Teflon films for chemically-inert microfluidic valves and pumps
Bibliographic record
Abstract
We present a simple method for fabricating chemically-inert Teflon microfluidic valves and pumps in glass microfluidic devices. These structures are modeled after monolithic membrane valves and pumps that utilize a featureless polydimethylsiloxane (PDMS) membrane bonded between two etched glass wafers. The limited chemical compatibility of PDMS has necessitated research into alternative materials for microfluidic devices. Previous work has shown that spin-coated amorphous fluoropolymers and Teflon-fluoropolymer laminates can be fabricated and substituted for PDMS in monolithic membrane valves and pumps for space flight applications. However, the complex process for fabricating these spin-coated Teflon films and laminates may preclude their use in many research and manufacturing contexts. As an alternative, we show that commercially-available fluorinated ethylene-propylene (FEP) Teflon films can be used to fabricate chemically-inert monolithic membrane valves and pumps in glass microfluidic devices. The FEP Teflon valves and pumps presented here are simple to fabricate, function similarly to their PDMS counterparts, maintain their performance over extended use, and are resistant to virtually all chemicals. These structures should facilitate lab-on-a-chip research involving a vast array of chemistries that are incompatible with native PDMS microfluidic devices.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".