MétaCan
Menu
Back to cohort
Record W2315973112 · doi:10.1021/la501723n

Functional Polymer Sheet Patterning Using Microfluidics

2014· article· en· W2315973112 on OpenAlexafffund
Minggan Li, Mouhita Humayun, Janusz A. Koziński, Dae Kun Hwang

Bibliographic record

VenueLangmuir · 2014
Typearticle
Languageen
FieldEngineering
TopicNanofabrication and Lithography Techniques
Canadian institutionsYork UniversityToronto Metropolitan University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMicrofluidicsNanotechnologyLithographyFabricationMaterials sciencePDMS stampPlanarPolymerNanoscopic scaleOptoelectronicsComputer scienceComposite material

Abstract

fetched live from OpenAlex

Poly(dimethylsiloxane) (PDMS)-based microfluidics provide a novel approach to advanced material synthesis. While PDMS has been successfully used in a wide range of industrial applications, due to the weak mechanical property channels generally possess low aspect ratios (AR) and thus produce microparticles with similarly low ARs. By increasing the channel width to nearly 1 cm, AR to 267, and implementing flow lithography, we were able to establish the slit-channel lithography. Not only does this allow us to synthesize sheet materials bearing multiscale features and tunable chemical anisotropy but it also allows us to fabricate functional layered sheet structures in a one-step, high-throughput fashion. We showcased the technique's potential role in various applications, such as the synthesis of planar material with micro- and nanoscale features, surface morphologies, construction of tubular and 3D layered hydrogel tissue scaffolds, and one-step formation of radio frequency identification (RFID) tags. The method introduced offers a novel route to functional sheet material synthesis and sheet system fabrication.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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: Empirical
Teacher disagreement score0.422
Threshold uncertainty score0.290

Codex and Gemma teacher scores by category

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

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.

Opus teacher head0.013
GPT teacher head0.206
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 teacher head, 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

Citations30
Published2014
Admission routes2
Has abstractyes

Explore more

Same venueLangmuirSame topicNanofabrication and Lithography TechniquesFrench-language works237,207