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Record W2002978375 · doi:10.1002/app.42135

The self‐healing mechanism of an industrial acrylic elastomer

2015· article· en· W2002978375 on OpenAlexaff
Fan Fan, Jerzy A. Szpunar

Bibliographic record

VenueJournal of Applied Polymer Science · 2015
Typearticle
Languageen
FieldMaterials Science
TopicPolymer composites and self-healing
Canadian institutionsUniversity of Saskatchewan
FundersChina Scholarship Council
KeywordsMaterials scienceSelf-healingFourier transform infrared spectroscopyElastomerPolymerComposite materialRaman spectroscopyUltimate tensile strengthPolymer scienceChemical engineeringOpticsPhysics

Abstract

fetched live from OpenAlex

ABSTRACT The self‐healing materials attract a lot of attention as self‐healing ability considerably improves reliability of service and extends the life time of materials. However, the present self‐healing materials lack the mechanical strength and thus cannot be used in practical applications. The industrial elastomer (VHB 4910) is a strong polymer, which has been used as dielectric actuator. Surprisingly, we observed that VHB 4910 has autonomic self‐healing ability. As this is an acrylic polymer, we analyzed the hydrogen bonding between carbonyl and hydroxyl groups and demonstrated that this bonding and the molecular chain entanglement contributes to its self‐healing ability. The tensile test, X‐ray diffraction (XRD), Raman, and Fourier transform infrared (FTIR) spectroscopy were employed to analyze the self‐healing processes. This study provides an insight into the mechanism of self‐healing behavior and ability of VHB 4910 to recover its strength. © 2015 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2015 , 132 , 42135.

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)0.004
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 score0.017
Threshold uncertainty score0.449

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.029
GPT teacher head0.267
Teacher spread0.237 · 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

Citations17
Published2015
Admission routes1
Has abstractyes

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