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Record W2021757576 · doi:10.1002/pc.22834

Injection molded self‐hybrid composites based on polypropylene and natural fibers

2013· article· en· W2021757576 on OpenAlexaff
Aida Alejandra Pérez‐Fonseca, Jorge Ramón Robledo‐Ortíz, Francisco Javier Moscoso‐Sánchez, Denis Rodrigue, Rubén González‐Núñez

Bibliographic record

VenuePolymer Composites · 2013
Typearticle
Languageen
FieldMaterials Science
TopicNatural Fiber Reinforced Composites
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsMaterials scienceComposite materialAbsorption of waterPolypropyleneNatural fiberUltimate tensile strengthFiberFlexural strengthIzod impact strength testMolding (decorative)ThermoplasticFlexural modulusSynthetic fiber

Abstract

fetched live from OpenAlex

Self‐hybrid thermoplastic composites (combination of two fiber sizes) were obtained by injection molding using pine or agave fibers with polypropylene (PP). The effect of self‐hybridization was determined through mechanical properties and water absorption for different total fiber contents between 10 and 30% wt. The results showed that impact strength (30% of fiber) and tensile modulus (20% of fiber) were improved by self‐hybridization compared with composites formulated with only one fiber size. Flexural properties were not improved by self‐hybridization. On the other hand, the combination of two fiber sizes had no effect on the water absorption behavior of these composites. Overall, the total fiber content was found to be an important parameter with 20% being the optimum condition where self‐hybridization provides the best mechanical properties. POLYM. COMPOS., 35:1798–1806, 2014. © 2013 Society of Plastics Engineers

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 score0.046
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.005
GPT teacher head0.206
Teacher spread0.201 · 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

Citations22
Published2013
Admission routes1
Has abstractyes

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