Applying state‐of‐the‐art microscopy techniques to understand the degradation of copper for nuclear waste canisters
Bibliographic record
Abstract
Abstract The metallurgy, mechanical properties, and corrosion of Cu, proposed as the corrosion barrier for Canadian used fuel containers (UFCs) for use in a deep geological repository (DGR), have been studied for decades. Bulk properties have been reported, and the knowledge applied to strengthen the performance of Cu produced by electrodeposition and cold spray. Despite this success, many degradation mechanisms are unclear from bulk testing, which cannot capture nanoscale phenomena driving degradation. This study provides examples using state‐of‐the‐art microscopy to understand mechanisms of Cu degradation, specifically for UFCs. Subtle changes in the electrodeposited Cu microstructure due to oxygen segregation are observed using atom probe tomography (APT). In aggressive sulfide‐containing environments, corrosion of the cold‐sprayed Cu occurs along particle–particle interfaces, likely inherent to the manufacturing process. Microscale tensile testing at particle–particle interfaces confirms brittle cracking in the cold‐sprayed Cu. Although experiments are not consistent with DGR conditions, results do warrant further study on the performance of the cold‐sprayed Cu in particular.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".