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Record W2278182730 · doi:10.1002/app.43518

Nonmonotonic piezoresistive effect in elastomeric composite films

2016· article· en· W2278182730 on OpenAlexafffund
Maxim Paliy, Tomáš Třebický, Qiuquan Guo, Brad Kobe, Natalie D. Suhan, Gilles Arsenault, Lorenzo Ferrari, Jingjing Yang

Bibliographic record

VenueJournal of Applied Polymer Science · 2016
Typearticle
Languageen
FieldEngineering
TopicAdvanced Sensor and Energy Harvesting Materials
Canadian institutionsLanxess (Canada)Western University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPiezoresistive effectMaterials scienceElastomerComposite materialComposite numberElectrical conductorCarbon blackCarbon nanotubePolymerElongationUltimate tensile strengthNatural rubber

Abstract

fetched live from OpenAlex

ABSTRACT We compared the change of electrical resistance with elongation (piezoresistive effect) in thin films made of conductive multiwalled carbon nanotubes embedded in eight different elastomers. Two distinct forms of piezoresistive effect were observed: (i) in the “monotonic” (M) case, the film resistance always increased with the applied strain; (ii) the “nonmonotonic” (NM) case showed an initial increase in the resistance, while with further elongation the resistance began to decrease. By varying the amount of nitrile and/or styrene groups in the polymer matrix one can alter the piezoresistive effect qualitatively: composites with ∼25 wt % or more of nitrile or styrene functional side groups exhibited M piezoresistance, while others, with no, or methyl side groups only, showed NM piezoresistance. Influence of the second filler (either conductive carbon black or nonconductive nanoclay) in the ternary composites on the piezoresistive effect was explored. The possibility to modify the piezoresistive behavior of the conductive elastomer composites, for example, via chemical modification of the polymeric matrix, opens up a new venue for practical applications such as diverse types of sensors and, in NM case, complex dynamical systems (bistable elements, electromechanical oscillators, etc.) in the MEMS field. © 2016 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2016 , 133 , 43518.

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 score0.011
Threshold uncertainty score0.324

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.004
GPT teacher head0.209
Teacher spread0.205 · 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

Citations3
Published2016
Admission routes2
Has abstractyes

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