, throughout both in vitro microfluidic cyclic burst-pressure characterizations (with applied pressures in excess of 250 kPa) and ex vivo brain tissue experiments, the MNA-capillary interface exhibited consistent fluidic integrity, without any signs of undesired leakage phenomena or MNA detachment from the capillary.

We envision that future efforts could extend the methodology reported here to achieve novel MNA designs that remediate the deficits of single-needle injection strategies by expanding the delivery range via simultaneous, distributed microinjection. For example, as both in vitro and ex vivo experiments for MNA-mediated microinjections of nanoparticle suspensions revealed homogeneous distributions of implanted particles, such capabilities could offer new means to address the cell crowding challenges of SCT associated with single-needle delivery systems that contribute to low cell viability and, thus, limited therapeutic efficacy.[88-91] Such a pathway to improved SCT could hold distinctive promise for treating a diversity of medical conditions and neurodegenerative diseases, but further studies are needed to explore the potential for MNAs at this scale to enhance therapies that rely on fluidic microinjections—not only for stem cells, but also additional therapeutic payloads (e.g., growth factors and viruses for gene therapy)—into the brain. Nonetheless, given the vast diversity of scientific and clinical applications that are founded on microinjections and/or microneedles, the presented hybrid additive manufacturing strategy offers unique potential as an enabling technology for realizing entirely new classes of MNAs to advance scientific discovery and promote human health and well-being.

4.Experimental Section

Batch Capillary Array Fabrication via DLP 3D Printing

The computer-aided design (CAD) software, SolidWorks (Dassault Systèmes, France), was used to generate models of batch arrays of capillaries (Figure S1, Supporting Information). Models were exported as STL files and then imported into the CAM (slicer) software for the Miicraft M50 DLP 3D printer (CADworks3D, Canada) to define the print parameter settings (Table S1, Supporting Information). The batch capillary arrays were DLP-printed using Clear Microfluidics Resin V7.0a (CAdworks3D) with the layer height set to 50 µm. Following the DLP printing process, the build plate was removed and the prints were manually detached from the build plate using a razor blade. The prints were developed in methanol for ≈10 s and then methanol was perfused through each capillary to eliminate any residual resin from the interiors. After one additional rinse with methanol, the prints were washed with 90% isopropyl alcohol (IPA). The prints were then dried with pressurized air and postcured under UV light for 20 s (flipping the device after 10 s to cure both sides equally).

MNA Fabrication Atop the Capillaries via esDLW

The microneedle arrays—modeled using SolidWorks (Dassault Systèmes)—were designed with identical needles (ID = 30 µm; OD = 50 µm; height = 550 µm) and arrayed with 100 µm needle-to-needle spacing (Figure S3, Supporting Information). MNA models were exported as STL files and then imported into the CAM software, DeScribe (Nanoscribe), to define the print parameter settings (Table S2, Supporting Information), which included a hatching distance of 800 nm and a layer height of 2.5 µm. Initially, IP-Q photoresist (Nanoscribe) was dispensed directly atop the DLP-printed capillaries and the batch was then loaded into the Nanoscribe Photonic Professional GT2 DLW 3D printer (Figure S2, Supporting Information). For esDLW printing, the dip-in laser lithography (DiLL) mode was used with a 10× objective lens, a laser power of 27.5 mW, and a laser scanning speed of 120 000 µm s−1. The printing process was initiated with 50 µm of overlap with the top capillary surfaces. Following the esDLW process, the batch assembly (with MNAs printed atop the capillaries) was removed from the DLW printer for development. The prints were developed using propylene glycol monomethyl ether acetate (PGMEA) for 30 min and IPA for 5 min, and then dried using a gentle stream of N2 gas. Individual MNA-capillary assemblies were removed from the batch by manually severing the five connecting structures arrayed radially around each capillary (Movie S3, Supporting Information).

Finite Element Analysis (FEA)

Numerical simulations of the MNA compression test were performed using the commercially available software, ABAQUS/Standard (Abaqus Inc., Palo Alto, CA). Initially, the complete 3D CAD model of the MNA (i.e., including both the base and needles) was imported into the FEA software, and then the distinct material properties were set. Specifically, the MNA was modeled as a linear elastic homogeneous material (E = 250 MPa; ν = 0.49). The mesh was constructed using four-node, linear, 3D-stress-tetrahedra elements (ABAQUS element type C3D4H), and the accuracy was verified by mesh convergence. During all studies, the circular bottom surface orthogonal to the loading direction was modeled to be perfectly fixed. A static analysis (STATIC step with NLGEOM = ON in ABAQUS) was conducted to characterize the nonlinear response and loaded the structure by linearly increasing the applied tip force. To characterize the nonlinear response at the interface between the needle tips and the brain substrate, the bottom surface of the cylinder mimicking the brain sample was modeled to be fully clamped while a displacement was applied to the MNA's cylindrical base. A surface-to-surface contact was defined between the brain substrate and the MNA needle tips. Both tangential and normal contact behaviors were defined. The MNA was modeled as a linear elastic homogeneous material, while the brain substrate was modeled as a hyperelastic Neo-Hookean material. To characterize the nonlinear response at the interface between the needle tips and the brain substrate, a dynamic implicit analysis (DYNAMIC step with NLGEOM = ON in ABAQUS) was conducted.

MNA Mechanical Characterization

Mechanical testing on the MNAs was conducted using a Q800 Dynamic Mechanical Analysis (DMA) system (TA Instruments, New Castle, DE) equipped with a compression clamp. Samples were compressed at a rate of 0.1 N min−1 until the failure was confirmed via optical microscopy. Values for E and σy of MNAs were calculated from the linear region of the resulting stress-strain curve. To evaluate the puncture ability of the MNAs, hydrogels with different stiffness were prepared by mixing agarose gel powder in 1% PBS (Sigma-Aldrich, Saint Louis, MO) at four different concentration levels: 1.2%, 2.4%, 5%, and 10%. The solutions were heated to a boiling temperature and then cooled down until the hydrogels were set at room temperature. Before each MNA puncture, the top surface of the hydrogel was rinsed with PBS. The MNA was mounted on a stereotaxic manipulator, slowly inserted into the hydrogel samples, and optically monitored for any signs of failure.

Ex Vivo Mouse Brain Extraction and Experimentation

Brain tissues excised from 6-month-old male mice (Wild-type C57BL/6 J, Jackson Laboratory) were used for all ex vivo experiments. Each brain with an intact dura mater was excised within 10 min of euthanasia and stored in cold PBS on ice prior to testing. To maintain tissue integrity, the tissue samples were handled gently before and during the experiment. Each MNA-capillary assembly was interfaced with a custom-built nanoinjector (Narishige) and mounted on a stereotax with a digital display (#68807, RWD, China) to control the displacement and perform microinjections. In separate experiments, blue-dyed water and green fluorescent nanoparticles (505/515, 100 nm diameter, #F8803, Thermofisher) diluted with PBS were injected into the freshly dissected mouse cerebral cortex (or agarose gel) using either an MNA-capillary assembly connected to a micromanipulator (#MO10, Narishige) or a Hamilton syringe with a 33G needle connected to a motorized pump (#78–8130, KD Scientific, Holliston, MA). The injection depth was 500 µm with an extra 200 µm overshoot. The injection duration was ≈2 min for both MNA and Hamilton syringe-mediated injections. After injection with fluorescent nanoparticles, the fresh mouse brains were fixed with 4% paraformaldehyde for 2 d, rinsed, and mounted on glass slides for imaging under a two-photon microscope. These studies were performed in accordance with the National Institutes of Health (NIH) Guide for Care and Use of Laboratory Animals and the University of Maryland, School of Medicine, Animal Care and Use Committee.

Optical Characterizations

SEM images were captured using a TM4000 Tabletop SEM (Hitachi, Tokyo, Japan) under low vacuum, which allowed for imaging of uncoated samples. The mechanical tests were recorded using a Monocular Max 300× microscope objective and a 41MP USB C-Mount Industry Microscope Camera Set (Hayear Electronics Co. Ltd., Shenzhen, China). Brightfield microscopy during microfluidic testing was performed using an inverted microscope (Motic AE31, Motic, Canada) connected to a CCD camera (Moticam Pro 285B, Motic). For ex vivo microinjection experiments, the injection process was recorded using the Monocular microscope while the fluorescent images of the top view of the gel injection site were captured using a DMi8 automated fluorescence microscope (Leica Microsystems, Wetzlar, Germany). The 3D stack images of the injection sites were acquired using the Modular In Vivo Multiphoton Microscopy System designed by Janelia Research Campus, Howard Hughes Medical Institute. A 900 nm laser (≈5 mW) was used for excitation of the green fluorescent nanoparticles. The 3D stacks from the top of the brain to the bottom of the needle track were acquired at a step size of 2 µm under a water-immersion 25× objective (numerical aperture of 1.05, Olympus). Fluorescence emission was collected by two GaAsP photomultiplier tubes after being split by a dichroic mirror (560 nm, T560pxrxt, Chroma) with an emission filter green (510/84 nm, 84–097, Edmund) fluorescence. A similar acquisition setting was used for imaging the needle tracks in hydrogels injected with the fluorescent nanoparticles. Fluorescence images were processed and visualized with ImageJ (NIH, Bethesda, MD). BigDataViewer was used to adjust the tilting angle of the 3D stack for optimized visualization. For comparisons of needle-to-needle injection sites within the MNAs as well as injection distributions between the MNA and Hamilton injections, ImageJ was used to quantify the fluorescence intensities.

Statistical Analysis

Statistical significance was quantified via unpaired Student's t-tests, with two-tailed p values greater than 0.05 considered statistically indistinguishable. A minimum of three samples were used to quantify any means reported, with data presented in the text as mean ± standard deviation (S.D.).

Acknowledgements

The authors greatly appreciate the contributions of Olivia Young, Michael Restaino, and Chen-Yu Chen, as well as additional members of the Bioinspired Advanced Manufacturing (BAM) Laboratory and the William Bentley Laboratory. The authors appreciate the help and support of staff members at the University of Maryland Terrapin Works and the Micro/Nanofabrication Center at the Princeton Institute of Materials. This work was supported in part by the Maryland Robotics Center, the Center for Engineering Concepts Development (CECD), U.S. NIH Award Numbers 1R01EB033354-01, 1R03NS123733-01, 1R21AG077631-01, 1R03NS128459-01, 1R01EB019963, and F31DK129021, the Maryland Stem Cell Research Fund 2022-MSCRFL-5893, and U.S. National Science Foundation (NSF) Award Number 1943356. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH. Correction added on 10th March 2023 after initial publication: The affiliation for P. Walczak was corrected.]

Conflict of Interest

The authors declare no conflict of interest.

Impact of Scala Tympani Geometry on Insertion Forces during Implantation

January 16, 2026November 5, 2022 by CadWorks3DAdmin

Impact of Scala Tympani Geometry on Insertion Forces during Implantation

Filip Hrncirik, Conceptualization, Methodology, Writing – original draft,† Iwan V. Roberts, Conceptualization, Methodology, Writing – original draft, Funding acquisition,,† Chloe Swords,Peter J. Christopher, Conceptualization, Writing – review & editing, Akil Chhabu, Andrew H. Gee, and Manohar L. Bance, Writing – review & editing, Supervision, Funding acquisition, Conceptualization

Background: During a cochlear implant insertion, the mechanical trauma can cause residual hearing loss in up to half of implantations. The forces on the cochlea during the insertion can lead to this mechanical trauma but can be highly variable between subjects which is thought to be due to differing anatomy, namely of the scala tympani. This study presents a systematic investigation of the influence of different geometrical parameters of the scala tympani on the cochlear implant insertion force. The influence of these parameters on the insertion forces were determined by testing the forces within 3D-printed, optically transparent models of the scala tympani with geometric alterations. (2) Methods: Three-dimensional segmentations of the cochlea were characterised using a custom MATLAB script which parametrised the scala tympani model, procedurally altered the key shape parameters (e.g., the volume, vertical trajectory, curvature, and cross-sectional area), and generated 3D printable models that were printed using a digital light processing 3D printer. The printed models were then attached to a custom insertion setup that measured the insertion forces on the cochlear implant and the scala tympani model during a controlled robotic insertion. (3) Results: It was determined that the insertion force is largely unaffected by the overall size, curvature, vertical trajectory, and cross-sectional area once the forces were normalised to an angular insertion depth. A Capstan-based model of the CI insertion forces was developed and matched well to the data acquired. (4) Conclusion: By using accurate 3D-printed models of the scala tympani with geometrical alterations, it was possible to demonstrate the insensitivity of the insertion forces to the size and shape of the scala tympani, after controlling for the angular insertion depth. This supports the Capstan model of the cochlear implant insertion force which predicts an exponential growth of the frictional force with an angular insertion depth. This concludes that the angular insertion depth, rather than the length of the CI inserted, should be the major consideration when evaluating the insertion force and associated mechanical trauma caused by cochlear implant insertion.

Keywords: cochlear implant, 3D printing, scala tympani, insertion forces, micro-CT

We kindly thank the researchers at Cambridge, UK for this collaboration, and for sharing the results obtained with their system.

1. Introduction

There are over 466 million people worldwide that suffer from disabling hearing loss and is expected to rise to 700 million by 2050 [1]. As the second leading disability worldwide [2], hearing loss can be severely debilitating and has been linked to depression [3,4,5,6,7], dementia [8,9,10,11], and living discomfort [12,13,14].

Those suffering from severe to profound sensorineural hearing loss can benefit from cochlear implants (CIs), a transformative technology that helps people regain their hearing. However, a key limitation in increasing the eligibility of CIs is the damage caused to the cochlea during the insertion of these implants as well as the resulting chronic inflammatory response. This insertion trauma has been shown to reduce or destroy the residual acoustic hearing in up to 50% of implantations [15,16,17,18,19]; therefore, only those with the most severe hearing loss are currently implanted.

A CI consists of a linear array of 12–22 platinum-based electrodes insulated by silicone connected via a lead to a processor placed on the skull. The electrode array is typically inserted into the scala tympani (ST) chamber of the cochlea, in the inner ear, which is a hollow spiral-shaped chamber within the mastoid bone, filled with perilymph fluid. In order to be implanted, patients must undergo surgery where the skin is opened behind the pinna, and the skull and mastoid bone are drilled until the facial nerve, chorda tympani, and incus are visible. These landmarks are used to find the round window, an opening to the ST covered with a membrane that can be easily penetrated and which provides an entry point for the CI insertion. The common approach is to implant through the round window niche and round window where possible, rather than through a cochleostomy [20,21,22,23,24,25], which requires surgeons to create a new entry to the ST by drilling into the cochlea. Implanted CIs can then electrically stimulate the auditory nerves in the modiolus (the inner part of the cochlea spiral) and facilitate “electronic hearing”.

