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Record W3098966378

A Three-Dimensional Atomistic Kinetic Monte Carlo Study of Dynamic Solute-Interface Interaction

2016· article· en· W3098966378 on OpenAlexaff
Aulia Tegar Wicaksono

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMaterials Science
TopicMaterial Dynamics and Properties
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsSolvent dragThermal diffusivityMaterials scienceMonte Carlo methodKinetic energyKinetic Monte CarloDragThermodynamicsInterface (matter)DiffusionPhenomenological modelStatistical physicsChemical physicsPhysicsClassical mechanicsCondensed matter physics
DOInot available

Abstract

fetched live from OpenAlex

Abstract. A three-dimensional atomistic Kinetic Monte Carlo model was developed and used to study the interaction between mobile solutes and a migrating interface. While the model was developed with a simplified energetic and topological description, it was also constructed to capture, in the absence of solute, the Burke-Turnbull model for interface migration and, in the presence of solutes, solute segregation to different types of interface sites. After parameterizing the model, simulations were performed to study the relationship between average interface velocity and imposed driving pressure for varying solute concentration and solute diffusivity. While the effect of solute concentration on solute drag pressure was found to be consistent with classical solute drag models, the effect of solute diffusivity was found to give a response not captured by either continuum or previously reported two-dimensional atomistic models. The dependence of maximum drag pressure on solute diffusivity was observed and attributed to the coupling between the structure of a migrating interface and the ability for solute to remain segregated to the interface. ar

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.543
Threshold uncertainty score0.999

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)0.0020.000

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 head0.017
GPT teacher head0.259
Teacher spread0.242 · 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.

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

Citations12
Published2016
Admission routes1
Has abstractyes

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