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Record W3132389717 · doi:10.1002/pc.25981

Behavior of polyethylene composites based on hemp fibers treated by <scp>surface‐initiated</scp> catalytic polymerization

2021· article· en· W3132389717 on OpenAlexaff
Désiré Yomeni Chimeni, Adrien Faye, Denis Rodrigue, Charles Dubois

Bibliographic record

VenuePolymer Composites · 2021
Typearticle
Languageen
FieldMaterials Science
TopicNatural Fiber Reinforced Composites
Canadian institutionsNational Research Council CanadaPolytechnique MontréalUniversité LavalFPInnovations
Fundersnot available
KeywordsMaterials scienceComposite materialUltimate tensile strengthComposite numberPolyethyleneIzod impact strength testYoung's modulusPolymerizationCompoundingModulusPolymer

Abstract

fetched live from OpenAlex

Abstract In this investigation, hemp fibers were‐surface treated by ethylene polymerization grafting to determine the effect of high grafting level on the mechanical (tensile and impact) and dynamic mechanical properties of linear medium‐density polyethylene (L) composites (20%wt.) produced via melt compounding. The results showed that, comparing the treated hemp composite (L20PH) with the untreated hemp composite (L20H), the modification reduced by 44% the modified fibers composite water absorption, while increasing the elongation and tensile strength by about 197% and 14%, respectively. Moreover, due to better interfacial interactions with the matrix and the flexibility imparted by the presence of both grafted and ungrafted polyethylene (PE) onto modified hemp fibers, the corresponding composite exhibited lower density and significantly high impact resistance (about 57%) compared to the untreated hemp composite. These results were confirmed by the composites creep strain as L20PH and L maximum strain (ε max ) was respectively 18% and 42% higher compared to that of L20H, showing that L20H has the high modulus followed by L20PH and then L. The significant improvement of the modified composite flexibility, impact resistance and the limited reduction of its modulus make this material not only suitable for building and construction applications, but also in the production of packaging and automotive parts.

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 score0.007
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.013
GPT teacher head0.242
Teacher spread0.229 · 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

Citations8
Published2021
Admission routes1
Has abstractyes

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