Furthermore, by avoiding key auditory structures (i.e., the eardrum and the middle ear) during implantation, patients can retain some residual hearing and benefit from some limited auditory cues. Furthermore, electro-acoustic stimulation (EAS), which is a combination of CI electrically stimulated hearing and low-frequency acoustic amplification, has been shown to improve the listening performance [26,27,28,29]. Additionally, destroying the residual hearing eliminates the possibility of a patient potentially being eligible for future therapies to restore the acoustic hearing, such as gene therapies [30]. Therefore, it is necessary to protect patients’ residual hearing whenever possible.

The loss of natural hearing is often associated with the mechanical trauma that arises during the CI insertion [17,18,19,31,32], which might result in fibrosis and neural degeneration, further limiting the CI performance [18,33,34]. Generally, there are two types of CI: (1) straight, which follows the lateral wall of the ST, and (2) perimodiolar, which is pre-curved and follows the modiolar (inner) wall of the ST. Although perimodiolar electrodes can, in theory, be placed closer to the target neural population, their placement can also risk more insertion trauma [35]. For straight electrodes, the initial contact is with the lateral wall of the ST, which is lined with soft tissue, and the CI slides along the lateral wall throughout the insertion. The basilar membrane, located along the top part of the lateral wall, accommodates the organ of Corti, which facilitates acoustic hearing. It is crucial to avoid damaging, or penetrating in some circumstances, this membrane as it can result in the permanent loss of hearing in that region [36,37].

Although CIs are a triumphant story of permanently implantable devices, there are still limitations in the implantation process. For instance, CIs are commonly inserted manually by a skilled surgeon; however, it has been shown that the stable, slow insertion speeds achieved with a robotic and a semi-robotic insertion setup could lower insertion forces (IFs) significantly [33,38,39,40]. Furthermore, there has been uncertainty about the effect of the CI size and its influence on the IFs. Historically, there has been a trade-off between making longer implants that could electrically stimulate a larger proportion of the cochlea, and convey a larger range of frequencies [41,42], and preventing large IFs at deeper insertions. The higher IF and related mechanical trauma have led the CI industry to converge to a “one size fits all” approach where newer CI electrode arrays are typically around 20 mm in length [43,44]. Additionally, few studies investigated how the ST size may affect IFs [45,46,47,48]; however, these either used artificial models with combined scalae (not a true ST model) or they did not investigate the individual parameters that might contribute to higher IFs.

This study aims to investigate the impact of the ST geometry on IFs. By systematically adjusting the key parameters of the ST, such as the volume, vertical trajectory, curvature, and cross-section area, it is possible to determine the influence of these individual components on the IFs. Furthermore, this can inform the optimal CI insertion strategies to improve patient outcomes by creating a mechanistic model from the acquired insights that match our experimental observations.

Materials

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2. Materials and Methods

2.1. Micro-CT Segmentation of Scala Tympani

A cadaveric specimen was imaged with a Nikon XT 225 ST micro-computed tomography (micro-CT) scanner with an accelerating voltage of 160 kV, current of 180 µA, and a voxel resolution of 27 µm. The specimen was reconstructed using Stradview software (version 7.0, https://mi.eng.cam.ac.uk/Main/StradView, accessed on 10 March 2022). Important landmarks highlighting 68 points along the basilar membrane on the ST surface were added, so complete parametrisation using a custom-built MATLAB script was possible.

2.2. Characterisation of Scala Tympani

The 3D PLY files exported from the segmentation were imported into a custom MATLAB script for analysis together with the coordinates of landmarks along the cochlear trajectory. This workflow used the gptoolbox [49] and geom3D [50] libraries available on the MathWorks FileExchange. Using a similar methodology to Gee et al. [51], a best-fit plane was determined for the landmark point coordinates along the first 270 degrees of the basal turn of the basilar membrane. This enabled the separation of the vertical (height) and radial (spiral) components of the cochlear trajectory.

The cross-sections of the ST model were determined by producing planes along the cochlear trajectory perpendicular to the cochlear lumen according to the landmarks placed along the ST and calculating the closest intersection of the plane and cochlear mesh to that landmark (to eliminate intersections through multiple turns of the cochlea).

This spiral, represented by the centroids of the cross-sections, was fitted to the following equation defining the radius of the curve, R, in terms of angle, θ, in degrees:

where Rscale parametrises the overall scale of the cochlea, and θ1 and θ2 characterise the tightness of the basal turn and central spiral, respectively. This is a modification of previous piecewise definitions [52,53,54] of the cochlear spiral in favour of a continuous double exponential function [55], which fits the whole cochlea while accounting for the “flaring out” of the base. Using a continuous function offers several advantages in the mathematical modelling and shape manipulation when compared to a piecewise function. Note, for the conversion of electrode insertion distance to degrees, Equation (1) was applied to the basilar membrane landmarks for each ST model as the CI would follow the lateral wall rather than the middle of the ST which was confirmed/adjusted according to the actual maximal insertion angle manually measured from the video of each insertion.

2.3. Manipulation of Scala Tympani Shape

In order to manipulate the shape of the cochlea, the extracted cross-sections described in Section 2.2 were positioned according to the required shape manipulation, as detailed below.

A custom lofting function was created in MATLAB to re-connect the cross-sections into a 3D mesh geometry from individual cross-sections. This involved sorting the vertices of the cross-sections in a clockwise direction (with respect to the base), interpolating the cross-sections to have 100 points each, triangulating the vertices between each cross-section in turn, and capping the ends to produce a fully enclosed mesh.

2.3.1. Cochlear Size Manipulation Volumetric scaling of the ST was conducted by directly multiplying the vertices of the original ST mesh by a constant factor to produce “large” (110% volumetric scaling) and “small” (90% volumetric scaling) models.

2.3.2. Vertical Trajectory Manipulation For vertical trajectory manipulation experiments, the z-component of the ST cross-sections was altered without changing the radial trajectory of the ST. For the “flat” models, the z-component of each cross-section was subtracted from each vertex so that the ST centreline would be a two-dimensional spiral along the basal plane.

In order to simulate non-planarity, a sinusoidal function was added to the mean z-component of each cross-section from 0–270°. The amplitude of the sinusoidal change was set at 200 µm, and the period was set at either 270° or 135° for conditions of artificial non-planarity 1 (NP1) and artificial non-planarity 2 (NP2), respectively.

2.3.3. Curvature Manipulation In order to manipulate the curvature of the ST models, the parameters of the fitted spiral Equation (1) were manipulated. Specifically, θ2 was doubled for the loose model and halved for the tight one to either decrease or increase the curvature of the inner spiral, respectively. The ST cross-sections were projected along this new spiral and lofted into a 3D structure ready to produce a 3D print.

2.3.4. Uniform Cross-Section Models Uniform cross-section models used a consistent cross-section (from 1 mm from the round window) projected onto the original ST centreline to build models with the same trajectory as the original ST but with a uniform cross-section.

2.4. 3D Printing an Artificial Scala Tympani

A custom MATLAB script, utilising Boolean operations from the gptoolbox library, was used to generate 3D printable stereolithography (STL) files for 3D printing. Scala tympani orientation was controlled to be consistent for all models where the first 10–20° degrees of the ST were orientated along the x-axis of insertion. In addition, the basal end of the ST remained open to provide a consistent entry trajectory, and an access hole was produced at the ST apex to allow for flushing of the models with solutions prior to insertion.

Prepared models were then printed at 30 µm resolution on a CADworks3D printer (M-50, CADworks3D μmicrofluidics, Toronto, ON, Canada) with Clear Microfluidics Resin (V7.0a, CADworks3D μmicrofluidics, Toronto, ON, Canada). The printed models were then post-processed using 99.9% isopropyl alcohol (SLS Ltd., Nottingham, UK). Lastly, the models were cured three times for 10 s with a one-minute break between the runs using a CureZone UV chamber (CADworks3D μmicrofluidics, Toronto, ON, Canada).

In order to achieve the transparent finish of the models, acrylic coating (Pro-cote Clear Laquer, Aerosol Solution) was used for coating the lumen (inner part) of the models. The coating was injected into the ST model, left for 10 s, and excess was then removed using compressed air to leave a thin layer to smooth the surface and achieve a clear finish. In addition, 5% solution of Pluronic (F-127, Merck KGaA, Germany) and distilled water was used for coating the lumen of the models 24 h prior to insertion to lower friction coefficient of the printed models.

2.5. Insertion Setup

A custom-built insertion setup used in this study consisted of several components, namely a one-axis force sensor (500 mN Load Cell, 402B, Aurora Scientific Europe), a six-axis force sensor (NANO 17Ti transducer, ATI Industrial Automation, Apex, NC, USA), a one-axis motorised translation stage (PT1/M-Z8, Thorlabs, UK) with a K-Cube brushed DC servo motor controller (KDC101, Thorlabs, UK), a high-precision rotation mount (PR01/M, Thorlabs, UK), a large dual-axis goniometer (GNL20/M, Thorlabs, UK), an XYZ translation stage (LT3/M, Thorlabs, UK), a high-sensitivity CMOS camera (DCC3240C, Thorlabs, UK), a ring illumination lamp (Kern OBB-A6102, RS Components, UK), and a Nexus breadboard (B6090A, Thorlabs, UK). The data acquisition was facilitated by a DAQ (USB-6210 Bus-powered, National Instruments Ltd., UK) and a connected laptop (DELL, Austin, TX, USA). A Form 3B 3D printer (Formlabs, Somerville, MA, USA) with Grey Pro resin (Formlabs, Somerville, MA, USA) was utilised to fabricate the necessary parts for attaching the aforementioned components. A custom C# program was used to synchronise the stepper motor insertion with force measurements and video recording.

The one-axis sensor was attached to the motorised translation stage with a custom adapter to facilitate the insertion movement. The six-axis sensor was attached to the dual-axis goniometer, located on the top of the rotation mount and the XYZ translation stage. The camera and the ring light were attached above the six-axis sensor to illuminate the model correctly to observe the implant behaviour during the insertion (see Figure 1).

A practice cochlear implant electrode (Cochlear Slim Straight CI422, Cochlear Europe Ltd., UK) was attached to the one-axis sensor, and a 3D-printed artificial ST model was connected to the six-axis sensor. A 1% solution of sodium dodecyl sulfate (SDS, Sigma Aldrich) in distilled water was injected into the model prior to the insertion for lubricating the lumen of the model [56,57]. The insertion speed, facilitated by the motorised translation stage, was set to 0.5 mm/s, and the insertion depth from the artificial model opening was set to 20 mm (only “small” and “tighter spiral” models were inserted to 17 mm). After the full insertion, a 5 s long pause was introduced, and then the electrode was retracted. Each model was implanted ten times combined over two identical CIs that were re-straightened by hand after every insertion.

To eliminate bubbles, the ST model was periodically filled with solution up until a point where no leakage of the fluid would occur due to surface tension at the ST basal opening.

2.6. Fitting of Insertion Forces to a Capstan Model

Capstan Model It has been shown before [58,59] that the forces on the implant can be modelled similarly to a classical Capstan problem. The Capstan problem is a statics problem—Figure S1 (left)—encountered when attempting to pull a rope around a rigid bollard. For a non-elastic, flexible, thin line on the verge of sliding around a rigid bollard, the problem can be modelled as

where T2 is the load held by the restraining for T1, θ is the total angle subtended by the contact region of the rope, and μ is the coefficient of friction. Notably, the Capstan equation acts as a “force multiplier”, with the ratio between T2 and T1 being fixed for a given position on the verge of sliding. The exponential nature of this relationship is such that theoretically, for a coefficient of friction of 0.7, approximately that of steel on steel, a 1 kg restraining force would be capable of holding over 3.5 million tonnes with only 5 full turns.

In our case, the Capstan equation can be expressed as an overall force on the implant during insertion, FImplant(θ), being related to the angular insertion along the ST wall, θ, according to:

where Ftip is the tip force of the electrode, μ′ is the exponential coefficient that is linearly correlated to the coefficient of friction but includes other factors, including surface roughness and the spiral nature of the ST. Note that θ, in this case, is related to the angle relative to the initial contact point of the CI with the ST lateral wall rather than to the round window, measured in degrees.

When fitting the exponential growth of the insertion force exhibited on the implant with respect to insertion angle, Ftip was fixed, as the tip force during initial contact between the CI and ST wall was observed to be very similar for all insertions within each experiment.

2.7. Statistical Analysis

MATLAB (Mathworks) ANOVA 1 with Multcompare function was used to study the statistical significance of exponential coefficients between the measurements. Data were found significant if p < 0.05. Each condition was replicated n = 5 times for two separate, but identical, Cochlear Slim straight electrodes for a total of 10 experimental repeats for each ST model.

3. Results

3.1. Insertion Setup with Accurate Scala Tympani Model

A workflow for creating the 3D printable CAD models of the ST was generated (Figure 1A), which included the characterisation of the micro-CT segmented cochlea and the manipulation of the ST shape before generating an STL file suitable for printing. The 3D-printed ST model and cochlear implant were secured to a six-axis and one-axis force sensor, respectively, to monitor the forces through the insertion (Figure 1B).

Using digital light processing (DLP) 3D printing, it was possible to produce highly accurate 3D models of the scala tympani cavity (Figure 2). Furthermore, through the addition of an acrylic coating after the standard post-processing on the inside and outside surfaces of the model, it was possible to significantly improve the transparency of the models, as seen in Figure 2A. The accuracy of these 3D prints was validated using a nominal–actual analysis to quantify the surface deviation of the 3D-printed ST with the original STL CAD file. This determined that 90% of the surface was within 32.1 µm of the original file, with the highest deviation occurring at the top surface of the basal and apical ends of the ST (Figure 2B). The localised deviation at the top surface of the ST is likely due to the printing of a free-standing surface without support structures. However, as the CI will not be in contact with these regions, they do not influence the CI insertion.

3.2. Influence of Overall Size on Insertion Force

Although some studies have found some relation between the overall size of the cochlea and the CI insertion force [46], as well as residual hearing preservation [60], a systematic study into the force dependence on size has not been previously conducted.

This study measured the forces exerted on both the implant and the cochlea. A six-axis force sensor provided the reactive force of the implant insertion in the x, y, and z axes (as depicted in Figure 1) which correspond to the forces in the direction of the implant insertion and perpendicular on the horizontal and vertical axes, respectively, as well as the torque around these axes. The overall force on the implant shows good agreement with the reaction force measured on the implant (R2 = 0.999), which acts as a good cross-validation of the two independent sensors (Figure S3). As expected, the overall force on the cochlea is dominated by the force in the direction of the CI insertion (along the x-axis), and the force along the perpendicular directions is approximately 10% of the magnitude of that primary force; see Figure S4.

