Bibliographic record
Abstract
As more of the world turns to nuclear energy as a source of low-carbon electricity, the demand for safe and economical nuclear materials grows. Canada has been a world leader in nuclear energy since the inception of nuclear science, and today is taking on ever more ambitious nuclear projects, including the design of small modular reactors, and the permanent disposal of nuclear waste in deep geological repositories.This document addresses the degradation methods that can affect materials used in the nuclear energy industry, both for electricity production and waste disposal. The applications and limitations of copper alloys used for nuclear energy production are discussed. This work is compiled as a paper-based thesis addressing the central theme of degradation of copper and copper alloys. As such, it is split into four individual papers, each structured in a typical journal article format. A mechanism for dealloying and intergranular attack of Monel 400, a Ni-Cu alloy used as a steam generator tubing material, is proposed. Dealloying of Monel is contingent on the accumulation of Cu2+, which stabilizes metallic copper. This is achieved in the nuclear steam generator by accumulation of corrosion products within hideout regions. The roles of steam generator impurities on the corrosion of Monel 400 are probed using electrochemical methods, and corrosion character is observed by electron microscopy and secondary ion mass spectrometry. The mechanical properties of high purity electrodeposited copper which is intended for use in the disposal of nuclear waste are evaluated. Hydrogen embrittlement was observed in electrodeposited copper. Internal hydrogen dynamics were studied using high temperature thermal desorption analysis, which provide insights into the trapping and storage of hydrogen within copper. Hydrogen embrittlement of electrodeposited copper was sensitive to both strain rate and temperature, and a mechanism of embrittlement contingent on the mobility of hydrogen is discussed.
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 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".