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Record W2501591661 · doi:10.1177/096739110401200102

Effect of Processing on Ductility and Strength of Kevlar/Polyethylene Composites

2004· article· en· W2501591661 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

VenuePolymers and Polymer Composites · 2004
Typearticle
Languageen
FieldEngineering
TopicFiber-reinforced polymer composites
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsMaterials scienceComposite materialUltimate tensile strengthKevlarDuctility (Earth science)FiberPolyethyleneStrain ratePolymerAspect ratio (aeronautics)Composite numberCreep

Abstract

fetched live from OpenAlex

Polymerization-filled composites (PFC) and melt-blended composites (MBC) were prepared to compare their mechanical properties. Improved ductility was obtained for PFC resulting from better fiber-polymer interfacial adhesion. On the other hand, ductility decreased upon increasing fiber content and strain rate, while normalized strengths were almost unchanged. This indicates that matrix and composites have similar responses to strain rate. Tensile strengths were compared with several modified models to include the effect of critical fiber aspect ratio. It was found that the numerical integration model with perfect interfacial bond in combination with Rosen's method for the critical fiber aspect ratio gave the best predictions among all the models tested. The results clearly show that the preparation technique has an effect on tensile strength of composites in relation with fiber distribution and interfacial adhesion.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.050
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
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 head0.004
GPT teacher head0.207
Teacher spread0.203 · 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