As seen in Figure 3, the insertion force on the implant increased exponentially with the depth of the insertion. Additionally, the increase in this force was highly dependent on the size of the model, where a 10% increase or decrease in the overall volume (respectively, for the “large” and “small” models) of the model significantly impacts the insertion force. However, when normalising these profiles to the angular insertion depth rather than the length of the electrode inserted, the profiles overlap. This is as predicted by the Capstan model (described in Section 2.6) and is based on the perhaps unintuitive fact that the friction force is independent from the contact area between sliding objects and depends only on the total normal force and the coefficient of friction. For instance, in a “large” model, a longer length of the CI is in contact with the cochlear wall for a given angle when compared to a “small” model, but this just distributes the same overall normal force on a larger area. However, this suggests that there would be higher local stresses in a smaller cochlea due to the same overall force being distributed along a smaller contact area.

It should be noted that the “small” model was inserted only to a 17 mm insertion distance to preserve the structural integrity of the implant as a deeper insertion might damage the implant and change the forthcoming measurements.

The tip force (Ftip) was determined as the force to bend the CI tip during the initial contact between the CI and the cochlear wall, at 100° depth relative to the round window. This remained consistent (at 3.00 ± 0.17 mN) between the different conditions and was fixed in fitting the Capstan model (Equation (3)) to the force exerted on the implant. The fitting of the force profile to the exponential Capstan model then determined the exponential coefficient μ’ (see Table S1 for the R2 error of the fitting and Figure S10 for an example of the fitting). The exponential coefficients were not significantly different between the samples, suggesting that the insertion force is related to the angle of the CI insertion rather than the overall length of the CI in contact with the ST wall.

As the overall size influences many aspects of the cochlear geometry, as depicted in Table 1, a systematic variation in the different aspects of the cochlear geometry and their effect on the cochlear implant insertion force was conducted. These three main factors included (1) the vertical trajectory of the ST, (2) the horizontal trajectory of the ST (i.e., curvature), and (3) the cross-sectional area of the ST.

3.3. Influence of Scala Tympani Vertical Trajectory on Insertion Forces

Firstly, the manipulation of the ST vertical trajectory was conducted wherein the centreline of the ST cross-sections was unaltered except for their vertical position, as depicted in Figure 4A. This included producing a “flat” model where the centreline of all the cross-sections lay along the same x-y plane. The non-planar models introduced a sinusoidal variation in the vertical trajectory in the first 270°, with conditions NP1 and NP2 having a consistent amplitude of 0.2 mm but a period of 270° and 135°, respectively. This replicates the “rollercoaster” vertical trajectories observed in several studies [51,61,62]. The overall vertical trajectory (or rising spiral) of the ST centreline did not have a significant effect on the insertion force when considering the flat model versus the original ascending model. However, an increased non-planarity (condition NP2) led to a small but statistically significant decrease (p = 0.024 relative to the “original” model) in the insertion force on the implant and along the z-axis of the model, whereas the decreased frequency of the non-planarity led to a slightly higher force along the z-axis.

3.4. Influence of ST Curvature on Insertion Forces

The curvature of the ST models was changed by adjusting the parameter influencing the curvature of the inner spiral of the cochlea (θ2), as seen in Figure 5A. This was conducted on flat models; therefore, only the curvature was influencing the force profiles. As the curvature affected the angular insertion of the implant, this was a significant factor in determining the total insertion force for a given length of the inserted CI. Once normalised for the angular insertion depth, the IF profiles of all three (“flat”, “loose” spiral, and “tighter” spiral models) models overlapped and there was no statistically significant difference in their exponential coefficients (p > 0.05; see Table S1). Similar to the “small” model, the “tighter” spiral model was also inserted to only a 17 mm insertion distance to preserve the structural integrity of the CI.

3.5. Influence of ST Cross-Sectional Area on Insertion Forces

Finally, the effect of the ST cross-sectional area was investigated (see Figure 6). Typically, there is a decrease in the cross-sectional area with an angle as the ST tapers from the base to the apex (see Figure S7). However, in this experiment, this was compared to a uniform cross-section where the cross-section of 1 mm depth from the round window was used along the whole spiral. Similar to the curvature experiment, the vertical trajectory was controlled for in this experiment by comparing to a “flat” model. When comparing the uniform cross-section model (“flat—uniform CS”) to the tapered cross-section model (“flat”), the insertion force is seemingly much smaller for a given insertion distance. However, when normalising for the angular insertion depth, the forces overlap as with other alterations of the ST geometry. When comparing the average exponential coefficient in the growth of the force with respect to the angle, there is no statistically significant difference (p > 0.05; see Table S1) between these models.

4. Discussion

4.1. Comparison with Previous Work

This study represents a thorough analysis of the different contributions of the selected geometrical features, namely the basal planarity, vertical trajectory, overall scaling, curvature, and cross-section area of the ST on the CI insertion. We have demonstrated a method for systematically manipulating the different features of the ST shape by taking the cross-sections of a single ST segmentation, changing their position, and reconstructing them into a 3D mesh. Although others have used a cross-section analysis to characterise the ST shape [63], none have reconstructed these cross-sections into a 3D structure to investigate their effect on physical properties.

As far as the authors are aware, the shape manipulation algorithm developed for this study is the first implementation of a generalised lofting function in MATLAB for arbitrary cross-section shapes. This algorithm performed more reliably for this task than the lofting functions in established 3D design software, such as Autodesk Fusion 360. Furthermore, using a nominal–actual analysis, it was determined that the reconstruction was highly accurate to the shape of the original CAD model of the ST (90% of the surface with < 7.24µm deviation), as seen in Figure S2. At the apex of the cochlea, some meshing errors could occur due to the tight curvature of the cochlea, although this region was not of interest for the CI insertions and was not included in the manipulated ST 3D prints. Note that in the “flat” models, the ST was cut off at the point where one turn of the cochlea would intersect another due to being on the same plane but would always be beyond the level of the full CI insertion.

Furthermore, this study demonstrates the fabrication of directly 3D-printed models with a transparent finish and validated accuracy (90% of the surface within <32 μm deviation; see Figure 2). In contrast, the previous studies have either employed scaling ratios of the ST to accommodate for mismatches in their 3D-printed models [45,46,47] or used direct casting, which results in models that combine all three scalae and which does not allow for flexibility in manipulating its shape [64].

4.2. Impact of ST Shape on Insertion Forces

Overall, it can be seen that the insertion force on the CI is determined by the angular insertion depth and is rather resilient to other factors. Although the overall volume affected several parameters, as detailed in Table 1, the changes in the force were accommodated for by controlling for the angular insertion depth rather than considering the length of the implant inserted. All the changes in the ST geometry did not cause a statistically significant difference in the force relative to the angle; this provides strong evidence for the Capstan model. The only exception is when a large non-planarity is added to the base where the implant trajectory may be altered to a point that it does not follow the Capstan model, as discussed below. As the force increases exponentially with an angular insertion depth, it is very sensitive to changes in the angle, which were confirmed manually using the videos of each insertion.

4.2.1. Effect of ST Vertical Trajectory When controlling for the vertical trajectory of the ST, the ascending portion of the cochlea did not affect the force when comparing the “flat” and “original” models, both in terms of the overall force and the force in the vertical direction, as seen in Figure 4.

Introducing a high non-planarity to the basal turn (as with NP2) led to a small statistically significant decrease in the force on the implant. This somewhat counterintuitive result may be due to the CI having less contact with the lateral wall as it travels through the centre of the cochlear lumen. NP2 also had a lower overall z-force. However, this may be due to the implant being in contact with both the top and bottom walls of the ST and the sum of the vertical forces cancelling each other out. The CI diameter relative to the ST cross-section is demonstrated in Figure S9. Although statistically significant, this rather extreme case of non-planarity only results in a small difference in the insertion force which will not likely be clinically significant.

A typical amplitude of the non-planarity and fixed angle of the insertion was used in this study, as the non-planarity can be highly dependent on the coordinate system used to define the vertical trajectory of the cochlea [51].

4.2.2. Effect of Curvature The effect of the ST curvature on the insertion force was accommodated for by controlling for the angular insertion depth. In this study, only θ2, which varied the curvature of the inner spiral, was altered and the basal turn of the ST remained unaffected. Therefore, the insertion forces were similar in this region. As with the small model, a full insertion was not possible with the tight ST models as there was a significant risk of kinking the CI at deeper insertion depths.

4.2.3. Effect of Cross-Sectional Area The cross-sectional area of the ST was determined to have a minimal effect on the CI insertion force. The “original” ST varies from 2.6 to 1.0 mm2 across the extent of the CI insertion, whereas the “uniform cross-sectional” model was fixed at 2.5 mm2, as seen in Figure S7. It is worth noting that the “uniform cross-section” ST represents a rather extreme difference in the cross-sectional area between the models, which is beyond anatomical variation. The alteration in the cross-sectional area in the volume-scaled models (as illustrated in Figure S7), however, does not demonstrate a significant influence on the force with respect to the angular insertion depth.

As predicted by the Capstan model, the insertion force is determined by the angular insertion depth of the CI into the ST. Therefore, this finding reinforces the fact that it is the CI contact with the wall that determines the force rather than the overall space within the ST. At the depths inserted in this study, the cross-sectional area and the height of the lateral wall are significantly larger than the CI, as illustrated in Figures S7 and S8, respectively. For instance, at a 20 mm insertion, the height of the lateral wall in the original model varies from 1.6 to 0.9 mm (Figure S8), whereas the CI diameter varies from 0.6 to 0.3 mm from the base to the apex [60]. The size of the CI within the ST is illustrated more directly in Figure S9 within a straightened ST. However, when the CI diameter would match the height of the ST, the insertion force and mechanical trauma are expected to increase significantly as the CI would be constrained by the top and bottom surfaces of the ST, deviating from the Capstan model.

4.3. Comparison with Surgical Approach

It should be noted that these experiments consisted of an insertion through a scala tympani with a fully open base rather than through a simulated round window or cochleostomy approach. Although not exactly the clinical approach, the round window anatomy can be very variable [65] and alters the angle of approach for the insertion. Therefore, by having a consistent insertion trajectory with an open base, it was possible to determine the influence of the ST size and shape on the insertion forces. This allowed the systematic determination of the contributors to the insertion force due to the ST shape. Future studies will focus on the angle approach of the CI insertion and the influence of many different segmentations of the cochlea and surgical approach rather than manipulating a single cochlea shape.

The amplitude range of the insertion forces measured in this study (~50–200 mN) were within the range measured in the cadaveric specimen listed in the literature [66,67,68,69,70]. However, these forces strongly depend on the angular insertion depth, which is often not reported; the treatment of the cadaveric specimen (e.g., a reduction in the endosteum—the soft tissue covering the inside of the ST lumen); and other parameters that might affect the coefficient of friction. Hence, it is difficult to compare the data with the published studies. Furthermore, no studies found used a Cochlear Slim Straight electrode as used in this study, which makes comparisons to the existing literature with different implants difficult. This supports the need for reporting insertion forces as a function of the angular insertion to ensure a fair comparison between studies.

4.4. Impact of Vertical Forces

The vertical forces exerted on the ST are important as they present a risk of damaging the basilar membrane and organ of Corti structures that are crucial in providing residual acoustic hearing. Therefore, measuring the effect of the force on the vertical z-axis could help determine the conditions of the increased risk of the basilar membrane damage and CI translocation between the scala, which can occur in up to 20% of lateral wall electrode implantations [71]. In our results, the spatial frequency of the variation in the non-planarity of the basal turn seemed to have differing effects on the insertion force. However, there was a significant variation in the force measured, as the range of the forces was reaching the limit of our sensor (a sensitivity of 1.5 mN for the z-axis). The vertical forces measured within this study are significantly lower (<5 mN) than those measured to rupture the partition, ranging from 42 to 122 mN [72], which included the bony osseous spiral lamina as well as the basilar membrane. However, the scalar translocation will largely depend on the localised stress applied to the cochlear partition, with the basilar membrane being significantly less stiff than the bony osseous spiral lamina and, therefore, being damaged at much lower forces.

4.5. Stress Relaxation of CI

Another factor that is related to the overall insertion forces is the elastic stress held in the CI, which can cause the CI to extrude due to stress relaxation. Due to the stepper motor-assisted insertion, a force relaxation could be observed when the CI was held in position at maximum insertion. The ratio of the force at a fixed distance to the maximum force was consistent across the conditions with a median value of 0.69, except for the “small” and “tight” models where a full insertion could not be achieved and therefore not fully comparable, and the results were more valid (see Figure S10). This is likely related to the inherent elasticity of the implant. This elasticity may vary across implant brands; hence, the same CI brand was used throughout this study to be consistent and eliminate the variability due to the implant mechanical properties. However, it was shown that there was no significant variability in the insertion force on the same model with repeated insertion (see Figure S9).

4.6. Consequences of Capstan Model

The basic Capstan equation has been used with significant success to understand the observed exponential behaviour of the cochlea insertion forces [59]. There are two particularly unintuitive observations, however, that have not been made.

The first consideration is that, for portions of the implant in contact with the ST wall, the bending stiffness does not affect the forces in that region. To see this, remember that

where M is the bending moment, E is the elastic modulus, I is the second moment of the area, and κ is the local curvature. It can be seen from the equilibrium conditions—Equation (S1)—that this term has no effect on the system solution as dM is zero for the locations of constant curvature. This counterintuitive fact was first noticed by Stuart et al. [73] for the classical Capstan problem and suggests that cochlea implant stiffness is not necessarily a limiting factor in the design. This comes with two major caveats, however.

Firstly, the bending moment does have a significant effect on the non-contact regions, such as at the base of the implant, and a stiffer implant may require a lateral constraint within a supportive stiff sheath.

Secondly, the bending moment does change which parts of the implant may be in contact. If the local tension/shear forces are not sufficient to hold the implant against the ST lateral wall, the forces will change.

Taken together, this suggests that the optimum implant stiffness profile is for a “pyramid of stiffness”, chosen to always be less than required to pull the implant away from the wall but great enough to maximise the steering control.

Nevertheless, the second consideration is just as significant: the angular insertion depth, coefficient of friction, and tip forces are the only significant factors affecting the implant forces. Features such as the ST size, flatness, and profile are only minor in their impact. Although these considerations would need to be directly investigated in a separate study with implants of varying stiffness, the fact that the ST curvature does not affect the insertion force suggests that the bending of the implant does not contribute significantly to the overall force. Particularly surprising is that the spiral geometry makes no difference at all in the model relative to the classical circular geometry used for a Capstan model. This suggests that the majority of the refinement effort in implant design should target the tip profiles and developing materials with low coefficients of friction.

4.7. Limitations of This Study

Although this study represents one of the more detailed studies of cochlear implant forces to date, there are still limitations to this setup. The conclusions of the Capstan model and overall forces on the cochlea do not let us investigate the local stresses on the cochlea and the identification of the local “hotspots” which could lead to localised insertion trauma. Therefore, there is a need for high-density force sensors that could be placed along the cochlea that could measure these localised forces. For instance, the buckling of the implant may push on the top and bottom surface of the ST and, therefore, cancel out forces measured with this setup.

