Analysis and Differentiation of Uniform and Localized Corrosion of Cu
Bibliographic record
Abstract
The current plan for disposal of used nuclear fuel in Canada involves sealing the waste in steel containers coated with 3 mm of copper and burying them in a deep geologic repository (DGR). The purpose of the copper coating is to provide corrosion resistance. To achieve long term containment, it is necessary that the copper layer corrodes slowly and predictably via active dissolution rather than passivating due to film formation. Film formation could allow pitting corrosion to occur in early phase repository conditions when groundwater ions such as Cl– , SO4 2– and HCO3 – play a dominant role in influencing copper`s corrosion behaviour. The tendency of copper to undergo active dissolution was tested by immersing a piece of copper in a variety of solutions with different combinations of Cl– , SO4 2– and HCO3 – ions at various concentrations and temperatures while observing the electrochemical behaviour. It was found that in most scenarios active dissolution was the preferred corrosion process. While active dissolution is favoured under DGR conditions, the distribution of corrosion damage in the form of surface roughening needs to be elucidated if an acceptable corrosion allowance is to be specified. Corroded copper surfaces were examined using a combination of optical microscopy and confocal laser scanning microscopy (CLSM). Multielectrode arrays (MEA’s) were designed to simulate copper surfaces. Copper coupons were tested using galvanostatic charging or immersion in Cl– -based solutions to determine the surface roughening pattern. Using this information, an oxidizing solution was designed which could buffer the potential of the system without externally controlling the potential or current. This solution also replicated the roughening damage observed in both the galvanostatic charging and immersion experiments. This created a link between accelerated and non-accelerated testing. This solution was then used to roughen the MEA electrodes. It was found that roughening of copper surfaces in Cl– -based solutions proceeds via preferential dissolution of different grains. The depth of metal dissolution was increased or limited depending on the grain orientation of the reactive surfaces present in the copper. Therefore, corrosion of used fuel containers in the DGR will be limited by the grain structure of their copper coating.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".