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Record W2058448149 · doi:10.1109/tdei.2013.6451357

Erosion resistance of electrospun silicone rubber nanocomposites

2013· article· en· W2058448149 on OpenAlexafffund
Shanshan Bian, Shesha Jayaram, E.A. Cherney

Bibliographic record

VenueIEEE Transactions on Dielectrics and Electrical Insulation · 2013
Typearticle
Languageen
FieldMaterials Science
TopicHigh voltage insulation and dielectric phenomena
Canadian institutionsUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMaterials scienceSilicone rubberComposite materialElectrospinningScanning electron microscopeNanocompositeNatural rubberVulcanizationFumed silicaPolymer

Abstract

fetched live from OpenAlex

This paper presents the results of an examination of the erosion resistance of two-part room temperature vulcanizing (RTV) silicone rubber (SiR) nanocomposites. The SiR composites were filled with 7 nm size fumed silica and 1.5 μm size micro-silica. Separate samples were prepared using conventional mechanical mixing and an electrospinning technique, and their erosion resistances were compared. The electrospinning technique allows for a higher volume fraction of nanofiller and micro-filler in the composites as compared to the conventional samples. The erosion resistances were tested using both an infrared-laser-based source and the ASTM D2303 standard inclined plane tracking and erosion method (IPT). The experimental results for the eroded mass, tracking voltage, and tracking time show that the erosion resistances of electrospun samples are much greater than those of conventional samples. Scanning electron microscope (SEM) images and variable tracking patterns of the conventional samples after the IPT tests suggest an improvement in the dispersion of the fillers within the electrospun samples compared to the conventional samples. Power analysis during the IPT tests also shows that more power is required to track and erode electrospun samples before sample failure occurs than is needed for conventional samples, which suggests improved bonding between the fillers and the silicone rubber matrix. These findings also are supported by the results of thermo-gravimetric analysis.

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 score0.258
Threshold uncertainty score0.954

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.221
Teacher spread0.211 · 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
Published2013
Admission routes2
Has abstractyes

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