5. Conclusions

In conclusion, after studying the parameters determining the CI insertion force, it is clear that accommodating for angular insertion depths accounts for most of the variation between the different ST geometries. Although the spatial frequency in the vertical trajectory of the basal turn may have a statistically significant effect on the insertion force, its small influence is unlikely to have a significant effect in surgery. These observations are summarised in Table 2.

This is promising in the pre-surgical planning of a CI insertion as even a basic analysis of the cochlear shape could feed into a predictive model of the insertion force and inform the decision of which CI and approach to use for a particular patient. Common measures such as the cochlear duct length and number of turns could be used to determine this angular insertion depth-to-distance relationship. Furthermore, to reduce insertion trauma, surgeons should consider implanting a CI to the same angular insertion depth rather than to a certain length of the implant. However, this comes with a trade-off between reducing trauma and achieving optimal CI electrode positioning to achieve effective neural stimulation. Additionally, the considerations within this paper relate to conventional straight electrodes that are positioned along the lateral wall rather than pre-curved electrodes which rely on the pre-tension to achieve a perimodiolar positioning.

By appreciating the consequences of the Capstan model that the tip force and coefficient of friction are the major determinants of the insertion force for a given angular insertion depth, it is clear that developing new CI tip designs and surface coatings to reduce friction will likely be most effective in reducing insertion trauma. Furthermore, the Capstan model shows that an increased stiffness of the implants may not increase the insertion forces so long as they do not affect the implant following the lateral wall.

By combining these insights to further understand the intracochlear forces during insertion, it may be possible to improve the CI insertion to provide an optimal electrical stimulation while minimising the trauma. This could improve CI users’ outcomes by retaining more of their residual hearing that provides acoustic cues to improve their hearing. Additionally, by reducing the risks of the CI insertion, it could be possible to widen the eligibility of CIs to include those with less severe hearing loss to provide these benefits to a much wider patient population.

A modular 3D printed microfluidic system: a potential solution for continuous cell harvesting in large-scale bioprocessing

January 16, 2026June 6, 2022 by CadWorks3DAdmin

A modular 3D printed microfluidic system: a potential solution for continuous cell harvesting in large-scale bioprocessing

Lin Ding, Sajad Razavi Bazaz, Mahsa Asadniaye Fardjahromi, Flyn McKinnirey, Brian Saputro, Balarka Banerjee, Graham Vesey & Majid Ebrahimi Warkiani

Microfluidic devices have shown promising applications in the bioprocessing industry. However, the lack of modularity and high cost of testing and error limit their implementation in the industry. Advances in 3D printing technologies have facilitated the conversion of microfluidic devices from research output to applicable industrial systems. Here, for the first time, we presented a 3D printed modular microfluidic system consisting of two micromixers, one spiral microfluidic separator, and one microfluidic concentrator. We showed that this system can detach and separate mesenchymal stem cells (MSCs) from microcarriers (MCs) in a short time while maintaining the cell’s viability and functionality. The system can be multiplexed and scaled up to process large volumes of the industry. Importantly, this system is a closed system with no human intervention and is promising for current good manufacturing practices.

We kindly thank the researchers at the University of Technology Sydney for this collaboration, and for sharing the results obtained with their system.

Introduction

Microfluidics, a science of precise fluid handling within the network of channels, has shown great promise in manipulating cells and particles. Microfluidics has attracted significant attention in biology and medical research due to their unique features including low price, high throughput, high customisability, and energy-efficiently compared to other technologies (Wang and Dandy 2017; Figeys and Pinto 2000). For example, micromixers have been used in chemicals synthesis and microparticle coating (Vasilescu et al. 2020). Multiple microfluidic devices, especially spiral microfluidic channels, have been demonstrated to separate or concentrate cells based on particle sizes (Xiang et al. 2019; Nivedita et al. 2017). To date, microfluidic devices are widely used in laboratories but one of the major limitations for applying microfluidics in the industry is its customisability (Yi-Qiang et al. 2018). For instance, in the stem cell bioprocessing industry, each company has its own manufacturing protocol. The lack of standard procedure is one of the reasons for the low yield of cell products and the inconsistent clinical outcome of stem cell therapy (Jossen et al. 2018; Schnitzler et al. 2016). Although microfluidic devices have been applied in the stem cell bioprocessing industry as cell separator and concentrator in a labour-free, low-cost, and high-throughput manner (Moloudi et al. 2018, 2019), the lack of modularity and integrity makes them hard to be applied in the bioprocessing industry. Microfluidic devices are normally made from polydimethylsiloxane (PDMS) by soft lithography. Compiling these single microfluidic devices together to increase the throughput requires multiple external tubing and diverters to meet the industrial need, and testing and modifying them to meet the demand requires a huge amount of time and effort. 3D printing technology can be a good solution for this inadequacy. In recent years, the advances in 3D printing technologies have made it increasingly appealing for producing microfluidic devices (Bhattacharjee et al. 2016). The resolution of 3D printing allows direct construction of microfluidic channels with micrometre-level features, and the study and treatment of 3D printed resin enable the production of soft-lithography mould in a few hours (Vasilescu et al. 2020; Razavi Bazaz et al. 2019). Although 3D printing technologies are not the solution for large-scale manufacturing of microfluidic devices, their potential to modify changes and fabricate microfluidic devices in a few hours is unique and valuable for the industry. This feature hugely decreases the cost and time needed for rapid prototyping and building integrated microfluidic systems.

In the stem cell industry, microcarriers (MC)-based culture systems are a promising candidate for maximising cell manufacturing on a large scale. MCs facilitate massive cell expansion at a lower cost and allow control of cell culture parameters in a homogenous condition to produce consistent quality cell products at a large scale (Fardjahromi et al. 2020; Chen et al. 2020). Despite the enormous advantages of microcarrier-based technologies in maximising cell production, harvesting cells from MCs still faces challenges with high product quality and yield (Chen et al. 2013). The common method for harvesting is detaching cells with digestive enzymes and separating them from MCs using membrane-based filtration or centrifugation (Chilima et al. 2018; Tavassoli et al. 2018). Membrane-based filtration separates the cells with a physical porous filter. Clogging filters is the major limitation of this method (Schnitzler et al. 2016; Zydney 2016). In addition, membrane fouling has been shown to cause cell death, cell fate changes, and reduce the therapeutic potential of harvested cells (Chilima et al. 2018; Zydney 2016; Rodrigues et al. 2018). Centrifugation-based methods, particularly continuous flow centrifugation, are another alternative method for separating cells from MCs (Schnitzler et al. 2016). The advantage of this method is that it washes cells during separation, but the centrifugation process is time-consuming, potentially causing cell damage (Joseph et al. 2016). In addition, the continuous washing and centrifuging process cost more reagents and disposables (Serra et al. 2018). Hence, a continuous, clogging-free, highly efficient, and low-cost harvesting method is severely lacking in this area.

Herein, in this paper we report an integrated 3D printed modular microfluidic system containing two micromixers, one spiral separator, and one zig-zag concentrator. We used this system to detach and separate mesenchymal stem cells (MSCs) from MCs and eventually concentrate them in a smaller volume for downstream processing. At first, each module was characterised using cells and microbeads in different volume fractions and flow rates to obtain the optimum condition for the MSC harvesting. Then, the viability, proliferation, and therapeutic properties of MSCs harvested with our proposed integrated system were compared with the manual method, i.e., Millipore filtration. The results indicate that the developed microfluidic device is a promising candidate for automated MSCs harvesting and concentrating from MCs. In the end, we demonstrated that the system could be multiplexed to process samples with higher throughput.

Materials and methods

Device fabrications

Figure 1A depicts the general concept of unidirectional imaging. To create a unidirectional imager using reciprocal structured materials that are linear and isotropic, we optimized the structure of phase-only diffractive layers (i.e., L1, L2, …, L5), as illustrated in Fig. 1 (B and C). In our design, all the diffractive layers share the same number of diffractive phase features (200 by 200), where each dielectric feature has a lateral size of ~λ/2 and a trainable/learnable thickness providing a phase modulation range of 0 to 2π. The diffractive layers are connected to each other and the input/output FOVs through free space (air), resulting in a compact system with a total length of 80λ (see Fig. 2A). The thickness profiles of these diffractive layers were iteratively updated in a data-driven fashion using 55,000 distinct images of the MNIST handwritten digits (see Materials and Methods). A custom loss function is used to simultaneously achieve the following three objectives: (i) minimize the structural differences between the forward output images (A → B) and the ground truth images based on the normalized mean square error (MSE), (ii) maximize the output diffraction efficiency (overall transmission) in the forward path, A → B, and (iii) minimize the output diffraction efficiency in the backward path, B → A. More information about the architecture of the diffractive unidirectional imager, loss functions, and other training-related implementation details can be found in Materials and Methods. After the completion of the training, the phase modulation coefficients of the resulting diffractive layers are shown in Fig. 2C. Upon closer inspection, it can be found that the phase patterns of these diffractive layers have stronger modulation in their central regions, while the edge regions appear relatively smooth, with weaker phase modulation. This behavior can be attributed to the size difference between the smaller input/output FOVs and the relatively larger diffractive layers, which causes the edge regions of the diffractive layers to receive weaker waves from the input, as a result of which their optimization remains suboptimal.For the fabrication of microfluidic devices using additive manufacturing, different techniques exist. Fused Deposition Modelling (FDM), Stereolithography (SLA), Digital Light Processing (DLP), two-photon polymerisation (2PP), Multijet, and wax printing are all capable of fabricating microfluidic devices. For the creation of complex microfluidic devices, however, DLP and wax printing methods show more promise in this regard. The fabrication process of these two methods is illustrated in Additional file 1: Fig. S1. The wax 3D printing method is a multi-step process, and the printed microfluidics are inherently fragile and prone to fault and error. As an alternative, DLP method has been selected for the current study because of its accuracy, precision, fast turn-around time, and the ability to fabricate robust complex microfluidic channels (Chai et al. 2021; Ding et al. 2022). Design selection consideration is introduced in detail in Additional file 1: Section S1.

The micromixers were designed in Solidworks 2018 × 64 edition (SolidWorks Corporation, USA) and fabricated with a high-resolution DLP resin printer (MiiCraft II, Hsinchu, Taiwan), with the layer thickness of 50 µm. BV-007 resin was used, which is an acrylate-based resin containing 80–95% acrylate components and 10–15% photoinitiator and additives (Razavi Bazaz et al. 2020a). After printing, the micromixers were carefully removed from the build plate, washed with isopropyl alcohol, and dried by air nozzle. This process was repeated three times to prevent uncured resin from clogging the channels. Then, the micromixers were cured by 450 nm UV light in a UV-curing chamber. The design and dimension of the micromixer are shown in Additional file 1: Fig. S2.

The spiral chip and zig-zag channel were produced as previously described (Razavi Bazaz et al. 2020a; Ding et al. 2022). Briefly, the devices were designed by SolidWorks and printed by the MiiCraft II 3D printer with a 10-µm layer thickness. Then the devices were rinsed with IPA and dried with an air nozzle three times. These devices were further post-processed by UV light in a UV-curing chamber and then bound to a PMMA sheet with a double-sided tape (ARclear®, Adhesive Research). Next, Tygon tubes (Tygon tubing, inner diameter: 0.50″, outer diameter: 0.90″) were used as connections of inlets and outlets to connect each part. Finally, the printed parts were then connected in series, as shown in Fig. 1.

Schematic representation of the modular microfluidic system. The whole system was built by 3D printing technology. The system comprises two micromixers, a micro separator, and a zig-zag channel connected vertically to detach cells from MCs, separate cells from MCs, and dewater the harvested cells. The adherent cells on MCs were detached from MCs through enzymatic treatment and gentle mechanical force inside of mixer channels. Cells and MCs were then collected separately from spiral outlets and concentrated using the zig-zag concentrator unit. The dimension of the micromixer is shown in Additional file 1: Fig. S1

Characterisation of micromixer module

The performance of the micromixer has been evaluated using numerical (described in detail in Additional file 1: Sections S2, and S3 explained the detail of mixing index calculation) and experimental results. To verify the mixing efficiency of the mixers, food dye (1 mL in 49 mL DI water) and pure DI water were loaded in 50-mL syringes and injected into the mixer with syringe pumps at different flow rates. The syringes were connected to the Tygon tubes with precision syringe tips (0. 0. 50″ Long Tip, Adhesive Dispensing Ltd, UK). The pictures of the mixed liquid before and after going through the mixing units were taken by Olympus IX73 microscope (Olympus, Japan). The pictures were then analysed, and the degree of experimental mixing efficiency in these channels was compared with numerical results obtained using COMSOL Multiphysics (Razavi Bazaz et al. 2020b) (refer to Additional file 1).

Characterisation of the microseparator module

Star-Plus MCs (Pall, SoloHill) were used to characterise the microseparator module. A spiral-shape microchannel was used for this purpose since it is capable of high-throughput and continuous sample processing without clogging issues (Moloudi et al. 2018). MCs were diluted in MACS buffer (Miltenyi Biotec, Australia) to acquire different volume fractions (0.1, 0.25 0.5, 0.75, 1% v/v%). The videos of particle movement were recorded by Phantom High-Speed camera (Phantom Academy, USA). The first 2000 frames of the video were stacked by ImageJ to observe the trajectory of the movement of the beads.

Characterisation of the microconcentrator module

To concentrate the collected MSCs, a zig-zag microfluidic channel was designed and tested. Based on the spiral outlet dimensions, the input flow rates of the zig-zag channel were calculated (~ 1.6–1.8 mL/min). As such, 15 µm microbeads (PMMA (polymethyl methacrylate) latex beads, Magsphere, USA) were used to characterise different zig-zag channels with different dimensions. To this end, 50 µL microbeads were added into 10 mL MACS buffer and loaded into a 10-mL BD plastic syringe (BD, Australia). The microbeads were pumped through the device, and high-speed camera videos were recorded and evaluated.

Microfluidic-based cell harvesting system setup

The modular 3D printed microfluidic system was set up with two micromixers, a spiral microfluidic device, and a zig-zag concentrator connecting in series with Tygon tubes. Cell harvesting was conducted in a biosafety cabinet to prevent any contamination. The upper mixer has two inlets, one was connected to the bioreactor through a peristaltic pump (Shenchen, China), and the other one was connected to a syringe pump (Fusion Touch, Chemyx Inc) for the TrypLE injection. Before cell harvesting, the whole setup was sterilised by 70% ethanol and UV irradiation. The same number of cell-attached MCs was harvested by the conventional membrane filtration method as a control. Briefly, the MCs were allowed to settle for 10 min, and then the culture media was carefully removed by a serological pipette. 40 mL of TrypLE was added to the bioreactor and incubated for 20 min. The microcarrier-cell suspension was gently pipetted before filtration. Lastly, the suspension was filtered by Steriflip Nylon Net filters (Millipore Steriflip filtration 100 μm, Merck, Australia), and the filtrated cells were collected. The recovery rate of cells and microcarriers were calculated by: R=Ntargetoutlet/(Ntargetoutlet+Noutheroutlet) , N is the number of particles counted with haemocytometer. Counting was repeated 3 times.

