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Record W3203738203 · doi:10.3390/polym13193444

Implementation and Characterization of a Laminate Hybrid Composite Based on Palm Tree and Glass Fibers

2021· review· en· W3203738203 on OpenAlexaff
Hamid Kaddami, F.Z. Arrakhiz, Oumaima Hafs, Taha El Assimi, Lamia Boulafrouh, El‐Houssaine Ablouh, Mohamed El Mansori, Hicham Banouni, Said Bouzit, Fouad Erchiqui, K. Benmoussa

Bibliographic record

VenuePolymers · 2021
Typereview
Languageen
FieldMaterials Science
TopicNatural Fiber Reinforced Composites
Canadian institutionsUniversité du Québec en Abitibi-Témiscamingue
Fundersnot available
KeywordsMaterials scienceComposite materialGlass fiberThermosetting polymerFlexural strengthUltimate tensile strengthComposite numberTransfer moldingCompression moldingFiberMolding (decorative)Polyester resinNatural fiberPolyesterMold

Abstract

fetched live from OpenAlex

In this work, laminated polyester thermoset composites based on palm tree fibers extracted from palms leaflets and glass mats fibers were manufactured to develop hybrid compositions with good mechanical properties; the mixture of fibers was elaborated to not exceed 25 vol.%. Samples were prepared with a resin transfer molding (RTM) method and mechanically characterized using tensile and flexural, hardness, and impact tests, and ultrasonic waves as a non-destructive technique. The water sorption of these composite materials was carried out in addition to solar irradiation aging for approximately 300 days to predict the applicability and the long-term performance of the manufactured composites. Results have shown that the use of glass fibers significantly increased all properties; however, an optimum combination of the mixture could be interesting and could be developed with less glass sheet and more natural fibers, which is the goal of this study. On the other hand, exposure to natural sunlight deteriorated the mechanical resistance of the neat resin after only 60 days, while the composites kept high mechanical resistance for 365 days of exposure.

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: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.866
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 studies0.0000.000
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 head0.017
GPT teacher head0.297
Teacher spread0.279 · 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 designOther design
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

Citations6
Published2021
Admission routes1
Has abstractyes

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