MétaCan
Menu
Back to cohort
Record W3092729794 · doi:10.1126/sciadv.abb1335

Graphene fatigue through van der Waals interactions

2020· article· en· W3092729794 on OpenAlexafffund
Teng Cui, Kevin Yip, Aly Hassan, Guorui Wang, Xingjian Liu, Yu Sun, Tobin Filleter

Bibliographic record

VenueScience Advances · 2020
Typearticle
Languageen
FieldMaterials Science
TopicGraphene research and applications
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of CanadaCanada Foundation for Innovation
KeywordsGraphenevan der Waals forceMaterials sciencePolymerComposite materialNanotechnologyPhysicsMoleculeQuantum mechanics

Abstract

fetched live from OpenAlex

Graphene is often in contact with other materials through weak van der Waals (vdW) interactions. Of particular interest is the graphene-polymer interface, which is constantly subjected to dynamic loading in applications, including flexible electronics and multifunctional coatings. Through in situ cyclic loading, we directly observed interfacial fatigue propagation at the graphene-polymer interface, which was revealed to satisfy a modified Paris' law. Furthermore, cyclic loading through vdW contact was able to cause fatigue fracture of even pristine graphene through a combined in-plane shear and out-of-plane tear mechanism. Shear fracture was found to mainly initiate at the fold junctions induced by cyclic loading and propagate parallel to the loading direction. Fracture mechanics analysis was conducted to explain the kinetics of an exotic self-tearing behavior of graphene during cyclic loading. This work offers mechanistic insights into the dynamic reliability of graphene and graphene-polymer interface, which could facilitate the durable design of graphene-based structures.

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 score0.152
Threshold uncertainty score0.867

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0010.001
Scholarly communication0.0000.002
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.069
GPT teacher head0.385
Teacher spread0.316 · 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

Citations49
Published2020
Admission routes2
Has abstractyes

Explore more

Same venueScience AdvancesSame topicGraphene research and applicationsFrench-language works237,207