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Record W2772979951 · doi:10.1063/1.5010472

Thermal conductivity behavior of oil palm/jute fibre-reinforced hybrid composites

2017· article· en· W2772979951 on OpenAlexfundno aff
Mohammad Jawaid, N. Saba, Othman Y. Alothman, H. P. S. Abdul Khalil

Bibliographic record

VenueAIP conference proceedings · 2017
Typearticle
Languageen
FieldMaterials Science
TopicNatural Fiber Reinforced Composites
Canadian institutionsnot available
FundersInstitute of Population and Public HealthKing Saud University
KeywordsComposite materialMaterials scienceThermal conductivityPalm oilThermalEnvironmental scienceAgroforestry

Abstract

fetched live from OpenAlex

In this study epoxy matrix, oil palm empty fruit bunch (EFB) fibres, jute fibres and oil palm EFB/jute fibre reinforced epoxy hybrid composites in different layering pattern at EFB: jute ratio (50:50) fabricated by hand lay-up technique. The thermal conductivity of epoxy matrix, oil palm EFB, jute and oil palm EFB/jute hybrid reinforced epoxy composites has been evaluated by Hot Disk Thermal Constants Analyser (Hot Disk TPS2500 S) equipped with Hot Disk Analysis Software version 5.9. Obtained results indicated that thermal conductivity of epoxy matrix increased with reinforcing of oil palm EFB and jute fibres. Hybridization of oil palm EFB with jute fibres allows an increased in thermal conductivity of oil palm EFB/jute hybrid composites. We concluded that oil palm EFB/jute hybrid composites can be used for thermal applications in automotive and construction industry to save energy.

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 score0.008
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 studies0.0010.001
Scholarly communication0.0010.002
Open science0.0020.001
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 head0.029
GPT teacher head0.269
Teacher spread0.240 · 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

Citations9
Published2017
Admission routes1
Has abstractyes

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