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Record W2045509535 · doi:10.1177/0731684413486846

Thermal transitions and temperature dependent mechanical behavior of wheat straw/talc isotactic/impact modified polypropylene composites

2013· article· en· W2045509535 on OpenAlexafffund
Mehdi Tajvidi, Arathi Mohan Sharma, Leonardo C. Simon

Bibliographic record

VenueJournal of Reinforced Plastics and Composites · 2013
Typearticle
Languageen
FieldMaterials Science
TopicNatural Fiber Reinforced Composites
Canadian institutionsUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of CanadaOntario Ministry of Agriculture, Food and Rural Affairs
KeywordsMaterials scienceComposite materialIzod impact strength testDynamic mechanical analysisFlexural strengthTalcPolypropyleneFlexural modulusTacticityWood flourUltimate tensile strengthPolymer

Abstract

fetched live from OpenAlex

Dynamic mechanical thermal analysis was used to evaluate temperature-dependent mechanical performance of wheat straw/talc polypropylene composites intended for automotive components as well as thermal properties of the produced formulations. Dynamic mechanical thermal analysis results were also correlated with impact tests and static bending test results. Isotactic and impact-modified copolymer polypropylene composites with various amounts of wheat straw or talc were prepared using extrusion followed by injection molding. Different thermal transitions as well as mechanical performance of the composites were evaluated and the effects of fiber loading, matrix type, filler type and hybridization were studied. Results indicated different mechanical behaviors of the two fillers within and between the two matrices. Modulus retention term and relative storage modulus were used as parameters defining mechanical performance at various temperatures. It was found that wheat straw composites were generally comparable to talc composites with better performance at very low or very high temperature regions. The correlations between the dynamic mechanical loss factor values at room temperature and impact strength data revealed a good relationship only for the isotactic polypropylene composites whereas statistically significant correlations were established between flexural strength and impact data for all formulations.

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)0.000
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 score0.011
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.009
GPT teacher head0.233
Teacher spread0.224 · 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.

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

Citations2
Published2013
Admission routes2
Has abstractyes

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