Exploring the Effects of Microstructure on Electrochemical Passivation of Copper Coatings for Used Fuel Containers in Canada’s Nuclear Industry
Bibliographic record
Abstract
This thesis investigates the influence of copper microstructure on electrochemical passivation performance, for the long-term storage of nuclear waste. The increasing global demand for nuclear power necessitates safe and reliable disposal strategies. The Canada-Deuterium-Uranium (CANDU) reactors and upcoming Small-Modular-Reactors (SMRs) contribute to a significant accumulation of used fuel bundles in Canada. To address this, the Nuclear Waste Management Organization (NWMO) proposes using Deep Geological Repositories (DGRs), where copper coatings on Used Fuel Containers (UFCs) are used for corrosion prevention. Through microstructural analysis and immersion tests under corrosive conditions, the corrosion performance of electrodeposited (ED(Py)-Cu), cold-sprayed (CS-AS-Cu), and oxygen-free electronic copper sheet (OFE-Cu) were compared. The passivating layer morphology was also examined under the influence of chloride and bicarbonate ions. The findings highlight the differences in corrosion behavior and passivation between different types of copper, emphasizing the importance of microstructure in designing effective corrosion prevention strategies for long-term nuclear waste storage.
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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 | 0.000 | 0.000 |
| 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".