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Record W1968160450 · doi:10.1002/app.39151

Mechanical properties and crack propagation of soy‐polypropylene composites

2013· article· en· W1968160450 on OpenAlexafffund
Barbara E. Guettler, Christine Moresoli, Leonardo C. Simon

Bibliographic record

VenueJournal of Applied Polymer Science · 2013
Typearticle
Languageen
FieldMaterials Science
TopicNatural Fiber Reinforced Composites
Canadian institutionsUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of CanadaGrain Farmers of Ontario
KeywordsComposite materialMaterials scienceAutoclaveMaleic anhydridePolypropyleneFlexural strengthComposite numberScanning electron microscopeFlexural modulusIzod impact strength testUltimate tensile strengthCopolymerPolymer

Abstract

fetched live from OpenAlex

Abstract Composites from soy flour (SF) and polypropylene (PP) exhibited increased impact and flexural properties when SF was treated with potassium permanganate (KMnO 4 ) or when subjected to autoclave treatment and maleic anhydride coupling agent addition. The impact strength increased by at least 13% for the KMnO 4 SF composites and by 18% for the autoclave SF composites with maleic anhydride coupling agent addition. These two SF composite materials showed increased impact and flexural modulus, an indication of multiscale material architecture. Scanning electron microscopy imaging of the fractured surfaces revealed different morphology and potential crack propagation mechanisms. Composites with untreated SF showed poor bonding with the polypropylene matrix whereas improved bonding was observed for SF subjected to KMnO 4 treatment. Composites with SF subjected to autoclave treatment combined with maleic anhydride revealed good bonding. © 2013 Wiley Periodicals, Inc. J. Appl. Polym. Sci., 2013

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 score0.005
Threshold uncertainty score0.363

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 studies0.0000.001
Scholarly communication0.0000.001
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 head0.013
GPT teacher head0.218
Teacher spread0.205 · 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

Citations16
Published2013
Admission routes2
Has abstractyes

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