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Development of a novel flax soy-based polyurethane prepreg composite

2024· article· en· W4392658894 on OpenAlexafffund
A. Belzile, Franco Armanasco, Leonel Matías Chiacchiarelli, Gilbert Lebrun, Édu Ruiz

Bibliographic record

VenueComposites Part A Applied Science and Manufacturing · 2024
Typearticle
Languageen
FieldMaterials Science
TopicNatural Fiber Reinforced Composites
Canadian institutionsUniversité du Québec à Trois-RivièresPolytechnique Montréal
FundersNational Research Council CanadaNatural Sciences and Engineering Research Council of Canada
KeywordsMaterials scienceComposite materialComposite numberUltimate tensile strengthFlexural strengthPolyurethaneCuring (chemistry)Glass fiberIzod impact strength testMicrostructure

Abstract

fetched live from OpenAlex

High performance composite materials are mostly synthesized from non-renewable resources with a detrimental environmental impact. In this work an innovative flax fiber-reinforced soy-based polyurethane composite prepreg was developed from a soy-based polyol crosslinked with glycerin and isocyanate. The flax reinforcement was manufactured by binding unidirectional flax strings with short flax fibers. Composite prepregs were fabricated using a three rolls mill and oven pre-curing to obtain a beta stage. Vacuum assisted molding was used to manufacture laminates with a fiber volume fraction up to 41 %. Electron beam and optical microscope images of the composite cross-section indicated an adequate microstructure. Tensile strength (209 MPa), flexural strength (231 MPa), and short beam shear strength (25 MPa) demonstrated that the composites had good specific mechanical properties comparable with composites containing glass fibers studied in previous works, while having a significantly lower expected environmental impact. These properties demonstrate the appropriateness of the eco-responsible composite material.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.000
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.020
GPT teacher head0.254
Teacher spread0.234 · 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 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

Citations6
Published2024
Admission routes2
Has abstractyes

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Same venueComposites Part A Applied Science and ManufacturingSame topicNatural Fiber Reinforced CompositesFrench-language works237,207