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Computational Insights into the Corrosion Behavior ofNbMoTaW and NbMoTaWV High-Entropy Alloys inMolten Fluoride Salts

2025· preprint· en· W4411841604 on OpenAlexafffund
Agnes Britte Katai, Arjun Varma, Conrard Giresse Tetsassi Feugmo

Bibliographic record

VenueChemRxiv · 2025
Typepreprint
Languageen
FieldEngineering
TopicHigh Entropy Alloys Studies
Canadian institutionsRegional Municipality of WaterlooUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Nuclear Safety Commission
KeywordsFluorideCorrosionMaterials scienceEntropy (arrow of time)MetallurgyThermodynamicsChemistryInorganic chemistryPhysics

Abstract

fetched live from OpenAlex

Molten salt reactors (MSRs) expose structural materials to harsh conditions, such as elevated temperatures, corrosive fluoride salts, and substantial neutron irradiation. These factors contribute to intricate degradation processes, including radiation-induced defect development, void swelling, and corrosion. Refractory high-entropy alloys with a body-centered cubic structure provide noteworthy thermal stability and mechanical strength, making them excellent candidates for MSR application. This study explores the corrosion properties of NbTaMoW and NbTaMoWV in FLiBe molten salt via density functional theory and ab initio molecular dynamics simulations. Analyses of electronic structure, including density of states and crystal orbital Hamilton population, shed light on interfacial bonding and charge distribution. NbTaMoW shows minimal d-band shifts and weak fluorine interaction, indicating enhanced oxidation resistance. Adding vanadium to form NbTaMoWV further diminishes oxidative vulnerability and stabilizes the electronic structure at the salt interface, suggesting superior corrosion resistance in molten salt conditions.

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 categoriesMeta-epidemiology (narrow)
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 score0.314
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
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 head0.009
GPT teacher head0.227
Teacher spread0.218 · 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 designSimulation or modeling
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

Citations0
Published2025
Admission routes2
Has abstractyes

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