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Record W3082330896 · doi:10.1002/maco.202011707

The kinetics of copper corrosion in nitric acid

2020· article· en· W3082330896 on OpenAlexaffabout
Joseph Turnbull, Ryan Szukalo, Dmitrij Zagidulin, Mark C. Biesinger, David W. Shoesmith

Bibliographic record

VenueMaterials and Corrosion · 2020
Typearticle
Languageen
FieldMaterials Science
TopicCorrosion Behavior and Inhibition
Canadian institutionsWestern University
Fundersnot available
KeywordsCopperNitric acidChemistryOxygenCorrosionDissolutionInorganic chemistryKineticsNitrateCatalysisNuclear chemistryMetallurgyMaterials science

Abstract

fetched live from OpenAlex

Abstract The strategy for the permanent disposal of high‐level nuclear waste in Canada involves sealing it in a copper‐coated steel container and burying it in a deep geologic repository. During the early emplacement period, the container could be exposed to warm humid air, which could result in the condensation of nitric acid, produced by the radiolysis of the humid air, on the copper surface. Previous studies have suggested that both nitrate and oxygen reduction will drive copper corrosion, with the nitrate reduction kinetics being dependent on the concentration of soluble copper(I) produced by the anodic dissolution of copper in the reaction with oxygen. This study focused on determining the kinetics of nitrate and oxygen reduction and elucidating the synergistic relationship between the two processes. This was investigated using corrosion potential and polarization measurements in conjunction with scanning electron microscopy and X‐ray photoelectron spectroscopy. Oxygen reduction was shown to be the dominant cathodic reaction with the oxidation of copper(I) to copper(II) by nitrate, promoting the catalytic cycle involving the reaction of copper(II) with copper to reproduce copper(I).

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 score0.002
Threshold uncertainty score0.335

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 head0.019
GPT teacher head0.237
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.

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

Citations20
Published2020
Admission routes2
Has abstractyes

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