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Record W4412512086 · doi:10.1149/ma2025-01201329mtgabs

Corrosion Properties of Oxidized Metallic Uranium and Uranium Carbide

2025· article· en· W4412512086 on OpenAlexaboutno aff
Mercy T. Ajayi, Jeffrey D. Henderson, Dmitrij Zagidulin, David W. Shoesmith, Mehran Behazin, James J. Noël

Bibliographic record

VenueECS Meeting Abstracts · 2025
Typearticle
Languageen
FieldMaterials Science
TopicNuclear Materials and Properties
Canadian institutionsnot available
Fundersnot available
KeywordsUraniumCorrosionMaterials scienceCarbideMetallurgyMetalRadiochemistryChemistry

Abstract

fetched live from OpenAlex

The long-term strategy for nuclear waste disposal involves the isolation and containment of spent fuel in a deep geological repository (DGR). CANDU fuel pellets are made from uranium dioxide, which exhibits exceptional wasteform properties due to its remarkably low solubility under the neutral or slightly alkaline conditions expected in a DGR. However, in the early years of nuclear fuel development, some non-oxide fuel forms, such as metallic uranium or uranium carbide, were used to fuel research reactors in Canada. These legacy materials pose challenges for disposal in their current state due to their elevated reactivity, instability, and exothermic reaction with water, air, and hydrogen. These drawbacks can be alleviated, and the used fuel rendered suitable for safe disposal, by conditioning it to an oxide form before disposal. While extensive research has been performed to determine the corrosion behaviour of uranium dioxide materials, including SIMFUELs (UO2 containing non-radioactive forms of fission products) and undoped unirradiated specimens in the presence of H2O2 (a primary radiolytic oxidant) and the scavenging effect of dissolved H2 under container failure scenarios, this study investigates the composition of the oxide forms prepared from uranium carbide and the impact of H2 on their corrosion in the presence of H2O2. The composition and properties of oxide forms prepared from uranium carbide using different conditioning methods were studied using a suite of surface analytical techniques. Also, the influence of H2 on their corrosion was studied via electrochemical techniques in aqueous chloride solutions containing bicarbonate anions. The morphological characteristics of the specimens were noticeably distinct, with some structural variations attributed to their conditioning methods. The preliminary electrochemical studies showed that under Ar-sparged conditions, the corrosion potential was about -100 mV; a higher potential was observed upon H2O2 addition at a low concentration of 10-6 M, indicating further surface oxidation. In Ar/H2 (95%/5%)-sparged solution, the corrosion potential of the fuel specimen was around -450 mV before H2O2 addition. Post oxidant addition, the potential increased, which suggests that the oxidation of the fuel specimen was not suppressed by the presence of H2 at low H2O2 concentration, unlike what has been seen on CANDU fuel under the same conditions. Studies using other concentrations of H2O2 ranging from (0.1 µM to 50 µM) in the presence of H2 are ongoing to understand the influence of H2 on the fuel specimens.

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)0.000
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 score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.020
GPT teacher head0.229
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 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

Citations0
Published2025
Admission routes1
Has abstractyes

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