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Record W2218750618 · doi:10.1109/ceidp.2015.7352138

Influence of interface on the dielectric response, electrical and thermal conductivity of high density polyethylene based composites

2015· article· en· W2218750618 on OpenAlexafffund
C. Vanga-Bouanga, Thomas Heid, M.F. Frechétte, Éric David

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMaterials Science
TopicConducting polymers and applications
Canadian institutionsÉcole de Technologie SupérieureHydro-Québec
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMaterials scienceHigh-density polyethyleneComposite materialPolyethyleneComposite numberDielectricMicrostructurePolyanilineThermal conductivityStearic acidConductivityDispersion (optics)PolymerPolymerizationChemistry

Abstract

fetched live from OpenAlex

The influence of interface on the dielectric response, electrical and thermal conductivity of the filled high density polyethylene (HDPE) was studied. Two types of composites containing 10 wt% of polyaniline (PAni) as filler was used. It was shown that the degradation temperature of the composites is slightly lower than that of the pure matrix. The crystalline content was found to remain unchanged at 67% for all composites except in the case of HDPE/PAni core-shell structure which exhibits a slightly higher crystalline content of 75%. The presence of PAni in the composite systems contributed to the increase of the conductivity by about eight orders of magnitude for the composite when stearic acid was used as a compatibilizer. The thermal conductivity of HDPE/PAni 10 wt% films was also found to remain unchanged at 0.35 W/m.K. The microstructure study by scanning electron microscopy revealed that the stearic acid helped to achieve a reasonably good dispersion of PAni in HDPE matrix.

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)0.001
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 score0.026
Threshold uncertainty score0.211

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.027
GPT teacher head0.267
Teacher spread0.241 · 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

Citations4
Published2015
Admission routes2
Has abstractyes

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