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Record W4405232582 · doi:10.4271/2024-01-5238

Effect of Silicon Carbide Addition and Jute Fiber Surface Treatment on Functional Qualities of Low-Density Polyethylene Composites

2024· article· en· W4405232582 on OpenAlexaff
R. Venkatesh, Gopal Kaliyaperumal, S. Manivannan, S. Karthikeyan, N. Aravindan, V. Mohanavel, Manzoore Elahi M. Soudagar, N. Karthikeyan

Bibliographic record

VenueSAE technical papers on CD-ROM/SAE technical paper series · 2024
Typearticle
Languageen
FieldMaterials Science
TopicNatural Fiber Reinforced Composites
Canadian institutionsHorizon College and Seminary
Fundersnot available
KeywordsMaterials scienceLow-density polyethyleneComposite materialComposite numberUltimate tensile strengthSilicon carbideFlexural strengthPolyethyleneFiberPolymerAdhesive

Abstract

fetched live from OpenAlex

<div class="section abstract"><div class="htmlview paragraph">In the modern era, advanced hybrid polymer-based composites have the potential to replace conventional polymers and exhibit unique behaviour. This study focuses on low-density polyethylene (LDPE) hybrid composite made with jute fiber and enhanced with nano silicon carbide particles through the injection moulding process. The natural jute fiber undergoes chemical surface treatment to improve its adhesive behaviour. The study evaluates the effects of 10wt% chemically treated jute fiber and 1, 3, and 5wt% of SiC on the structural, impact, tensile, and flexural strength of the synthesized composites according to ASTM D7565, D3039, and D790 standards. The structural behaviour of LDPE composites is assessed through X-ray diffraction analysis, revealing improved crystalline structure and interaction. Among the five prepared composite samples, the composite containing 10wt% treated jute fiber and 5wt% SiC demonstrated enhanced impact, tensile, and flexural strength of 5.7 J/mm<sup>2</sup>, 43 MPa, and 56 MPa, respectively.</div></div>

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 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 score0.261
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.010
GPT teacher head0.253
Teacher spread0.243 · 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

Citations8
Published2024
Admission routes1
Has abstractyes

Explore more

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