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Record W4392699485 · doi:10.1177/14658011231212630

Effect of MAPE on the morphological, physical and mechanical properties of GTR/PP composites produced by rotational moulding

2024· article· en· W4392699485 on OpenAlexaff
Yao Dou, Denis Rodrigue

Bibliographic record

VenuePlastics Rubber and Composites Macromolecular Engineering · 2024
Typearticle
Languageen
FieldEngineering
TopicFiber-reinforced polymer composites
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsMaterials scienceComposite materialInjection mouldingRotational speedMechanical engineering

Abstract

fetched live from OpenAlex

In this work, untreated ground tire rubber (GTR) and maleated polyethylene-treated GTR (GTR/MAPE) were dry-blended with polypropylene (PP) to produce PP/GTR and PP/MAPE/GTR blends via rotational moulding. From the samples produced (0–50 wt-%), a complete characterisation including morphological, physical and mechanical properties (tensile, flexural and impact) was performed. The results showed that all the mechanical properties of PP/MAPE/GTR are below the neat PP values due to the elastomeric properties of GTR. However, the properties were significantly higher for GTR/MAPE compared to neat GTR. For example, the tensile modulus and tensile strength increased by up to 57% and 76%, respectively. Similarly, the flexural modulus and impact strength were improved by up to 74% and 52%, respectively. These results indicated that successful rotomoulding of these blends was achieved with good mechanical properties for the range of parameters studied.

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 score0.004

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 head0.004
GPT teacher head0.182
Teacher spread0.178 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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