MétaCan
Menu
Back to cohort
Record W3186883150 · doi:10.5539/apr.v13n1p42

Fracture Nucleation Phenomena and Thermally Activated Crack Dynamics in Monocrystals

2021· article· en· W3186883150 on OpenAlexvenueno aff
Leonardo Golubović, Dorel Moldovan

Bibliographic record

VenueApplied Physics Research · 2021
Typearticle
Languageen
FieldMaterials Science
TopicThermal properties of materials
Canadian institutionsnot available
Fundersnot available
KeywordsNucleationMaterials scienceFracture (geology)Growth rateGrowth theoryMonte Carlo methodStress (linguistics)Ultimate tensile strengthCondensed matter physicsChemical physicsMolecular dynamicsComposite materialMechanicsThermodynamicsChemistryComputational chemistryPhysicsGeometry

Abstract

fetched live from OpenAlex

We explore irreversible thermally activated growth of cracks which are shorter than the Griffith length. Such a growth was anticipated in several studies [Golubović, L. & Feng, S., (1991). Rate of microcrack nucleation, Physical Review A 43, 5223. Golubović, L. & Peredera, A., (1995).  Mechanism of time-delayed fractures, Physical Review E 51, 2799]. We explore this thermally activated growth by means of atomistic Monte-Carlo dynamics simulations of stressed monocrystals. This crack growth is stepwise. Each step is marked by nucleation of a microcavity close to the crack tip, and by creation of a passage connecting the microcavity and the crack. If the external tensile stress is weak, many such nucleation events occur before the crack length reaches the Griffith size. In addition to the simulations, we also present an analytic theory of the stepwise thermally activated crack growth. The theory explains surprising observation form our simulations that the thermally activated crack growth remains fairly well directed in spite of the stochastic nature of the crack growth process.

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 score0.013
Threshold uncertainty score0.905

Codex and Gemma teacher scores by category

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

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 head0.043
GPT teacher head0.309
Teacher spread0.266 · 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

Citations1
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueApplied Physics ResearchSame topicThermal properties of materialsFrench-language works237,207