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Record W2105409924 · doi:10.1103/physrevb.84.014110

Crystallization of amorphous silicon induced by mechanical shear deformations

2011· article· en· W2105409924 on OpenAlex
Ali Kerrache, Normand Mousseau, Laurent J. Lewis

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.

Bibliographic record

VenuePhysical Review B · 2011
Typearticle
Languageen
FieldEngineering
TopicMetallic Glasses and Amorphous Alloys
Canadian institutionsUniversité de MontréalRegroupement Québécois sur les Matériaux de Pointe
Fundersnot available
KeywordsMaterials scienceShear (geology)CrystallizationAmorphous solidSiliconMolecular dynamicsShear rateComposite materialShear stressInteratomic potentialAmorphous siliconCondensed matter physicsCrystalline siliconCrystallographyThermodynamicsMetallurgyRheologyPhysicsChemistryComputational chemistry

Abstract

fetched live from OpenAlex

We investigate the response of amorphous silicon ($a$-Si) to external mechanical shear deformations using classical molecular dynamics simulations and the empirical environment dependent interatomic potential [Phys. Rev. B 56, 8542 (1997)]. In agreement with previous results, we find that, at low shear velocity and low temperature, shear deformations increase disorder and defect density. At low shear and high temperature, the deformations are found to induce crystallization, demonstrating a dynamical transition associated with both shear rate and temperature. The properties of $a$-Si under shear deformations and the extent at which the system crystallizes are analyzed in terms of the potential energy difference between the sheared and nonsheared material, as well as the fraction of defects and the number of particles that possess a crystalline environment.

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 score0.274
Threshold uncertainty score0.404

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 head0.029
GPT teacher head0.248
Teacher spread0.219 · 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