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Record W2895166263 · doi:10.1016/j.matdes.2018.10.006

Atomistic and continuum modelling of stress field at an inhomogeneity in graphene

2018· article· en· W2895166263 on OpenAlexafffund
M.A.N. Dewapriya, R. K. N. D. Rajapakse

Bibliographic record

VenueMaterials & Design · 2018
Typearticle
Languageen
FieldMaterials Science
TopicGraphene research and applications
Canadian institutionsSimon Fraser University
FundersNatural Sciences and Engineering Research Council of CanadaWestern Canada Research Grid
KeywordsMolecular dynamicsMaterials scienceGrapheneContinuum hypothesisNanoscopic scaleContinuum mechanicsStress fieldAtomic unitsBoron nitrideHexagonal boron nitrideClassical mechanicsNanotechnologyPhysicsThermodynamicsFinite element methodQuantum mechanics

Abstract

fetched live from OpenAlex

The influence of an atomic inhomogeneity on the resulting stress field of a nanoscopic matrix material can be remarkably different from the corresponding continuum descriptions due to the significance of surface energy and the discrete nature of matter at the nanoscale . In this work, we conducted a comprehensive molecular dynamics study to investigate the stress field at an atomic inhomogeneity, in the form of an elliptical hole or a circular hexagonal boron-nitride inclusion, in graphene. The results show that stress concentration factor at an inhomogeneity is higher than the corresponding classical continuum solution. We estimated the surface elastic constants for a modified continuum framework using the molecular dynamics results. Comparison between the atomic simulations and the modified continuum model reveals the limitations of such continuum-based models for the two-dimensional materials. Molecular dynamics results imply that the underlying atomic structure softens the effect of inhomogeneity compared to a continuum description thus causing an amplification of the stress filed. The molecular dynamics and modified continuum solutions for stress concentration are presented in simplified forms and design charts to facilitate preliminary design of graphene-based hybrid materials .

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.057
GPT teacher head0.289
Teacher spread0.232 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations10
Published2018
Admission routes2
Has abstractyes

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