ELECTROCHEMICAL STUDIES SIMULATING CORROSION OF NICKEL-BASE ALLOYS IN THIN LAYERS OF PARTICULATES
Bibliographic record
Abstract
Highly corrosion-resistant, nickel-chromium-molybdenum Alloy 22 is designated for use for containment of high-level nuclear waste at the proposed Yucca Mountain Repository. At the University of Toronto and several other North American universities, background scientific studies are in progress to improve our understanding of the possible corrosion mechanisms that might affect this class of alloys. We are using less-resistant alloys, beginning with binary Ni-22CrY to study the stability of localized corrosion, such as pitting, in thin layers of moist dust. Relative humidity and temperature are controlled. The arrangement of miniature sensor electrodes (NiCr, Pt, Ag/AgCl) to carry out meaningful electrochemistry in thin layers has been optimized. Various possible pitfalls in such measurements have been identified. The effect of nitrate ion on corrosion behavior in thin layers of particulate is compared with its effect in bulk liquid environments, and the differences quantified and explained.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".