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Record W3212568467 · doi:10.1039/d1nr07363j

The role of interface on the toughening and failure mechanisms of thermoplastic nanocomposites reinforced with nanofibrillated rubber

2021· article· en· W3212568467 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueNanoscale · 2021
Typearticle
Languageen
FieldEngineering
TopicComposite Material Mechanics
Canadian institutionsUniversity of AlbertaUniversity of Toronto
FundersUniversity of TorontoWestern Canada Research GridCompute Canada
KeywordsMaterials scienceComposite materialToughnessNanocompositeNatural rubberNanofiberThermoplastic

Abstract

fetched live from OpenAlex

a nanofiber-pair atomistic scheme, and the obtained results were subsequently incorporated into the pull-out and uniaxial test simulations. The results indicate that the compatibilizer grafting results in enhanced interfacial shear strength by introducing extra chemical interactions at the interface. In particular, it was found that the compatibilizer restricts the formation and coalescence of nanovoids, resulting in enhanced toughening effects. Together, we have shown that the presence of a small amount of well-dispersed rubber nanofibrillar network whose surfaces are grafted with maleic anhydride compatibilizer can dramatically increase the toughness and alter the failure mechanisms of the nanocomposites without any deterioration in the stiffness, which is also consistent with the recent experimental observations in our lab. The interfacial failure mechanism was also investigated by monitoring the changes in the atomic concentration profiles, mean square displacement and fractional free volume. The results obtained may serve as a promising alternative for the continuum-based modeling and analysis of interfaces.

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.

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 score0.010
Threshold uncertainty score0.331

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 head0.003
GPT teacher head0.169
Teacher spread0.166 · 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