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Record W2618557262 · doi:10.1049/mnl.2017.0230

Oxygen plasma treatments of polydimethylsiloxane surfaces: effect of the atomic oxygen on capillary flow in the microchannels

2017· article· en· W2618557262 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueMicro & Nano Letters · 2017
Typearticle
Languageen
FieldMaterials Science
TopicSurface Modification and Superhydrophobicity
Canadian institutionsInstitut National de la Recherche Scientifique
Fundersnot available
KeywordsPolydimethylsiloxaneOxygenCapillary actionMaterials scienceChemistryMicrochannelPlasmaNanotechnologyComposite materialOrganic chemistry

Abstract

fetched live from OpenAlex

Modification of polydimethylsoloxane/water interaction, to promote a spontaneous water flux through the microchannels, is a crucial task in microfluidic applications. For that reason, in this research, the authors study the hydrophilicity improvement induced by low‐power oxygen plasma treatments (15 W) on the polydimethylsiloxane (PDMS) microchannel. The effects of the oxygen plasma treatments on wettability and water‐work of adhesion on PDMS surfaces have been studied by sessile contact angle. The chemical composition of the plasma has been investigated by means of optical emission spectroscopy. The results indicate that the improvement of wettability on treated PDMS is led by the percentage of atomic oxygen in the plasma discharge. Super‐hydrophilic surfaces (contact angle < 5°) have been obtained optimising the atomic oxygen percentage in the plasma discharge varying only the plasma working pressure. Super‐hydrophilic PDMS microchannels show the highest spontaneous capillary flow in the channels while the hydrophilic microchannel shows only a small capillary flow.

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.

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)0.001
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 score0.023
Threshold uncertainty score0.564

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0010.000
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 head0.014
GPT teacher head0.241
Teacher spread0.227 · 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