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Record W4281565928 · doi:10.1002/ppap.202200047

Investigation of 3‐aminopropyltrimethoxysilane for direct deposition of thin films containing primary amine groups by open‐air plasma jets

2022· article· en· W4281565928 on OpenAlexafffund
Gabriel Morand, Cédric Guyon, Pascale Chevallier, Manon Saget, Vincent Semetey, Diego Mantovani, Michaël Tatoulian

Bibliographic record

VenuePlasma Processes and Polymers · 2022
Typearticle
Languageen
FieldMaterials Science
TopicSurface Modification and Superhydrophobicity
Canadian institutionsUniversité Laval
FundersNatural Sciences and Engineering Research Council of CanadaAgence Nationale de la Recherche
KeywordsAmine gas treatingCoatingMaterials scienceDeposition (geology)PolymerizationPlasma polymerizationPolymer chemistryChemical engineeringPolyethylene glycolPlasmaChemistryNanotechnologyPolymerComposite materialOrganic chemistry

Abstract

fetched live from OpenAlex

Abstract Open‐air plasma jets are becoming increasingly popular due to easy and affordable large‐scale coating deposition on diverse substrates. However, direct deposition of primary amine groups (NH2), which are attractive as covalent anchor points for molecule grafting, remains challenging. In this study, 3‐aminopropyltrimethoxysilane (APTMS) has been directly polymerized on glass by a plasma jet. Quantification of NH2 showed that APTMS polymerization and NH2 degradation were correlated with Yasuda's parameter and that a compromise between NH2 retention and coating stability is required. Evaporation of APTMS was found to improve surface smoothness and homogeneity but was found to decrease the deposited NH2 concentration, from 3.7 ± 1.3 NH2/nm2 to three times lower. Results showed that deposited NH2 could be used as anchor points for polyethylene glycol chain immobilization.

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)0.000
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: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.027
GPT teacher head0.248
Teacher spread0.221 · 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

Citations6
Published2022
Admission routes2
Has abstractyes

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