Cells culture and cells characterisation

Cells culture before harvesting and cells characterisation after harvesting are described in detail in Additional file 1: Section S4 and S5.

Statistical analysis

The statistical significance in the data was calculated by Student’s t-test using Graph Pad Prism7 software. Significance levels were shown as *p < 0.05.

Results

Working principle of micromixer module

Two mixing strategies were applied in the proposed micromixer: Dean force induced by the helical 3D channel structure and the mismatch of flow rates induced by twisted helical groove structures following the 3D spiral. The first strategy creates fluid velocity mismatching in the channel’s inner side and outer side by having the curved channel, leading to the formation of two opposing vortexes in the channel and thus reducing the diffusion distance of the two fluids (Chai et al. 2021; Cai et al. 2017). For the second strategy, the twisted helical groove structure contributes to fluid mixing by creating a slow fluid flow zone and therefore inducing another mismatching of fluid velocity. This fluid mismatching carries the fluid from one side towards the other side of the channel, increasing the chance of fluids contact (Vasilescu et al. 2020; Chai et al. 2021); consequently, the increased contact of different fluids enhances the molecular diffusion. As previously reported, the groove designs in the channel would not introduce strong secondary flow (Tsui et al. 2008). Additional file 1: Fig. S3 shows the simulation results of the micromixer. Increasing the inlet fluid flow ratio leads to increased pressure in the system, which is negligible for smaller flow rate ratios and shows the system can be powered by normal lab-scale pumps. The cross-section 1 (CS1) across different flow rates in Additional file 1: Fig S3 shows that the chaotic advection phenomena dominate over diffusion when the flow rate increases. However, higher flow rate ratios do not necessitate a higher mixing index since fluids take time to mix and diffuse (Additional file 1: Fig. S3). Interestingly, velocity distribution for lower flow rates shows a symmetric profile along the channel length (Additional file 1: Fig. S3C), while it becomes asymmetric for higher flow rate ratios. This phenomenon might also contribute to the reduction of the mixing index at higher flow rates.

The experimental results of the mixing index with pure water and food dye for various flow rate ratios are illustrated in Fig. 2A. The mixing efficiency of the device was higher than 95% (Additional file 1: Fig. S5) at the flow rate ratio of 1 mL/min:2 mL/min. Hence, the total flow rate of 3 mL/min was chosen as an optimised flow rate for cell harvesting. Based on the method described in Additional file 1: Section S1, the experimental mixing index is 82.7%. The discrepancy between simulation and experimental results can be attributed to the difficulties of imaging 3D printed channels with microscopy and the addition of extra noise in the picture due to the unsmooth surface of the micromixer (Rouhi et al. 2021). The micromixers have no splitting, obstacles, or sharp turning, which are appropriate for processing cells without damaging them.

Characterisation of the microfluidic harvesting system using food dye, MCs, and fluorescent microparticles. A The micromixer reached 95% mixing efficiency with a 1:2 fluid flow mixing ratio. B The spiral microfluidic device can be operated at a flow rate of 3 mL/min with 0.75% v/v% microcarrier concentration. C The micromixers and spiral apply gentle forces to the microcarriers, and no breakage of microcarriers happened even when the flow rate was 6 times higher than the operation flow rate. D The zig-zag channel focuses 15 um beads from 1.6 to 2 mL/min with a 100% recovery rate

Working principle of the microseparator module

The focusing position of microparticles inside a curved microfluidic channel is affected by two forces, inertial lift force (FL ) and Dean drag force (FD) (Amini et al. 2014):

FL is affected by the density of fluid ρ , the hydraulic diameter Dh (which can be calculated by 4A/P , A= channel cross-section and P= perimeter of the channel), the maximum fluid velocity Umax which is approximated as 2×Uf (Uf is the average velocity), CL which is a constant named dimensionless lift coefficient number and is dependent on the channel Reynolds number (Re=ρUfDh/μ,μ is the viscosity of the liquid) and the diameter of particles a . FL consists of two forces: shear-gradient and wall-induced lift force. Shear gradient lift force pushes the particles towards the wall due to the velocity difference between the middle area and the side area of the channel. When the particles move close to the wall, the wall lift force pushes the particles away. The balancing point of inertial equilibrium position contributed to the lift force is where these two forces balance each other (Razavi Bazaz et al. 2020c).

In a curved channel, the channel’s curvature causes the inner wall (IW) fluid to flow faster than the outer wall (OW) due to the shorter distance travelled. This transverse fluid flow creates another force that affects the focusing position of the particles, which is the Dean drag force (FD ). FD is defined in Eq. (2), where De=ReDh/2R−−−−−−√ is the Dean number, and R is the radius of curvature; it describes the strength of FD . According to Eqs. (1) and (2), the forces applied to the particles are proportional to the particle size (FL∝a4,FD∝a ). Therefore, different particle sizes have different focusing positions across the channel cross-section, and they can be collected through separate outlets (Mihandoust et al. 2020; Ozbey et al. 2019).

In a normal spiral channel, the particles inside the channel need to follow the rules of Cr>0.07 , where Cr=a/Dh to be affected by the inertial forces inside the channel. In a scaled-up microfluidic channel, the increase in Dh results in a reduction of absolute flow velocity compared with a normal microfluidic channel. Therefore, the secondary forces applied to the microparticles were weaker, and the Cr value in the scaled-up microfluidic channel was much higher than the microfluidic channels (Cr>0.17) (Moloudi et al. 2019; Carlo 2009). Another factor that affects particle focusing is channel rigidness. There is no swelling or channel inflation in rigid channels compared to traditional PDMS chips; thus, the scaled-up device should have theoretically a lower Cr . Also, larger particles are more likely to be affected by mass and gravity since they are not neutrally buoyant (Moloudi et al. 2019), adding another variable despite flow velocity; the variable sizes of particles would also increase the difficulty in the channel design. When MCs and cells pass through the channels, focusing MCs near the IW causes the MSCs to be dispersed in the channel due to the large size difference between MCs and cells (MCs size are 150–220 µm, and MSCs are 15–20 µm). However, since large particles occupy the inner channel, the particle–particle interaction can stop some of the MSCs from going out through the inner outlet (Moloudi et al. 2018). Considering all these factors, in this study, we have designed the channel with a trapezoidal cross-section and heights of 550 µm and 620 µm, and a width of 1100 µm. This spiral chip has 6 loops and a slightly slanted enlarged inlet size to prevent clogging of MCs at the beginning of the channel (Fig. 1).

Working principle of the microconcentrator module
The zig-zag channel relies on inertial, and Dean drag forces to focus the MSCs at the centre of the channel. When Reynolds number of the channel falls in the intermediate range 1 < Re < 100, the fluid flow is laminar, between Stokes and turbulent flow regimes. Therefore, inertial forces focus the randomly dispersed particles toward certain equilibrium positions after a sufficiently long channel length. As explained above, shear-gradient and wall-induced lift force are the main forces affecting the particle focusing in straight channels, and they both contribute to the overall inertial lift force FL . Straight channel relies on the difference in particle sizes to focus the particles at different positions (FL∝a4 ). In zig-zag channels, Dean force FD is introduced differently compared to the spiral microfluidic channel. The interchanging channel direction creates a mismatch of fluid flow velocity in an alternating pattern and introduces Dean force, accelerating the focusing of particles inside the channel. A zig-zag channel has three focusing modes across different flow rates. When FL<FD , the particles focus at the side of the channels. When FL>FD , the particles were focused in the middle of the channel due to due to the strong FL . When FL∼FD , particles are in the transition mode. For the aim of this study, MSCs need to satisfy the condition of FL>FD. One primary advantage of the zig-zag channel is its operating ranges of flow rates, i.e., it can focus particles at the centre over a wide range of flow rates. After careful evaluations, the zig-zag channel with a cross-section of 360 µm × 60 µm, 60° angle has been proposed to concentrate cells after the spiral microfluidic device. To avoid clogging of zig-zag channels caused by the remaining MCs in the target outlet, some obstacles were planted at the target outlet of the spiral to ensure no MCs could enter the zig-zag channel.

Pressure balance of microfluidic system
ombining multiple microfluidic devices in one system requires careful arrangement to balance the fluid flow and pressure change. An electronic circuit was used as an analogy for our system to understand better the fluid behaviour in the system (Additional file 1: Fig. S5). These microfluidic devices resemble the resistors that reduce the pressure input from the pumps, similar to the voltage drop in an electronic circuit (Oh et al. 2012). Keeping the flow rate and pressure stable according to the following equation is the key point of the successful operation of this system:

where Q is the volumetric flow rate, RH is the hydraulic resistance of the channel, μ is the viscosity, Δp is the pressure drop, and L is the channel length. In a serial circuit, Q (which is current I in the electronic circuit) remains constant in each device, thus Qspiral=Qmixer1=Qmixer2 . Qmixer1 has two inputs, one from the peristaltic pump, and one from the syringe pump. In a parallel circuit, the current of the circuit Qmixer=Qinlet1+Qinlet2 . The working flow rates of micromixers and zig-zag channels are more flexible, while the spiral microfluidic device only works under a specific flow rate. To achieve this flow rate, we change the flow rate of the two pumps according to Qspiral=Qinlet1+Qinlet2 . The outlet’s resistance of the spirals affects the focusing of the MCs in the inner outlet. Therefore, the fluid pressure of the zig-zag channel must be balanced with the pressure-damping channel connecting to the inner outlet of the spiral device. This pressure-damping channel needs to have the same hydraulic resistance RH to the zig-zag channel, which can be calculated by Eq. (4) (Oh et al. 2012):

where η is the viscosity and L is the finite length of the channel. Since Dh of the channel is fixed and RH∝8L , changing the length of the pressure-damping channel to reach R3 = R4 balances the pressure of the system and would not affect the particle focusing positions in the spiral channel (Additional file 1: Fig. S6). This system potentially eliminates the debris larger than cells through spiral channel, and removes debris smaller than the cells through the zig-zag channel.

Evaluation of different modules with fluorescent microbeads and microcarriers

The maximum capacity and optimal flow rate of the spiral microfluidic device was determined by passing a different concentration of MCs through the device across a range of flow rate. As shown in Fig. 2B and Additional file 1: Fig. S6, from 2.0 to 4.0 mL/min, the focusing position of the MCs gradually shifts to the outer outlet. Noticeably, 3.0 mL/min is the critical flow rate that runs under high throughput while still focusing the MCs at the inner outlet. MCs with a concentration higher than 1% escape from the outer outlet even at a lower flow rate. However, MCs with a concentration of 0.75% can be sufficiently removed from the inner outlet at a flow rate of 3 mL/min. At the flow rate of 3 mL/min (2 mL/min from the bioreactor, 1 mL/min from the enzyme reservoir), the fluid mixing efficiency reached 95% after the first micromixer (Additional file 1: Fig. S4). The addition of the enzyme from the syringe pump inlet of the micromixer dilutes the sample.

The microcarrier concentration used for cell culture was 1.29% v/v% (1 g in 80 mL media). Therefore, MCs’ volume and concentration for cell harvesting before entering the microfluidic gadget were set to 70 mL to reach 0.75% when the sample arrived at the spiral microfluidic chip. The volume was calculated by the following equations: target concentration (0.75%)/dilution factor in micromixer (2/3)/concentration in culture (1.29%) × volume in culture (80 mL). As such, 40 mL of TrypLE was added since there was 30 mL of media inside the bioreactor after 50 mL of supernatant was taken away. The flow rate was set at 2 mL/min from the bioreactor and 1 mL/min TrypLE from the syringe pump, so the total flow rate of 3 mL/min fluid proceeded into the spiral. To demonstrate the inertial forces in the system do not damage the MCs, we passed MCs through the two micromixers and one spiral chip setup under a 20 mL/min flow rate. The results showed that the gentle forces applied by the micromixer do not change the shape and size of the MCs (Fig. 2C). Various inertial microfluidic channel designs can be used in this application as evidenced in our previous publications (Moloudi et al. 2018). In this study, we have showcased a rigid channel in the processing of large particle through the power of 3D printed inertial microfluidics. The zig-zag channel was responsible for further concentrating the harvested cells. Since it was connected to the outer outlet of the spiral, the operation flow rate of the zig-zag channel needed to match the flow rate of the outer outlet of the spiral. The zig-zag concentrator was tested with 15 and 20 µm beads across different flow rates. The results showed that from 1.6 to 1.9 mL/min, the beads were concentrated 100% in the middle outlet (Fig. 2D). The beads were concentrated ~ 3.5 times, with ~ 70% of the volume removed, indicating good dewatering efficiency of the device.

Results

Harvesting MSCs from bioreactor using the microfluidic system

To investigate the efficiency of the microfluidic gadgets on cell detachment, the cells were stained with Hoechst before passing through the mixer. To ensure the complete detachment of cells in the micromixers, a one-inlet micromixer was added at the end to increase the interaction of cells and enzyme under the same mixing efficiency (Vasilescu et al. 2020). Figure 3A shows microcarrier-cell suspension before cell harvesting in which cells covered the whole surface of MCs. The growth of healthy MSCs on MCs commonly leads to cell–MCs aggregation (Ferrari et al. 2012) (Additional file 1: Fig S7). Therefore, to prevent the blockage of microfluidic devices, the cells–MCs suspension was incubated with enzyme for 5 min in the incubator to detach these aggregates. Figure 3B shows the MSCs were detached from MCs’ surface by enzymatic treatment and gentle mechanical force after passing through the micromixers.

Harvesting MSCs with our microfluidic system. The concentrating efficiency of the zig-zag channel is shown in Additional file 1: Fig. S9. A and B Fluorescent microscopy images of cells–MCs before and after passing through the mixer. Cell nuclides were stained with Hoechst. C Separation of cells and microcarriers through the spiral chip. Cells and MCs were separated through different channels based on their size difference. D The recovery rate of cells and MCs after passing through the spiral chip in one round. The liquid collected from the inner outlet of the spiral was collected and performed a second-round running through to further recover the cells. The two-round separation results are shown in Additional file 1: Fig. S8

The media containing detached cells and MCs from the micromixers were then passed through the spiral. Later, they were collected separately from two outlets (Fig. 3C). 94.11% of MCs were successfully removed in the first round of separation. 76.62 ± 2.1% and 17.21 ± 0.6% cells were recovered from the OW outlet in the first and second pass, respectively, and 6.16 ± 1.80% cell loss through the IW outlet at the end of the process (Fig. 3D, Additional file 1: Fig. S8). The sum of yield (sum of cells harvested from the OW outlet over the total cell harvest from all outlets) can reach ~ 94%. Adding some obstacles at the outlet leads to 100% of the microcarrier removal rate, making it ready for clinical applications. Additional file 1: Fig. S9 shows the tight focusing band of MSCs in the middle outlet and the removal of small debris in the outer outlets. The cell solutions were collected from the outer outlets, and no cell was found in the waste outlet. Cells were concentrated 4.5 times compared to the pre-filtered samples. Although the counting results showed that the recovery rate was higher than 100%, a small number of cell loss could potentially happen due to the heterogeneity, clumping of cells, or attachment to the tubing or channel walls.

