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Record W4311723510 · doi:10.3390/jcs6120373

Mechanical, Thermal, and Acoustic Properties of Hemp and Biocomposite Materials: A Review

2022· review· en· W4311723510 on OpenAlexaff
Raj Kumar Dahal, Bishnu Acharya, Animesh Dutta

Bibliographic record

VenueJournal of Composites Science · 2022
Typereview
Languageen
FieldMaterials Science
TopicNatural Fiber Reinforced Composites
Canadian institutionsUniversity of SaskatchewanUniversity of Guelph
Fundersnot available
KeywordsBiocompositeMaterials scienceComposite materialThermal conductivityComposite numberThermal

Abstract

fetched live from OpenAlex

Bio-based products are paving a promising path towards a greener future and helping win the fight against climate change and global warming mainly caused by fossil fuel consumption. This paper aims at highlighting the acoustic, thermal, and mechanical properties of hemp-based biocomposite materials. Change in sound absorption as a result of hemp fibers and hemp particle reinforcement are discussed in this paper. The thermal properties characterized by the thermal conductivity of the composites are also presented, followed by the mechanical properties and the current issues in biocomposite materials mainly containing hemp as a constituent element. Lastly, the effects of biofillers and biofibers on the various properties of the hemp-composite materials are discussed. This paper highlights the development of and issues in the field of hemp-based composite materials.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.002

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 head0.048
GPT teacher head0.306
Teacher spread0.258 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations53
Published2022
Admission routes1
Has abstractyes

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