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Record W4224279885 · doi:10.1155/2022/1458547

Mechanical Properties of Polymer Composites Reinforced with Alkaline-Treated Natural Fibre

2022· article· en· W4224279885 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

VenueAdvances in Polymer Technology · 2022
Typearticle
Languageen
FieldMaterials Science
TopicNatural Fiber Reinforced Composites
Canadian institutionsToronto Metropolitan University
FundersKing Saud University
KeywordsMaterials scienceComposite materialUltimate tensile strengthComposite numberModulusIzod impact strength testInjection mouldingYoung's modulusPolymer

Abstract

fetched live from OpenAlex

The mechanical characteristics of a high impact polyethylene composite (HIPC) reinforced with abaca fibre (AF) are investigated in relation to fibre loading. An alkaline behaviour was used to improve the characteristics of the abaca fibre. With a fibre length of 100 mm, five different fibre loadings of the abaca fibre were used to create the samples of the composite (25, 35, 45, 55, and 65 wt percent). The object was made using compression moulding with unidirectional fibre orientation. The influence of fibre loading was investigated using tensile, hardness, and density tests. In an experiment, it was shown that with 55 percent fibre loading, tensile strength was 312 percent higher than without, and Young’s modulus was 545 percent higher than without. While this was happening, the hardness and density of the AF/PE composites were found to be quite similar, with minor increases from 25 wt percent to 65 wt percent AF loading in comparison to the control sample’s zero wt percent AF loading. 67.42 Shore-D and 1.014 g/cm3 are the highest values. The alkaline treatment of the AF/PE composite had a substantial influence on mechanical characteristics, according to the findings.

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 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 score0.045
Threshold uncertainty score0.914

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
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 head0.006
GPT teacher head0.225
Teacher spread0.220 · 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