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Record W3095517614 · doi:10.1080/02670836.2020.1839193

Effect of crystal orientation on the size effects of nano-scale fcc metals

2020· article· en· W3095517614 on OpenAlexafffund
Mahdi Bagheripoor, Robert D. Klassen

Bibliographic record

VenueMaterials Science and Technology · 2020
Typearticle
Languageen
FieldMaterials Science
TopicMicrostructure and mechanical properties
Canadian institutionsWestern University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMaterials scienceNanopillarNucleationCrystal twinningSlip (aerodynamics)Crystal (programming language)Crystal plasticityCondensed matter physicsComposite materialPlasticityGrain sizeFree surfaceDeformation (meteorology)CrystalliteCrystallographyNanostructureMechanicsNanotechnologyMetallurgyMicrostructureThermodynamics

Abstract

fetched live from OpenAlex

The present work investigates the dominant mechanisms in the plasticity of nano-sized fcc metallic samples. Molecular dynamics simulations of nanopillar compression show that plasticity always starts with the nucleation of dislocations at the free surface, and the crystal orientation affects the subsequent microstructural evolution. The Schmid factor of leading and trailing partials plays a decisive role in leading to the twinning, or slip deformation. A significant difference is observed in the strength of pillars of the same size with different orientations. The power-law equation exponent is completely dependent on the crystal orientations, and a weak or no size effect is observed in the compression of [100]- and [110]-oriented nanopillars. The observed orientation based behaviour decreases by confining the free surface.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0020.000

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 head0.005
GPT teacher head0.219
Teacher spread0.214 · 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 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

Citations5
Published2020
Admission routes2
Has abstractyes

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