MétaCan
Menu
Back to cohort
Record W4309971504 · doi:10.1149/1945-7111/aca07e

The Effect of Temperature on Dealloying Mechanisms in Molten Salt Corrosion

2022· article· en· W4309971504 on OpenAlexafffund
Touraj Ghaznavi, S.Y. Persaud

Bibliographic record

VenueJournal of The Electrochemical Society · 2022
Typearticle
Languageen
FieldMaterials Science
TopicNanoporous metals and alloys
Canadian institutionsQueen's UniversityUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of CanadaUniversity Network of Excellence in Nuclear Engineering
KeywordsMolten saltCorrosionMaterials scienceGrain boundaryDiffusionAqueous solutionMetallurgyIsotropyChlorideMicroporous materialChemical engineeringDissolutionChemical physicsMicrostructureThermodynamicsComposite materialChemistryPhysical chemistry

Abstract

fetched live from OpenAlex

The mechanism of molten salt corrosion of Ni− and Fe-based model alloys is studied at different homologous temperatures relevant to molten salt nuclear reactor application. Dealloying of Fe and Cr occurs in molten chloride salts in the range of 350 °C–700 °C and the dealloying parting limit depends on temperature. At 350 °C, molten salt dealloying is similar to aqueous systems; surface diffusion of elemental Ni at the solid/electrolyte interface is the governing transport mechanism, and the microporous ligaments have an isotropic morphology. The high surface mobility of Ni blurs the ordinary parting limit concept, but such a limit is still present. Above 500 °C, grain boundary dealloying is prevalent; the governing mechanism is interface-controlled, but a transitional morphology evolves, signaling a role of lattice diffusion. When the temperature exceeds 600 °C, the crystal orientation of dealloyed substrates is no longer that of their parent grain, and the fairly isotropic nature of dealloying shifts to a more one-dimensional corrosion ahead of the dealloying front that indicates some kind of hybrid mechanism. At 700 °C, the dealloying threshold approaches below 22 at%, accompanied by rapid coarsening and densification of the dealloyed material due to strong influence of lattice diffusion of alloying elements.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0010.000

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 head0.004
GPT teacher head0.219
Teacher spread0.215 · 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 source (direct Gemma or distilled Codex), 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

Citations31
Published2022
Admission routes2
Has abstractyes

Explore more

Same venueJournal of The Electrochemical SocietySame topicNanoporous metals and alloysFrench-language works237,207