Oxygen-accelerated corrosion of Alloy 800 in a molten LiCl-KCl-MgCl2 eutectic mixture
Bibliographic record
Abstract
This study investigates the corrosion behavior of Alloy 800 (Fe-32Ni-21Cr) in a ternary eutectic molten salt mixture (LiCl-KCl-MgCl₂) at 350 °C and 750 °C under flowing argon (Ar) and Ar+ 1 % O₂ atmospheres. The objective is to understand the effect of minor oxygen ingress on corrosion in a relatively pure salt where corrosion had ceased. At lower temperature (350 °C), increasing exposure time in pure Ar conditions led to minimal changes in corrosion depth after 48 h, suggesting that corrosion had stopped after this time. The addition of 1 % oxygen to the gas flow resulted in only slight increases in corrosion, with larger ligaments observed on the surface and minor roughening in the cross-sectional images. Similarly, 750°C testing under pure Ar showed only grain boundary attack at 12 h, and increasing exposure time did not significantly increase the corrosion depth. However, in contrast to 350 °C testing, the addition of 1 % oxygen resulted in increased grain boundary attack and dealloying, specifically at and adjacent to grain boundaries. These findings suggest that minor oxygen ingress into a molten halide salt environment can significantly increase the corrosion rate in a short period of time at high homologous temperatures, which is relevant to practical applications of molten salts where minor oxygen ingress is a likely upset condition.
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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".