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Record W4402413948 · doi:10.3390/ma17184445

Corrosion of Chromium Coating Fabricated on Zircaloy-4 Substrate

2024· article· en· W4402413948 on OpenAlexaboutno aff
Florentina Golgovici, Diana Diniași, P. Dincă, Bogdan Butoi, Ioana Demetrescu

Bibliographic record

VenueMaterials · 2024
Typearticle
Languageen
FieldMaterials Science
TopicNuclear Materials and Properties
Canadian institutionsnot available
Fundersnot available
KeywordsMaterials scienceCorrosionCoatingZirconium alloyCladding (metalworking)MetallurgyGravimetric analysisAlloyOxideAutoclaveChromiumSputteringComposite materialThin film

Abstract

fetched live from OpenAlex

In the nuclear industry, coated cladding is a topical problem and it is chosen as the near-term and most promising ATF (Accident-Tolerant Fuel) cladding concept. The main objective of this concept is to enhance the accident tolerance of nuclear power plants and accordingly, the performance of cladding is expected to be improved. This work assesses the corrosion performance of a Zircalloy-4 alloy coated with a thin chromium coating by MS (magnetron sputtering), tested under a CANDU (CANada Deuterium Uranium) reactor primary circuit simulated condition (LiOH solution, 10 MPa, 310 °C, pH = 10.5). The anticorrosive performance is evaluated by a gravimetric analysis, a metallographic analysis, X-ray diffraction, electronic microscopy, and electrochemical methods. A four times less gain mass was noticed compared to uncoated Zircaloy-4, indicating a smaller corrosion rate. The SEM micrographs illustrate that the coatings are still adherent, and they are keeping the initial morphological characteristics during the autoclaving process. A SEM cross-section analysis shows values of the thickness of the coatings between 0.8 and 1.46 µm. By XRD, the presence of Cr2O3 oxide is identified. Electrochemical testing confirms good stability and good corrosion performance of Cr coating over time under autoclave 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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
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 score0.005
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0070.002

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 head0.024
GPT teacher head0.248
Teacher spread0.224 · 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; both teacher heads agree on what is shown here.

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

Citations1
Published2024
Admission routes1
Has abstractyes

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