MSCs viability and proliferation after microfluidic cell harvesting

Cell viability was assessed immediately after harvesting. The live and dead staining results indicate that the microfluidic device did not compromise the viability of cells (Fig. 4A). MTS (3-(4,5-dimethylthiazol-2-yl)-5-(3-carboxymethoxyphenyl)-2-(4-sulfophenyl)-2H-tetrazolium) assay illustrating the metabolic activity of cells harvested by the device is also similar to the control. In the microfluidic group, the absorbance of media at 490 nm wavelength increased over time which indicates that cells have slightly higher metabolic activity than the control group, although the difference is not significant (Fig. 4B). Cell attachment, morphology, and proliferation were evaluated by staining the post-harvesting cells using DAPI and phalloidin. The fluorescent microscopy images in Fig. 4C and D indicate cells harvested with the microfluidic device have comparatively better cell attachment (Additional file 1: Fig. S10) than the control group on the first day of culture. After 3–5 days of culture, both groups of cells were confluent in the wells, and no significant difference in the growth rate was observed. Additionally, cells maintained their spindle morphology after harvesting with the device, and the size of cells was around 13–17 µm in both groups. The number of harvested cells after 1, 3, 5 days of cell seeding was counted by ImageJ to verify the MTS results. The results confirm that the microfluidic system does not affect cell attachment and growth after harvesting (Additional file 1: Fig. S10).

Viability and proliferation of MSCs after harvesting process. A The viability of cells harvested by the microfluidic system and filtration method. Cell viability did not change significantly compared with the control group. Data are presented as mean ± SEM (****p value < 0.0001, n ≥ 3). B MTS viability/proliferation rate of harvested cells. The morphology and proliferation rate of MSCs of the two groups were also compared with DAPI/phalloidin staining via C filtration group and D microfluidic group on 1st, 3rd, and 5th day of culture. F-actin filaments were visualised via FITC labelled phalloidin (green) and nuclei with DAPI (blue)

Stem cell properties and therapeutic properties of the harvested MSCs

To confirm the stemness and multipotency of the harvested cells, the MSC surface markers were evaluated and trilineage differentiation was performed. CD90, CD73, and CD105 were stained with fluorescent antibodies (ThermoFisher, Australia) staining and counted by a flow cytometer (CytoFLEX LX, Beckman Coulter, USA). Figure 5A shows 98%, 100%, and 100% of the cells express CD90, CD73, and CD105, respectively, confirming the well-preserved MSCs identity. To assess the multipotency of cells after harvesting, cells were stained with Oil Red, Alizarin Red, and Alcian Blue staining after treating with adipogenic and osteogenic/chondrogenic induction media, respectively (Fig. 5B). Formation of bright red stain calcium deposits stained by Alizarin Red S confirmed osteoblastic phenotype of cells. Additionally, presence of red lipid droplets stained by Oil Red O verified the adipocyte phenotype, and the blue glycosaminoglycan complex staining showed the presents of chondrogenic cells. These results indicate that cells retained their differentiation potential.

MSCs characterisation after harvesting. A Expression of the MSCs surface markers CD90, CD73, and CD105 after 3 passages of indicated cells preserve their stemness after harvesting. B Multipotency assay of harvested cells using Oil red (left), Alizarin red (middle), and Alcian blue (right) showed the cells maintained their capacity to differentiate into different cell types. C The expression level of the surface therapeutic proteins of the experimental group. The changes in the expression level of HLA-G and CD54 were similar in both groups. D Comparison of the cytokine secretion profile of MSCs harvested from the microcarriers with microfluidic system and the passage 4, passage 8 planar flask cultured cells

The therapeutic effect of harvested MSCs is verified by staining the surface therapeutic proteins and analysis of the cytokines in the cultured supernatant. Figure 5C shows the changes in the expression level of the surface therapeutic proteins after priming with TNF-α and IFN-Υ for 24 h. HLA-G is a protein that prohibits the growth of lymphocytes, which expression level does not change with priming (Nasef et al. 2007; Selmani et al. 2009; Najar et al. 2012). The expression level of HLA-G in both microfluidic and control groups remained constant after priming. CD54 (iCAM) is a T-cell activation-related protein that is sensitive to inflammation, and the expression level of this protein increased significantly after priming (Rubtsov et al. 2017; Tang et al. 2018). Figure 5C shows that the expression level of CD54 increased 100% after priming in both groups. These results prove that there is no significant difference in the therapeutic properties of the MSCs after proceeding through the microfluidic device. Next, using the Custom ProcartaPlex Multiplex immunoassay panel, we analysed the secretion profile of the harvested cells compared to the secretion profile of cells passaged stably in multilayer cell factories. The results showed that the harvested cells expressed a similar or lower level of HGF, IL-6, CCL2, VEGF-A, and TNF-RI compared to the passage 4, passage 8 multilayer cell factory grown controls, the expression level of SDF-1 alpha and TIMP-1 are much higher than the control group (Fig. 5D).

Multiplexing the microfluidic harvesting system for large-scale application

A multiplexed system was built with the same printing protocols to demonstrate the capability of scaling up the microfluidic system for large-scale applications. The system consists of five layers (Fig. 6); the first layer is the fluid splitting layer; it has one inlet for cell and microcarrier solutions to enter the system and another inlet for the digestive enzyme with a flow rate of 8 mL/min for the cell and microcarrier solution and 4 mL/min for the enzyme. These two inlets split the total flow into four even sets and enter the 4 micromixers evenly in the second layer. The micromixers have inserted holes for the pins to anchor the positions and prevent leakage. The flow rate in each micromixer is 3 mL/min for detaching cells from MCs. The third layer is the spiral layer, with a pin inserted into the outlet of the micromixers. The solutions collected from each of the two micromixers were evenly split into two spiral microfluidic devices, and each spiral received 3 mL/min liquid flow to separate cells from MCs. Then, the fourth layer, a splitting layer was used as the bottom layer of the spiral. Two holes were opened at the outlets of the spirals, and this layer was bonded with the fifth layer spiral layer with double adhesive tape. Lastly, a whole 3D printed layer with 4 zig-zag channels and pressure-damping channels was attached to the splitting layer with double adhesive tape. The inner outlets of each spiral are connected to one pressure-damping channel, and the outer outlets of each spiral are connected to one zig-zag channel. The cross-sectional area ratio of the inner and outer outlet is 2:3; the flow rate of the outer outlet is, therefore 1.8 mL/min for each spiral. As shown in Fig. 2, the zig-zag channel can focus the cells from 1.4–1.9 mL/min. This flexible working range of the zig-zag channel ensures the cells focus on the middle outlet of the device and reduce the requirement of precision of the pressure-damping channel. The total flow rate of the cell outlet was 7.2 mL/min, while the MCs outlet was 4.8 mL/min.

The setup and components of each layer. The multiplexing system consists of five layers: a top guide layer to distribute the liquid evenly into the micromixers; a micromixers layer that detaches MSCs from MCs; a spiral layer separating MSCs and MCs; a middle guide layer that provided a base for spiral and zig-zag channels and a zig-zag channel and pressure-damping channel layer that concentrate the MSCs. The cells and MCs are left from the outlets, respectively

Discussion

The merits of microfluidic devices, such as low-cost, high throughput, labour-free, customisability, and energy efficiency, meet the need of the bioprocessing industry. Recently, multiple attempts have been made to bring microfluidic devices to solve the challenges associated with bioprocessing. However, microfluidic devices are still facing difficulty in accommodating and integrating themselves in the bioprocessing industry. In this manner, 3D printing technology can be used as a bridge to connect microfluidic devices and the bioprocessing industry. The one-step fabrication method of 3D printing technology (printing and washing) allowed us to test 16 zig-zag channels with different dimensions, six different inertial concentrator designs and three micromixers.

In our proposed microfluidic system, cells detachment, separation, and concentration–time are short, 5 min for incubation and 20 s for passing through the system with a total length of < 5 cm. This short processing time could effectively minimise the negative impact of enzymatic treatment on the cell membrane and enhance attachment and growth of harvested cells (Fig. 4), indicating well-preserved cell membrane integrity and functionality. Although the damages caused by enzymatic treatment can be reversible (Tsuji et al. 2017), it takes a few passages for the cells to recover and is not feasible for clinical applications.

The results of cell viability and MTS assays indicate that the viability and proliferation rate of the microfluidic-harvested cells are the same as the control. This is in agreement with the results reported by Nienow et al. (2016), who suggested that agitating cell–MCs suspension facilitates cell detachment while not compromising cells’ properties and viability. As expected, the cells maintain their differentiation potential trilineage (Fig. 5D), their size, spindle morphology (Fig. 4D), and surface markers expression (Fig. 5A). The size and morphology of the cells are important indicators of the cell potencies and secretion profile since different sizes MSCs were shown to have a different expression levels of differentiation promotor/inhibitor genes and different secretion levels of therapeutic factors (Yin et al. 2018, 2020; Lee et al. 2014).

Our experiment showed that the anti-inflammatory surface proteins expression level of the harvested cells during the subsequent subculture had no difference compared to the control group (Fig. 5C). This indicates that the cells preserved their therapeutic properties after the process, and the microfluidic system is safe for the industrial production of stem cells for clinical purposes. The high secretion level of SDF-1α and TIMP-1 proteins suggest strong potential in therapeutic applications. However, these results are not enough to draw the conclusion of whether this harvesting method alters cytokine secretion levels of the MSCs. Previous works show that the topography of the culture system (Leuning et al. 2018) and shifting from 2 to 3D culture (Russell et al. 2018) influenced the cytokine expression level of cells. Ng and Wang (2021) showed that even growing cells on different types of microcarriers influence the secretion profile. Therefore, the secretion profile changes caused by our 3D printed modular harvesting system require further characterisation. These results showed that the cells harvested with our 3D printed modular microfluidic system preserved all the cell properties with no cytotoxic effect, and damage caused by the material, or the hydrodynamic forces was observed.

With the aid of 3D printed technologies (Additional file 1: Section S6), our microfluidics system has multiple advantages over the current laboratory and industrial adherent cell harvesting methods. This microfluidic system requires only two pumps to trigger, and no complicated tubing and valve is needed. This system is cGMP compatible and the design of the system ensures negligible risk of contamination (Tamura et al. 2012; Caruso et al. 2014); The device can be operated in a continuous manner, which is particularly suitable for industrial-scale application (Castilho and Medronho 2002); The system can be used as a single unit system for lab-scale production or easily scaled-up by paralleling the devices together for large volume processing; Other microfluidic devices can also be integrated to perform other functions such as quality control of cellular products (Ding et al. 2021). With the small device footprint, reaching 2 L/min flow rate requires 100 chips, and the total volume would be only 1 m3. It will take 25 min to harvest 50 L MCs. The small footprint allows easy integration into any current-available system, 3D printing technologies allow easy and rapid prototyping of customised fluidic interconnects at a low cost to aid the industrial integration (Ho et al. 2015). On the other hand, our system shows clear advantages over TFF (Schnitzler et al. 2016) with its clogging-free operation manner. This important feature reduces the production cost since the device does not need frequent membrane replacement and maintenance and can be single used due to the low-cost. Also, the low flow rate in each individual unit of our device ensures the cells are not suffering from shear stress like TFF, resulting in cell damage (Cunha et al. 2015). Moreover, this system can be integrated into other enzymatic detachment methods or even enzyme-free cell detachment procedures as well. In recent years, frontier research about smart MCs shows that thermosensitive MCs and soluble MCs have great potential in future cell culture (Tamura et al. 2012; Kalra et al. 2019; Hanga et al. 2021). Proceeding these MCs through our microfluidic gadget may increase exposure to light and heat while benefiting from the agitation of fluid flow. In our multiplexing design, we showcased the first multiplexed modular microfluidic system. The system is built in a nonlinear and modular manner which has not been showcased before. This rapid, low-cost prototyping is not possible without 3D printing technology.

Conclusion

In this paper, we proposed a 3D printed modular microfluidic system consisting of three modules, which are micromixer, microseparator, and microconcentrator, to detach and separate MSCs from MCs. Each module was produced with direct SLA printing, creating highly accurate 3D structures with a low cost and a simple, rapid manufacturing process. Operating at the throughput of 3 mL/min, this microfluidic gadget can detach the cells fully from MCs with 5 min incubation time and 20 s proceeding time through the device, removing 100% of the MCs from cells solution while recovering 77% of cells in one round. The cells passing through the device were viable proliferative with preserving their differentiation potential. More importantly, the therapeutic potential of the cells was well preserved. Our scaled-up version shows that the current system has the potential to apply in the stem cell industry in cGMP compatible manner. Compared to the current system, this gadget is operated in high throughput and clogging-free manner. It simplifies the cell harvesting procedure, minimises the damage and chance of contamination to the cells, and reduces the overall production cost on a large scale. Furthermore, this system is flexible and can potentially be modified to fit with any microcarrier and bioreactor to produce various cell types and products.

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Microfluidic chain reaction of structurally programmed capillary flow events

January 16, 2026May 18, 2022 by CadWorks3DAdmin

Microfluidic chain reaction of structurally programmed capillary flow events

Mohamed Yafia, Oriol Ymbern, Ayokunle O. Olanrewaju, Azim Parandakh, Ahmad Sohrabi Kashani, Johan Renault, Zijie Jin, Geunyong Kim, Andy Ng & David Juncker

Chain reactions, characterized by initiation, propagation and termination, are stochastic at microscopic scales and underlie vital chemical (for example, combustion engines), nuclear and biotechnological (for example, polymerase chain reaction) applications1,2,3,4,5. At macroscopic scales, chain reactions are deterministic and limited to applications for entertainment and art such as falling dominoes and Rube Goldberg machines. On the other hand, the microfluidic lab-on-a-chip (also called a micro-total analysis system)6,7 was visualized as an integrated chip, akin to microelectronic integrated circuits, yet in practice remains dependent on cumbersome peripherals, connections and a computer for automation8,9,10,11. Capillary microfluidics integrate energy supply and flow control onto a single chip by using capillary phenomena, but programmability remains rudimentary with at most a handful (eight) operations possible12,13,14,15,16,17,18,19. Here we introduce the microfluidic chain reaction (MCR) as the conditional, structurally programmed propagation of capillary flow events. Monolithic chips integrating a MCR are three-dimensionally printed, and powered by the free energy of a paper pump, autonomously execute liquid handling algorithms step-by-step. With MCR, we automated (1) the sequential release of 300 aliquots across chained, interconnected chips, (2) a protocol for severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) antibodies detection in saliva and (3) a thrombin generation assay by continuous subsampling and analysis of coagulation-activated plasma with parallel operations including timers, iterative cycles of synchronous flow and stop-flow operations. MCRs are untethered from and unencumbered by peripherals, encode programs structurally in situ and can form a frugal, versatile, bona fide lab-on-a-chip with wide-ranging applications in liquid handling and point-of-care diagnostics.

