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Record W2030711893 · doi:10.1002/polb.23351

Polyaniline‐tailored electromechanical responses of the silver/epoxy conductive adhesive composites

2013· article· en· W2030711893 on OpenAlexafffund
Sarang P. Gumfekar, Behnam Meschi Amoli, Alex Chen, Boxin Zhao

Bibliographic record

VenueJournal of Polymer Science Part B Polymer Physics · 2013
Typearticle
Languageen
FieldMaterials Science
TopicConducting polymers and applications
Canadian institutionsUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMaterials sciencePolyanilineComposite materialEpoxyAdhesiveElectrical conductorConductive polymerElectrical resistivity and conductivityPolymer

Abstract

fetched live from OpenAlex

ABSTRACT In this article, the electromechanical properties of silver‐in‐epoxy conductive adhesives with the polyaniline (PANI) micron particles as cofillers have been investigated. PANI is a conductive polymer and has a moderate conductivity in between those of silver and epoxy. It was found that PANI can be used to tailor both the adhesive's electrical contact resistance and its relaxation behavior; however, the effects of adding PANI were complex. The addition of small amount of PANI (2 wt %) dramatically increased the contact resistance; it might block the electrical contacts among silver flakes and was not able to form a continuous path among themselves. The addition of more PANI showed a moderate increase in contact resistance, which increased with the weight fraction of PANI from 6 to 15 wt %. Interdependent behavior of compressive strain and relaxation in electrical contact resistance is characterized to evaluate the origin of this relaxation. The addition of PANI made the relaxation in electrical contact resistance more sensitive to the compressive strain and the electromechanical coupling to deviate from the linear relationship. These research findings provide insights into the way to use PANI to tailor the electromechanical properties of the adhesive bonds or joints in the development of advanced functional devices. © 2013 Wiley Periodicals, Inc. J Polym Sci Part B: Polym Phys, 2013, 51, 1448–1455

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 score0.005
Threshold uncertainty score0.749

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.002
Scholarly communication0.0000.001
Open science0.0020.000
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 head0.022
GPT teacher head0.270
Teacher spread0.247 · 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

Citations5
Published2013
Admission routes2
Has abstractyes

Explore more

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