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Record W4391035962 · doi:10.1016/j.ijlmm.2024.01.003

The prospects of natural fiber composites: A brief review

2024· review· en· W4391035962 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

VenueInternational Journal of Lightweight Materials and Manufacture · 2024
Typereview
Languageen
FieldMaterials Science
TopicNatural Fiber Reinforced Composites
Canadian institutionsCarleton University
Fundersnot available
KeywordsSISALKenafCoirNatural fiberBambooComposite materialMaterials scienceFiberComposite numberBiocompositeEnvironmentally friendlyBiodegradationSynthetic fiberPulp and paper industryPolymer scienceEngineeringChemistry

Abstract

fetched live from OpenAlex

This research explores natural fiber composites (NFCs) as alternatives to traditional materials such as fiberglass. By examining fibers like abaca, bamboo, banana, coir, flax, hemp, jute, kenaf, pineapple leaf (PALF), sisal, and others, we emphasize their lower weight, cost-effectiveness, competitive mechanical properties, commendable specific strength, and potential for biodegradability. NFCs offer practical and eco-friendly substitutes for conventional composite fibers in industries like construction, automotive, and packaging. The article provides a brief overview of NFCs, covering their chemical, physical, and mechanical characteristics, and highlights diverse applications. The comparative analysis underscores the potential of natural fibers as sustainable choices in various industries.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.748
Threshold uncertainty score0.988

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
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 head0.013
GPT teacher head0.301
Teacher spread0.289 · 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