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Record W4402930078 · doi:10.1177/0967391120000801001

Electrical Properties of Conductive Polypyrrole-Coated Textiles

2000· article· en· W4402930078 on OpenAlexaff
Anqing Lian, Lê H. Dao, Ze Zhang, Martin W. King, Robert Guidoin

Bibliographic record

VenuePolymers and Polymer Composites · 2000
Typearticle
Languageen
FieldMaterials Science
TopicConducting polymers and applications
Canadian institutionsUniversité LavalUniversity of ManitobaHôpital Saint-François d'AssiseInstitut National de la Recherche Scientifique
Fundersnot available
KeywordsPolypyrroleElectrical conductorMaterials scienceConductive polymerElectrically conductiveComposite materialPolymerPolymerization

Abstract

fetched live from OpenAlex

Conductive polymer-coated textiles are part of a family of recently developed composite materials with potential applications in many fields. In this paper. we report the electrical properties of conductive polypyrrole-coated polyester fabrics under various experimental conditions. The properties studied include the volume and surface resistivities. as well as the broadband dielectric relative permittivity and loss index. We found that both the surface and volume resistivities of the coated textiles dropped by more than 10 orders of magnitude compared with the uncoated fabric. while the dielectric properties exhibited a strong relaxation from 5 Hz to 13 MHz. The volume resistivity of the coated materials varied between 10 1 and 10 2 Ω.m, while the surface resistivity changed from 10 2 to 10 4 Ω/square depending on the coating thickness. It was also found that their electrical properties were not affected significantly by environmental factors. such as humidity and sterilization by gamma/radiation. The conduction and relaxation mechanisms associated with these changes are discussed.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0010.000

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 head0.017
GPT teacher head0.228
Teacher spread0.210 · 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 source (direct Gemma or distilled Codex), 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
Published2000
Admission routes1
Has abstractyes

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