We kindly thank the researchers at McGill University for this collaboration, and for sharing the results obtained with their system.

Main

The MCR encodes the deterministic release of reagents stored in a series of reservoirs, with the release of reservoir n being conditional on the emptying (draining) of the reagent in reservoir n − 1, and emptying reservoir n, in turn triggering the release of reservoir n + 1. Capillary domino valves (CDVs) encode this condition, and serially connect, that is, chain, the reservoirs, and thus control the propagation of the chain reaction (Fig. 1a). MCRs were implemented in three-dimensionally printed circuits made with a common stereolithography printer with feature size from 100 µm to 1.5 mm, hydrophilized using a plasma chamber (Extended Data Fig. 1 and 2), sealed with a plain cover and connected to a capillary pump made of paper (filter papers or absorbent pads). The paper was spontaneously wetted by aqueous solution drawn from the microfluidic circuit by releasing free energy stored in the paper surface, and this drove the chain reaction; expressed differently, the capillary pump generated a negative capillary pressure that was hydraulically transmitted back into the circuit through the main channel and serially drained side-reservoirs connected by a small conduit, called the functional connection (further described below). CDVs form air links between adjacent reservoirs, serially connecting them along a path parallel to the main channel, but interrupted by filled reservoirs that form liquid plugs between CDV air links. When the (first) reservoir connected to the air vent through a continuous air link is emptied, the plug is removed and the length of the air link propagates to the next filled reservoir in the MCR (Fig. 1a–d and Supplementary Video 1). This simple design structurally encodes the conditional propagation of capillary flow events and the step-by-step release of an arbitrary number N of reservoirs without peripheral connections or moving parts, and is further detailed in the Supplementary Information.

a, (i) Serial MCR, (ii) branching MCR, (iii) cascaded, timed MCR. b, MCR unit with three reservoirs chained through CDVs and close-up of dual function SV/RBVs that keep liquid out of the CDV air link (forming a pneumatic connection) and prevent premature drainage. c, Symbolic view of the MCR unit with capillary retention valves (infinity symbol), CDV (grey overlay) that includes an air link, two SV/RBVs and functional connection. d, Screen shots of Supplementary Video 1 showing MCR sequences in which most of the capillary elements have dual functions, one during reagent loading, one during MCR propagation. (i) A loaded chip with liquids confined to the reservoirs by physical and capillary valves. (ii) MCR is triggered (the inlet becomes a capillary retention valve and the top SV becomes a RBV). (iii) Emptying of the first reservoir on bursting of the top RBV. (iv) The bottom SV momentarily becomes an RBV that bursts immediately. (v) Air now occupies the emptied reservoir. The functional connection (FC) becomes a capillary retention valve preventing the air from penetrating into in the main channel. The air link connects the air to the RBV of the next reservoir, which bursts and triggers reservoir emptying. Scale bar, 2 mm.

MCRs require ancillary capillary microfluidic components that fulfil different functions depending on the intended operation (for example, loading, holding, mixing and draining liquids following the MCR progression) to form fully integrated and scalable capillaric circuits (CCs). CCs are designed on the basis of a library of building blocks including capillary pumps, flow resistances and many types of capillary valve (stop valves (SVs), trigger valves, retention valves, retention burst valves (RBVs))12,14, and thus are analogous to microelectronic integrated circuits, but lacking the scalability and functionality. In MCRs, samples are loaded by capillary flow through an inlet with a capillary retention valve and entirely fill the reservoirs lined with three SVs, including two with a dual RBV function connecting to the two lateral CDVs, and one at the intersection of the functional connection and the main channel (Fig. 1c). Although the functional connection is a deceptively simple straight channel, it fulfils six key functions. It is (1) the air vent during filling of the reservoir, and (2) a SV preventing the reagent from spilling into the main channel while it is empty. After filling of the main channel, it forms a (3) hydraulic link propagating the pressure from the main channel into the reservoir and (4) a barrier (and bottleneck) to the diffusion of reagents between the reservoir and the main channel. (5) It becomes the outlet and a flow resistance (discussed further below) during reservoir emptying, and (6) a capillary retention valve stopping air from invading the main conduit after the reservoir is emptied. As a result, many trade-offs guide its design.

We sought to understand the design window and failure modes of MCRs, notably under which conditions downstream of CDVs might trigger prematurely, using both theory and experiments. MCR-CCs incorporate numerous capillary SVs according to previously established design criteria13 and while considering three-dimensional (3D) printer performance including resolution, imprecision and printing errors. We then analysed the MCR based on an electrical circuit analogy (Extended Data Fig. 3) and derived a simplified circuit that neglects minor resistances (Fig. 2a)13. Successful and incremental propagation of the MCR is conditional on preventing the breach of the liquid in reservoir n into the CDV and air link connecting n + 1, which is equivalent to stating that all the liquid in reservoir n must flow exclusively through the functional connection n.

a, The simplified equivalent electrical circuit of the MCR units shown in Fig. 1. b, Experimental SV burst pressure (1) and RBV retention pressure (2) for valves with conduits with different, square cross-sections fitted with a numerical and an analytical model, respectively. c, Illustration of failure for a CDV with long serpentine FCs with very high resistance leading to liquid breach inside the air link, and premature draining of reservoir n + 1. d, Tests of six MCRs with increasing RFC and three different paper pumps to determine the effect of varying the flow rate (n = 3 for each paper pump and RFC). All data points are shown in b and d. Error bars are standard deviations from three experiments, the centre of each error bar is the mean value. As predicted, the CDVs fail when the pressure drop across the FC PFC(n) exceeds the CDV threshold pressure PBURS(n) + PRBV(n+1).

The flow path from reservoir n to n + 1 is interrupted by the CDV, which includes the capillary SV at one extremity and RBV at the other, with bursting thresholds of PBURS and PRBV, respectively. If either of these valves fails prematurely, then the propagation of the MCR is at risk of disruption. But because both valves are pneumatically connected by the air trapped within the air link, their pressures are additive and hence the threshold for failure of either is the sum of the two. The condition for success is QFAIL = 0, which during drainage of reservoir n is satisfied if the pressure drop on the functional connection (FC) PFC = QFC × RFC is (see also Supplementary Information for a detailed mathematical derivation):

We calculated PBURS (numerically)20 and PRBV (analytically, Supplementary Information) for conduits with a square cross-section (W = H) for the typical dimension in our 3D-printed CCs, and measured them experimentally for validation (Fig. 2b and Extended Data Fig. 4). Both PBURS and PRBV are inversely proportional to the smallest dimension of the rectangular conduit. We accounted for the hydrophobic ceiling formed by the sealing tape in both cases (Extended Data Fig. 2b), and which is a key feature to forming a functional SV20. Note that because of the comparatively low pressures and small volume of the air links, the compressibility of air is negligible here.

Next, several MCRs featuring functional connections with large and increasing RFC were tested with pumps with different capillary pressure and flow rates. The interplay between the resistance and the flow rate determines the operational window for the CDV while they are inversely proportional. We found excellent concordance between theory and experiments for the operation window of the MCR, and failure only occurred for the highest values of RFC (nos. 5 and 6), and for only the most powerful capillary pumps (Fig. 2c,d and Extended Data Fig. 5). The MCR designs used in the proof-of-concept applications, shown below, are well within the failure threshold, helping to ensure reliable propagation of the chain reaction.

We designed a chip-to-chip interface with a leakage-free connection for liquid (main channel) and air (connecting the CDVs), respectively, and connected four chips with 75 MCRs each (Fig. 3a and Supplementary Video 2). This result illustrates the reliability of the MCR and of CDVs, and demonstrates integrated, large-scale fluidic operations by ‘passive’ capillary microfluidics, beyond the capability of many ‘active’, computer programmable microfluidic systems.

Fig. 3: Large-scale MCR and COVID-19 serology assay in saliva.

a, A MCR of 300 aliquots stored in 4.9 µl reservoirs across four chained and interconnected chips (Supplementary Video 2). b, SARS-CoV-2 antibody detection in saliva. Sequential, preprogrammed release of reagents by MCR is triggered by connecting the paper pump (Supplementary Video 3). The MCR supplies four reagents and four buffers in sequence. The functionality includes delivery and removal (by flushing) of solutions, metering (40–200 µl) by reservoir size, flow speed and time control by the flow resistance of the FC and the capillary pressure of the paper pump. The enzymatic amplification produces a brown precipitate line visible to the naked eye. c, Assay results and binding curve obtained by spiking antibody into saliva, and imaging by scanner and cell phone with representative images of the detection zone for each concentration, indicating the potential for quantitative point-of-care assays. d, An assembled chip filled with coloured solutions highlighting the channels for the different reagents and washing buffer.

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Automated SARS-CoV-2-specific saliva antibody detection assay

We measured antibodies against the nucleocapsid protein (N protein) of SARS-CoV-2 in saliva, with application potential for early infection detection21,22, initial patient assessment as prognosis indicator23 and for serosurveys to differentiate vaccinated and naturally infected individuals24. Conventional lateral flow assays with predried reagents are simple to operate, but typically do not include enzymatic amplification that underlies the laboratory enzyme-linked immunosorbent assay (ELISA), and have to be read out within a few minutes of completion. Here, we used MCR to automate a sequence of eight steps in common laboratory ELISA protocols (Fig. 3b and Supplementary Video 3). The chip is connected to a small paper pump to drain excess buffer, and a nitrocellulose strip for assay readout itself connected to a large-capacity paper pump that drives the MCR. Note that the MCR propagates in a direction opposite from the flow in the main channel, and reagents released sequentially from reservoirs all flow past previously emptied reservoirs, thus minimizing the diffusional mixing between reagents. We used 3,3ʹ-diaminobenzidine as a substrate that on enzymatic conversion produced a brown, persisting precipitate that could serve both as an immediate readout and a record for archival. Assay parameters such as volume, time and reagent concentrations were optimized extensively following standard protocols (see Extended Data Fig. 6 for examples) and will be reported elsewhere. The result can be visualized by the naked eye or quantified using a scanner or a smartphone integrated with a simple folded origami box to minimize light interference, with a sensitive, quantitative and reproducible output (Fig. 3c and Extended Data Figs. 7 and 8).

Automated microfluidic thrombin generation assay (TGA)

Routine coagulation tests (prothrombin time and activated partial thromboplastin time) are used as initial evaluation of haemostatic status. These tests terminate on clot formation and thus only inform on the initiation of clotting, whereas the coagulation cascade continues and generates 95% of total thrombin (the final enzyme in the coagulation cascade)25. The haemostatic capacity, expressed as the endogenous thrombin potential, can therefore not be fully evaluated by these tests26. Global coagulation assays, such as the TGA that provides the time-course of active thrombin concentration in clotting plasma, are better measures of haemostatic function. Peak height, shape and area under curve of the thrombin generation curve (also known as the thrombogram, Fig. 4a) can be determined and correlated to clinical phenotypes to investigate coagulation disorders, and measure the effect of anticoagulants27. The first TGA was introduced in the 1950s, and involves the activation of coagulation of blood or plasma, followed by a two-stage assay that requires the collection and mixing of subsamples with fibrinogen (or chromogenic substrates following their availability) at precisely timed intervals (for example, 1 min) over the course of 20 min or so, followed by the quantification of thrombin in each of them28,29. The labour intensity, strict timing requirements and risk of error are great obstacles to wider adoption and clinical use of TGAs-by-subsampling. The calibrated automated thrombogram (CAT) introduced in 2002 simplifies operations thanks to newly synthesized thrombin substrates, a calibration TGA using the patient sample spiked with reference material and mathematical extrapolation30.

a, Model thrombin generation curve (thrombograms) for plasma with normal (red) and disordered (blue) coagulation. The grey box is the time window of the thrombochip. b, TGA operations and algorithm encoded in the thrombochip. c, Schematic of the thrombochip with inset. d, The (i) timer, (ii) simultaneous release of defibrinated plasma and reagents (quencher and substrate), (iii) mixing and (iv) flow-stop in the reaction chamber and monitoring of the fluorescence time-course signal. e, Fluorescent thrombin substrate turnover in the ten 1-min interval subsamples; the slope of each curve is proportional to thrombin concentration, and is one data point in the thrombogram. f, g, Abridged thrombograms of defibrinated human plasma that is normal (three replicates of pooled plasma), factor depleted (F5, F8, F9; single measurement for each factor) (f) and mixed with anticoagulant drug (Enoxaparin) at different concentrations (g) (single measurement at each concentration). The thrombin generation time-courses are concordant with expectations.

Here, we demonstrate the capacity of MCR to automate the original TGA-by-subsampling in a microfluidic implementation that we called a "thrombochip". We devised an algorithm (Fig. 4b) for automating and timing the procedure with cascaded, iterative and branching fluidic operations, and structurally programmed it into a 3D-printed chip (Fig. 4c, Extended Data Fig. 9 and Supplementary Video 4). Defibrinated, coagulation-activated plasma subsamples and reagent were loaded into the thrombochip, and on triggering of the MCR, without further intervention, they were released at 1 min intervals from the ten pairs of reservoirs, mixed in the serpentine mixer and stored in a 2.1 µl reaction chamber with a width of 500 µm for fluorescence signal generation and readout using a camera (Supplementary Videos 5 and 6). The concentration of thrombin in each of the subsamples is proportional to the rate of the fluorescent substrate turnover, and the time-course of thrombin is reported as a thrombogram.

Reliable execution of the TGA subsample analysis algorithm faced several practical challenges, and in particular draining of two reservoirs simultaneously is inherently unstable. Indeed, as soon as one reservoir starts being drained, the (absolute) pressure in the CC drops, and readily falls below the threshold of the RBV of the second reservoir, which will not burst, meaning the reservoir will remain filled. The MCR and 3D printing helped overcome this challenge and the reservoir pair containing plasma and reagents could be drained synchronously. An embedded air link connecting the outlet of reservoir n to the RBVs of both n + 1 and n + 1’, which were identical and very weak RBVs (cross-section, 1 × 1 mm2) lead to simultaneous bursting and reliable propagation of the chain reaction. Other critical features are a serpentine mixer; stop-flow and holding of the solution in the reaction chambers for the thrombin quantification; a pressure pinning structure at the main outlet to cut the hydraulic connection to the paper pump after completion of the fluidic operation; an RBV at the main outlet that pins liquid and helps prevent backflow to safeguards the reaction chambers from uncontrolled mixing and finally evaporation during the extended monitoring and imaging of the thrombin reaction.

