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Record W2796342158 · doi:10.1126/sciadv.aao7202

Nonlinear fracture toughness measurement and crack propagation resistance of functionalized graphene multilayers

2018· article· en· W2796342158 on OpenAlexafffund
Changhong Cao, Sankha Mukherjee, Jane Y. Howe, Doug D. Perovic, Yu Sun, Chandra Veer Singh, Tobin Filleter

Bibliographic record

VenueScience Advances · 2018
Typearticle
Languageen
FieldMaterials Science
TopicGraphene research and applications
Canadian institutionsUniversity of Toronto
FundersOntario Ministry of Research and InnovationNatural Sciences and Engineering Research Council of CanadaCanada Research ChairsCanada Foundation for Innovation
KeywordsGrapheneMaterials scienceFracture toughnessComposite materialFracture mechanicsToughnessNonlinear systemFracture (geology)Nanotechnology

Abstract

fetched live from OpenAlex

). A linear fracture analysis, similar to that previously applied to other 2D materials, was also conducted and found to be inaccurate due to the nonlinear nature of the stress-strain response of functionalized graphene multilayers. A crack arresting mechanism of functionalized graphene multilayers was experimentally observed and identified as the main contributing factor for the higher fracture toughness as compared to graphene. Molecular dynamics simulations revealed that the interactions among functionalized atoms in constituent layers and distinct fracture pathways in individual layers, due to a random distribution of functionalized carbon atoms in multilayers, restrict the growth of a preexisting crack. The results inspire potential strategies for overcoming the relatively low fracture toughness of 2D materials through chemical functionalization.

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 score0.026
Threshold uncertainty score0.760

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.002
Scholarly communication0.0000.001
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 head0.026
GPT teacher head0.310
Teacher spread0.285 · 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

Citations107
Published2018
Admission routes2
Has abstractyes

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