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Record W2346260960 · doi:10.1002/app.43802

Effect of surface modification on the interface quality between hemp and linear medium‐density polyethylene

2016· article· en· W2346260960 on OpenAlexafffund
Désiré Yomeni Chimeni, Jean Luc Toupe, Charles Dubois, Denis Rodrigue

Bibliographic record

VenueJournal of Applied Polymer Science · 2016
Typearticle
Languageen
FieldMaterials Science
TopicNatural Fiber Reinforced Composites
Canadian institutionsPolytechnique MontréalUniversité Laval
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMaterials scienceWettingComposite materialThermogravimetric analysisPolyethyleneContact angleAdhesionRheologyScanning electron microscopeCoupling (piping)Surface modificationChemical engineering

Abstract

fetched live from OpenAlex

ABSTRACT In this work, hemp fibers (mercerized or not) were modified by a coupling agent (maleated polyethylene) to evaluate the level of interfacial improvement related to wettability or adhesion in LMDPE composites. To do so, different analyses in the solid (thermogravimetric analysis, dynamic mechanical analysis, and scanning electron microscopy) and melt (rheology) states were combined. From the results obtained, it can be shown that mercerization mostly controls the level of wettability (physical contact) of the fibers, while the addition of a coupling agent mostly controls interfacial adhesion (chemical interactions). These conclusions were obtained based on shifts in transition temperatures ( T g and T α ), as well as maxima in van Gurp–Palmen plots. Overall, the best properties were obtained when mercerization was combined with coupling agent addition under optimized processing conditions. © 2016 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2016 , 133 , 43802.

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)0.004
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.331

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.019
GPT teacher head0.318
Teacher spread0.299 · 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.

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

Citations22
Published2016
Admission routes2
Has abstractyes

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