As validation of the thrombochip, human pooled plasma, plasma depleted of Factors V, VIII and IX, and plasma spiked with the anticoagulant Enoxaparin (an anti-Factor Xa drug) were analysed. The corresponding thrombograms were reproducible, consistent with normal and impaired coagulation cascades caused by factor depletion, and measured the dose-response of Enoxaparin (Fig. 4f, g). The general profile of the thrombograms generated in these proof-of-concept experiments are comparable to those by CAT and other microtitre plate-based assays31,32, but direct comparison of the data such as lag time and peak concentration requires standardized sample processing, reference materials and normalization, which can guide future development of the thrombochip.

Conclusion and discussion

MCRs introduce deterministic, modular and programmable chain reactions at the mesoscale and constitute a new concept for autonomous, programmable liquid operations and algorithms by control of both hydraulic and pneumatic flow and connectivity. The automation of complex and repetitive liquid handling operations has so far only been possible with a computer, software programs and cumbersome peripheral equipment, either robotics or, in the case of microfluidics6, systems to supply reagents, power or flow control8,9,10,11. MCR introduces mesoscale chain reactions as a frugal, integrated, scalable and programmable process that power integrated labs-on-a-chip.

The MCR chip micro-architecture is simultaneously the circuit and the code of the chain reaction, is manufacturable with a variety of techniques and scalable along two distinctive paths: First, following microelectronics example and Moore’s law, by shrinking and increasing the number of features per unit area and per unit volume (for example, by using 3D printing). Second, by expanding the overall size of CC-MCRs by interconnecting and chaining chips, and, inspired by trees that draw liquids more than 100 m in height, linking them to powerful capillary pumps33. We anticipate numbers of steps far beyond the 300 shown here, and far more complex algorithms than the ones of the thrombochip.

MCRs are generalizable, compatible with positive pressure operations and could be interfaced with active microfluidics and robotic liquid handling systems. Spontaneous, capillary flow MCRs may be further improved too with permanently hydrophilic resins or coatings, liquid storage pouches and predried reagents34, notably for point-of-care applications and any other uses. An end-user, by simply depositing a drop of solution at the inlet, could trigger a choreography of timed operations including aliquoting, delivery, mixing, flushing and reactions of several chemicals. As MCRs can be 3D-printed and monolithically encoded in a chip, the entry barrier is very low (entry-level resin-based printers cost <US$300). MCRs may be home-manufactured easily, or mail-ordered, opening the way for rapid dissemination and for new inventions, advances and for downloadable and printable microfluidic apps.

Methods

Chip design and fabrication
The chips were designed using AutoCAD (Autodesk) and exported as .STL files for 3D printing. CCs encoding MCRs were made with a digital micromirror display (DMD) 3D printer (Miicraft 100, Creative Cadworks) using a transparent resin (Rapid Model Resin Clear, Monocure 3D) purchased from filaments.ca. The following printing parameters were used: the layer thickness was 20 µm and the exposure time 1.5 s per layer, whereas the exposure time for the base layer was 10 s with four transition buffer layers. Following completion of the print, the chips were cleaned with isopropanol and post-cured for 1 min under ultraviolet (UV) light (Professional CureZone, Creative Cadworks).

Microchannels with cross-sections ranging from 250 × 100 to 1,500 × 1,000 µm2 were fabricated and hydrophilized by plasma activation for 10 s at approximately 30% power (PE50 plasma chamber, Plasma Etch).

CCs were sealed with a delayed tack adhesive tape (9795R microfluidic tape, 3M) forming the cover.

Paper capillary pump Filter papers (Whatman filter paper grade 4, 1 and 50 Hardened, Cytiva) were used as paper capillary pumps for all experiments except the SARS-CoV-2 antibody assay. The pore size from 4, 1 and 50 hardened is in decreasing order, and flow resistance and capillary pressure increase with decreasing pore size.

For the SARS-CoV-2 antibody assay, absorbent pads (Electrophoresis and Blotting Paper, Grade 238, Ahlstrom-Munksjo Chromatography) were used as pumps.

Chip-to-chip connections for the 300 capillary flow events
To obtain a leakage-free connection, a thin layer of uncured photoresin, prepared by mixing poly (ethylene glycol) diacrylate (PEG-DA MW 258, Sigma-Aldrich) and Irgacure-819 (1% w/w), was applied to all of the chip-to-chip interfaces. Next, the chips were assembled and exposed to UV light in a UV chamber (320–390 nm, UVitron Intelliray 600) at 50% intensity for 30 s to cure the resin and seal the connections.

Videos and image processing
Videos and images were recorded using a Panasonic Lumix DMC-GH3K. Structural images of the chip and the embedded conduits were obtained using micro-computed tomography (Skyscan 1172, Bruker) and used to confirm the dimensions. Contact angles were measured on the basis of side view images (n = 3) and analysed using the Dropsnake extension in Image J.

Modelling and calculations
The theoretical burst pressures of capillary SVs were calculated by solving the flow field using the finite element method with COMSOL Multiphysics v.5.5. Experimentally measured contact angles (100º and 40º for the cover and the channel, respectively) were used to solve two-phase capillary flow using the level-set method. The capillary flows leading up to the SV was solved for a time period of 0–0.02 s with a time step of 1 × 10−5 s. The inlet pressure was varied with 10 Pa increment for each simulation until a burst was observed.

Experiments on pressure thresholds for capillary SV and RBV
We 3D-printed modules to evaluate SV/RBV with different cross-section areas. Each module contained three SV/RBV for replicate results. SV/RBV consisted of a two-level SV based on a geometrical channel expansion, as described elsewhere12. The chips integrated a conical inlet/outlet for tubing connection to a microfluidic flow controller system (MFCS-4C) and Fluiwell package (Fluigent) with fluidic reservoirs containing 5% red food dye in MilliQ water solution (see Extended Data Fig. 4 for setup images and Fig. 2 for contact angles). MAESFLO v.3.3.1 software (Fluigent) controlled the application of positive or negative pressure to calculate the burst pressures of the SV (liquid burst into air link) and RBV (receding meniscus), with increments of 0.1 mbar (roughly 10 Pa).

SARS-CoV-2 antibody assay
Reagents
SARS-CoV-2 nucleocapsid protein was purchased from Sino Biological, Inc. (40588-V08B). Human Chimeric antibody against SARS-CoV-2 nucleocapsid protein was purchased from Genscript Biotech (A02039). SIGMAFAST 3,3ʹ-diaminobenzidine tablets were purchased from Sigma-Aldrich. Biotinylated Goat-anti-Human antibody was purchased from Cedarlane (GTXHU-003-DBIO). Pierce streptavidin poly-HRP (21140) was purchased from ThermoFisher.

Nitrocellulose strips
Nitrocellulose membranes (Whatman FF80HP Plus nitrocellulose-backed membranes, Cytiva) were cut into 5.2-mm-wide strips using the Silhouette Portrait paper cutter (Silhouette). Membranes were striped with a 5-mm-wide test line of 0.25 mg ml−1 SARS-CoV-2 nucleocapsid protein delivered using a programmable inkjet spotter (sciFLEXARRAYER SX, Scienion). The test line consists of four lanes of 50 droplets of about 350 pl printed 100 µm apart from each other. Eight passes of 25 droplets were used for each lane on even and odd positions to allow solution absorption in between passes. The membranes were then dried for 1 h at 37 °C before blocking by dipping into 1% BSA in 1× PBS solution until completely wet, then retrieved and left to dry for 1 h at 37 °C and then stored with desiccant at 4 °C until use the next day.

Connection of capillary pump and nitrocellulose chip to MCR chips
Nitrocellulose strips were mounted following standard lateral flow assay assembly protocols. The nitrocellulose strip was connected to a glass fibre conjugate pad (G041 SureWick, Millipore Sigma) on one end, and to an absorbent pad (Electrophoresis and Blotting Paper, Grade 238, Ahlstrom-Munksjo Chromatography) serving as the capillary pump at the other end. All three were attached to an adhesive tape serving as the backing layer. For the saliva antibody assay, the nitrocellulose strip was sandwiched between three absorbent pads (15 × 25 mm2) and clamped with a paper clip. For the food-dye demonstrations a single absorbent pad (25 × 45 mm2) was magnetically clamped to the nitrocellulose membrane.

Saliva assay protocol
Human saliva was extracted with oral swabs (SalivaBio, Salimetrics), followed by centrifugation and 1:10 dilution with 0.22 µM filtered phosphate buffer saline containing 1% BSA, 0.1% Tween 20. Human chimeric antibody against SARS-CoV-2 nucleocapsid protein at 0 to 1,000 ng ml−1 was spiked into diluted saliva and loaded to the sample reservoirs. Three replicate measurements for concentrations of 0–10 ng ml−1, two replicate measurements for concentrations of 30–300 ng ml−1 and one measurement for 1,000 ng ml−1. Biotinylated goat anti-human antibody at 0.5 µg ml−1 and streptavidin poly-HRP at 0.5 µg ml−1 were used to detect the human antibody. Control line in the nitrocellulose strip confirms reagents delivery and colorimetric reaction completion.

Image analysis on the nitrocellulose strips
After drainage of all reservoirs, the nitrocellulose membrane strip was removed, placed on a support and left to dry for 1 h.

The dry strips were imaged using (1) a flatbed scanner (mfc-9970cdw, Brother) at a resolution of 600 dpi and (2) using a Huawei P10 smartphone with a 12 megapixel image sensor and a rear camera with a 27 mm focal length (Huawei) in a customized box. The box was cut and folded with black cardboard paper to block ambient light when imaging with the smartphone. The box had two slots fitting the size of camera and nitrocellulose strip, respectively, to ensure accurate alignment of the strip for readout. Images were taken with on-camera dual tone light-emitting diode flash at full power. Analysis of smartphone-taken and scanned images was done as follows.

Mean grey values of nitrocellulose test lines were extracted with ImageJ 1.48v (ImageJ, public domain software, W. Rasband, National Institutes of Health) within a 100 × 10 pixel rectangular area. Local background grey values were taken at 2.5 mm (0.1 inch) above each test line (following direction of the flow) for the same rectangular area, and subtracted from test line values. The normalized standard curve was then generated by subtracting negative control signal value (0 ng ml−1) from all data points.

The limit of detection was calculated using the three-sigma criterion using a non-linear four-parameter logistic curve fit of the log-transformed data with OriginPro 8.5 SPR (OriginLab Corporation).

Automated microfluidic TGA (Thrombochip)
Citrated human plasma (P9523, lot number SLBX8880), fluorogenic thrombin substrate Z-GGR-AMC and Enoxaparin were purchased from Sigma-Aldrich; Batroxobin was from Prospec; Technothrombin TGA RC High reagent was from Diapharma; Human thrombin, non-patient plasma that were immuno-depleted of Factor V and Factor IX, and Factor VIII inactivated were from Haematologic Technologies; (4-(2-hydroxyethyl)-1-piperazineethanesulfonic acid) (HEPES), and ethylenediaminetetraacetic acid (EDTA) and CaCl2 were from Sigma-Aldrich.

The purchased pooled human plasma (collected in the United States in a Food and Drug Administration licensed centre site no. 268, as specified in the Certificate of Origin supplied by the manufacturer) was prepared by the manufacturer from whole blood collected by standard industry method using 4% trisodium citrate as an anticoagulant, pooled and then centrifuged. The resulting plasma was 0.45 µm filtered and lyophilized. Factor V- and Factor IX-depleted plasma were immune depleted; Factor VIII-depleted plasma was prepared by chemical depletion. The plasma preparations were assayed to ensure the activity of the remaining factors by the manufacturer.

Human plasma (pooled normal or factor depleted) were defibrinated by the addition of batroxobin (final concentration 0.6 BU ml−1). The mixtures were incubated at room temperature for 20 min, followed by an extra incubation at 4 °C for 1 h. The mixtures were then centrifuged at 10,000g for 10 min to remove the fibrin clot and other debris. Defibrinated plasma were collected from the supernatant.

A solution containing 21% defibrinated plasma (plasma defibrination is needed to prevent clogging of the microfluidic channels by the fibrin clot), 48% Technothrombin TGA RC High reagent (high phospholipid and relipidated tissue factor content) and 20 mM CaCl2 in 25 mM HEPES at pH 7.4 was loaded into the sample reservoirs of the thrombochip. A substrate solution containing 420 µM Z-GGR-AMC, 30 mM EDTA in 25 mM HEPES at pH 7.4 was loaded into the reagent reservoirs. The concentration of plasma, activation agent and substrate were optimized to yield a peak thrombin concentration and time of 150 nM and 200 s. All solutions were equilibrated to room temperature for 20 min before loading. Coagulation-inhibited plasma contained Enoxaparin at final concentrations of 0 to 1.0 anti-Xa units ml−1 or IU ml−1. The samples and reagents were loaded on the chip after initiating the coagulation cascade. The paper pump was connected to the chip to start the flow after 5 min from initiating the coagulation cascade. Fluorescence signals generated in the reaction chambers were monitored by illuminating the thrombochip with UV light at 365 nm with 20 W (realUV LED Flood Light, Waveform Lighting) and the visible 440 nm fluorescence emission signals measured by imaging at 5 s intervals using a Panasonic Lumix DMC-GH3K digital camera (f/3.5, Exposure time: 2 s, ISO-200). The rate of fluorescence signal generation in each reaction chamber (that is, the slope of the recorded fluorescence generation curve) is a measure of the rate of substrate turnover by thrombin and was used to deduce the amount of thrombin generated using a standard curve. Image J was used to analyse the images for fluorescence intensity.

Standard curve for thrombin quantification
Ten human thrombin solutions at concentrations ranging from 0 to 300 nM in 25 mM HEPES at pH 7.4 were loaded into the ten sample reservoirs in the thrombochip. A substrate solution containing 420 µM Z-GGR-AMC, 30 mM EDTA in 25 mM HEPES at pH 7.4 was loaded into the reagent reservoirs. The standard curve was constructed by plotting the slope of the recorded fluorescence generation curve in each reaction chamber against the known thrombin concentration of the solution that was loaded to the corresponding sample reservoir.

Reporting summary
Further information on research design is available in the Nature Research Reporting Summary linked to this paper. Data availability The 3D design files of the MCR-CC chips are included as part of this article, and are also available for download along with more images and descriptions at https://www.thingiverse.com/junckerlab/collections/microfluidic-chain-reaction-of-structurally-programmed-capillary-flow-events. Data not presented in the article or supplementary material will be available upon request. Source data are provided with this paper.

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