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Record W2977661404 · doi:10.1109/tdei.2019.008099

Effect of blending and nanoclay on dielectric properties of polypropylene

2019· article· en· W2977661404 on OpenAlexaff
Mostafa Eesaee, Éric David, Nicole R. Demarquette

Bibliographic record

VenueIEEE Transactions on Dielectrics and Electrical Insulation · 2019
Typearticle
Languageen
FieldMaterials Science
TopicHigh voltage insulation and dielectric phenomena
Canadian institutionsÉcole de Technologie Supérieure
Fundersnot available
KeywordsMaterials scienceNanocompositePolypropyleneComposite materialMontmorilloniteExfoliation jointPolymer blendDielectricCopolymerMicrostructurePhase (matter)PolymerGrapheneNanotechnology

Abstract

fetched live from OpenAlex

This paper investigates the effects of organomodified montmorillonite (clay) and styrene-(ethylene-co-butylene)-styrene triblock copolymer (SEBS) on the morphological and electrical properties of polypropylene (PP). A series of binary PP-clay nanocomposites along with nanocomposites having a blend matrix were prepared. The nanofillers were found to be well-embedded into the polymeric matrix with a high degree of dispersion. The microstructure of the blend matrix revealed a co-continuous structure for the equal proportion of the two polymers. This was shown to control the localization of nanofiller by triggering them to migrate into the SEBS phase, mostly accommodating in the interface and creating a strong network which eventually resulted in more exfoliation of clay platelets and comparable/superior electrical properties comparing to binary nanocomposites. The incorporation of clay resulted in a solid-like rheological behavior which was more enhanced in blend nanocomposites due to the stronger network of nanofiller. The dielectric spectra of the nanocomposites revealed two major relaxation processes aroused by the presence of clay. A new relaxation process was observed for the nanocomposites with the blend matrix, related to the SEBS phase. Both blending and nanofiller inclusion resulted in less accumulated space charge. A significant improvement in the AC breakdown strength of PP was witnessed upon addition of clay. Despite the less inherent breakdown strength of SEBS, the blend nanocomposites showed even more enhanced breakdown properties confirming the further improvement of nanofiller network structure.

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 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 score0.046
Threshold uncertainty score0.822

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.010
GPT teacher head0.226
Teacher spread0.216 · 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

Citations6
Published2019
Admission routes1
Has abstractyes

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