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Record W3015004685 · doi:10.1149/1945-7111/ab856d

Multi-Phase-Field Model of Intergranular Corrosion Kinetics in Sensitized Metallic Materials

2020· article· en· W3015004685 on OpenAlexaff
Talha Qasim Ansari, Jing‐Li Luo, San‐Qiang Shi

Bibliographic record

VenueJournal of The Electrochemical Society · 2020
Typearticle
Languageen
FieldEngineering
TopicAluminum Alloy Microstructure Properties
Canadian institutionsUniversity of Alberta
FundersResearch Grants Council, University Grants Committee
KeywordsIntergranular corrosionCorrosionMaterials scienceGrain boundaryGibbs free energyMetallurgyMetalElectrolytePhase (matter)KineticsThermodynamicsSaturation (graph theory)ChemistryPhysical chemistryMicrostructureElectrodePhysics

Abstract

fetched live from OpenAlex

Improperly heat-treated metals exhibit preferential corrosion along sensitized grain boundaries when exposed to a corrosive electrolyte. This localized corrosion process is commonly known as Intergranular Corrosion (IGC). A multi-phase-field (MPF) model is presented to quantitatively predict IGC kinetics in metallic materials. The total free energy of the system is defined in terms of chemical, gradient and electromigration energy. The system is defined by a set of phase field variables which evolve due to the minimization of Gibbs free energy of the system. The simulation results show that IGC predicted by two-dimensional MPF model agrees well with the experimental results. The model also predicts plane-direction-dependent IGC in rolled sheets, commonly observed in the experimental studies. It is also observed that the corrosion process becomes transport controlled even at lower values of applied potentials due to the saturation of the metal ions in the corroded grain boundaries region. A three-dimensional study is also presented to show the practical applications of using this MPF model for complex three-dimensional geometries.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.070
Threshold uncertainty score0.369

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 head0.014
GPT teacher head0.223
Teacher spread0.209 · 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

Citations23
Published2020
Admission routes1
Has abstractyes

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Same venueJournal of The Electrochemical SocietySame topicAluminum Alloy Microstructure PropertiesFrench-language works237,207