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Record W2991248136 · doi:10.1002/app.48648

Heterogeneous method of chitosan film preparation: Effect of multifunctional acid on film properties

2019· article· en· W2991248136 on OpenAlexafffund
Joseph Khouri, Alexander Penlidis, Christine Moresoli

Bibliographic record

VenueJournal of Applied Polymer Science · 2019
Typearticle
Languageen
FieldMaterials Science
TopicNanocomposite Films for Food Packaging
Canadian institutionsUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsCitric acidThermogravimetric analysisChitosanUltimate tensile strengthMaterials sciencePlasticizerThermal stabilityContact angleGlass transitionChemical engineeringPolymer chemistryNuclear chemistryComposite materialPolymerChemistryOrganic chemistry

Abstract

fetched live from OpenAlex

ABSTRACT The heterogeneous crosslinking method was applied to chitosan films with citric acid to observe and understand the effect of a multifunctional acid at a low concentration on film properties. Neat and neutralized chitosan films and films containing 15% (w/w) citric acid (denoted as CA films) were characterized by mechanical, water vapor permeability (WVP), and thermogravimetric analysis tests. The CA films displayed a higher tensile strength by 10%, lower WVP by 30%, and higher thermal stability, compared to neutralized films. The crystalline structure converted back from tendon to Type II after the addition of citric acid, as determined by X‐ray diffraction. Neat films displayed a lower water contact angle (72°) compared to neutralized and CA films (78°–79°). The heterogeneous method was also applied to incorporate a plasticizer into a neutralized film to potentially observe the glass transition using dynamic mechanical analysis. © 2019 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2020 , 137 , 48648.

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)0.001
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 score0.004
Threshold uncertainty score0.545

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 head0.009
GPT teacher head0.262
Teacher spread0.253 · 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

Citations22
Published2019
Admission routes2
Has abstractyes

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