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Record W2014609842 · doi:10.1021/ac048303p

Torque-Actuated Valves for Microfluidics

2005· article· en· W2014609842 on OpenAlexfundno aff
Douglas B. Weibel, Maarten Kruithof, Scott Potenta, Samuel K. Sia, Andrew Lee, George M. Whitesides

Bibliographic record

VenueAnalytical Chemistry · 2005
Typearticle
Languageen
FieldEngineering
TopicMicrofluidic and Capillary Electrophoresis Applications
Canadian institutionsnot available
FundersDivision of Materials ResearchNational Institute of General Medical SciencesDefense Advanced Research Projects AgencyCanadian Institutes of Health ResearchMaterials Research Science and Engineering Center, Harvard UniversityNational Institutes of HealthNational Science Foundation
KeywordsChemistryMicrofluidicsTorqueNanotechnologyMechanical engineeringThermodynamicsEngineering

Abstract

fetched live from OpenAlex

This paper describes torque-actuated valves for controlling the flow of fluids in microfluidic channels. The valves consist of small machine screws (> or =500 microm) embedded in a layer of polyurethane cast above microfluidic channels fabricated in poly(dimethylsiloxane) (PDMS). The polyurethane is cured photochemically with the screws in place; on curing, it bonds to the surrounding layer of PDMS and forms a stiff layer that retains an impression of the threads of the screws. The valves were separated from the ceiling of microfluidic channels by a layer of PDMS and were integrated into channels using a simple procedure compatible with soft lithography and rapid prototyping. Turning the screws actuated the valves by collapsing the PDMS layer between the valve and channel, controlling the flow of fluids in the underlying channels. These valves have the useful characteristic that they do not require power to retain their setting (on/off). They also allow settings between "on" and "off" and can be integrated into portable, disposable microfluidic devices for carrying out sandwich immunoassays.

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 score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.002

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 head0.008
GPT teacher head0.224
Teacher spread0.216 · 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

Citations192
Published2005
Admission routes1
Has abstractyes

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