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Record W2114631721 · doi:10.1039/b800600h

Teflon films for chemically-inert microfluidic valves and pumps

2008· article· en· W2114631721 on OpenAlexfundno aff
William H. Grover, Marcio G. von Muhlen, Scott R. Manalis

Bibliographic record

VenueLab on a Chip · 2008
Typearticle
Languageen
FieldEngineering
TopicMicrofluidic and Capillary Electrophoresis Applications
Canadian institutionsnot available
FundersNational Institute of General Medical SciencesNational Cancer InstituteMcMaster University
KeywordsPolydimethylsiloxaneMicrofluidicsMaterials scienceInertFluoropolymerMembraneNanotechnologyWaferPDMS stampPolymerComposite materialFabricationChemistryOrganic chemistry

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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.

Opus teacher head0.010
GPT teacher head0.203
Teacher spread0.193 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations126
Published2008
Admission routes1
Has abstractyes

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