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Record W2158799031 · doi:10.1088/1361-651x/aa9289

Modeling of particle coarsening and precipitation free zones

2017· article· en· W2158799031 on OpenAlex

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

VenueModelling and Simulation in Materials Science and Engineering · 2017
Typearticle
Languageen
FieldMaterials Science
TopicMicrostructure and mechanical properties
Canadian institutionsQueen's UniversityMcMaster University
Fundersnot available
KeywordsMaterials sciencePrecipitationParticle (ecology)MechanicsThermodynamicsMeteorologyGeology

Abstract

fetched live from OpenAlex

Previous simulation studies of the effect of volume fraction on the precipitate coarsening process have treated precipitates as point sources or sinks of solute atoms. These studies have demonstrated that, although the average particle size varying with time as t 1 / 3 is still valid, the coarsening rate constant is an increasing function of volume fraction. In this study we extend these simulation methods to model particle coarsening near grain boundaries. An essential feature of the new model is the solute depletion that occurs at grain boundaries. The simulation results are shown to quantitatively reproduce the following aspects of particle coarsening near grain boundaries in certain alloys: (a) precipitate free zones (PFZs) form near grain boundaries, (b) the width of PFZs increases with time and is proportional to the square root of time, (c) particles at the edge of PFZs are larger than those inside the grain. This novel model is shown to be well suited to describe particle coarsening near grain boundaries. In addition, it reinforces the credibility of the theories built into our mathematical model, i.e., the formation of PFZs near grain boundaries is caused by diffusion of solute atoms.

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)0.001
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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.287
Threshold uncertainty score0.240

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 communication0.0000.001
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 head0.034
GPT teacher head0.252
Teacher spread0.217 · 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