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Record W2783994504 · doi:10.1098/rsta.2017.0212

A phase-field-crystal alloy model for late-stage solidification studies involving the interaction of solid, liquid and gas phases

2018· article· en· W2783994504 on OpenAlexafffund
Nan Wang, Gabriel Kocher, Nikolas Provatas

Bibliographic record

VenuePhilosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences · 2018
Typearticle
Languageen
FieldMaterials Science
TopicSolidification and crystal growth phenomena
Canadian institutionsMcGill University
FundersCanada Research ChairsCompute Canada
KeywordsAlloyMaterials sciencePhase (matter)Field (mathematics)Stage (stratigraphy)ThermodynamicsMetallurgyChemistryPhysicsMathematicsGeology

Abstract

fetched live from OpenAlex

We present a multiphase binary alloy phase-field-crystal model. By introducing density difference between solid and liquid into a previous alloy model, this new fusion leads to a practical tool that can be used to investigate formation of defects in late-stage alloy solidification. It is shown that this model can qualitatively capture the liquid pressure drop due to solidification shrinkage in confined geometry. With an inherited gas phase from a previous multiphase model, cavitation of liquid from shrinkage-induced pressure is also included in this framework. As a unique model that has both solute concentration and pressure-induced liquid cavitation, it also captures a modified Scheil-Gulliver-type segregation behaviour due to cavitation. Simulation of inter-dendritic channel solidification using this model demonstrates a strong cooling rate dependence of the resulting microstructure.This article is part of the theme issue 'From atomistic interfaces to dendritic patterns'.

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 categoriesnone
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 score0.809
Threshold uncertainty score0.389

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 studies0.0000.001
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 head0.064
GPT teacher head0.324
Teacher spread0.260 · 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

Citations8
Published2018
Admission routes2
Has abstractyes

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