Thermoplastic elastomer with advanced hydrophilization and bonding performances for rapid (30 s) and easy molding of microfluidic devices
Bibliographic record
Abstract
One of the most important areas of research on microfluidic technologies focuses on the identification and characterisation of novel materials with enhanced properties and versatility. Here we present a fast, easy and inexpensive microstructuration method for the fabrication of novel, flexible, transparent and biocompatible microfluidic devices. Using a simple hot press, we demonstrate the rapid (30 s) production of various microfluidic prototypes embossed in a commercially available soft thermoplastic elastomer (sTPE). This styrenic block copolymer (BCP) material is as flexible as PDMS and as thermoformable as classical thermoplastics. It exhibits high fidelity of replication using SU-8 and epoxy master molds in a highly convenient low-isobar (0.4 bar) and iso-thermal process. Microfluidic devices can then be easily sealed using either a simple hot plate or even a room-temperature assembly, allowing them to sustain liquid pressures of 2 and 0.6 bar, respectively. The excellent sorption and biocompatibility properties of the microchips were validated via a standard rhodamine dye assay as well as a sensitive yeast cell-based assay. The morphology and composition of the surface area after plasma treatment for hydrophilization purposes are stable and show constant and homogenous distribution of block nanodomains (∼22° after 4 days). These domains, which are evenly distributed on the nanoscale, therefore account for the uniform and convenient surface of a "microfluidic scale device". To our knowledge, this is the first thermoplastic elastomer material that can be used for fast and reliable fabrication and assembly of microdevices while maintaining a high and stable hydrophilicity.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".