Analysis of Corrosion of Hastelloy-N, Alloy X750, SS316 and SS304 in Molten Salt High-Temperature Environment
Bibliographic record
Abstract
Nickel superalloy Hastelloy-N, alloy X-750, stainless steel 316 (SS316), and stainless steel 304 (SS304) are among the alloys used in the construction of molten salt reactor (MSR). These alloys were analyzed for their corrosion resistance behavior in molten fluoride salt, a coolant used in MSR reactors with 46.5% LiF+ 11.5% NaF+ 42% KF. The corrosion tests were run at 700 °C for 100 h under the Ar cover gas. After corrosion, significant weight loss was observed in the alloy X750. Weight loss registered in SS316 and SS304 was also high. However, Hastelloy-N gained weight after exposure to molten salt corrosion. This could be attributed to electrochemical plating of corrosion products from other alloys on Hastelloy-N surface. SEM–energy-dispersive X-ray spectroscopy (EDXS) scans of cross-section of alloys revealed maximum corrosion damage to the depth of 250 µm in X750, in contrast to only 20 µm on Hastelloy-N. XPS wide survey scans revealed the presence of Fe, Cr, and Ni elements on the surface of all corroded alloys. In addition, Cr clusters were formed at the triple junctions of grains, as confirmed by SEM–EBSD (Electron Back Scattered Diffraction) analysis. The order of corrosion resistance in FLiNaK environment was X750 < SS316 < SS304 < Hastelloy-N.
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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".