The Role of Alloying Elements on the Crevice Corrosion Behavior of Ni-Cr-Mo Alloys
Bibliographic record
Abstract
The roles of the alloying elements Mo, Cr, and W in resisting crevice corrosion of UNS N06022, UNS N06625, and UNS N10362 have been studied under galvanostatic conditions in 5 mol/L NaCl at 150°C. Corrosion damage patterns were investigated using surface analytical techniques such as scanning electron microscopy and optical imaging, and the corrosion products characterized by energy dispersive x-ray spectroscopy. While the Cr content of the alloy is critical in controlling initiation of crevice corrosion, the rate of activation (passive-to-active transition) is influenced by both the Cr and the Mo (and W) contents. The alloy’s Mo content also determines the distribution of corrosion damage within the crevice. In alloys with high Mo content, corrosion propagates laterally across the surface, while in alloys with low Mo content, it penetrates into the alloy. This can be attributed to the accumulation of molybdates (and tungstates), which stifle alloy dissolution at active sites. Thus, as the Mo content of the alloy increases in the order N06625 (9 wt% Mo) < N06022 (13 wt% Mo [3 wt% W]) < N10362 (22 wt% Mo), the depth of corrosion penetration decreases. In addition, once crevice corrosion initiates and the crevice acidifies, metal oxidation can also couple to proton reduction inside the crevice. The role of internal proton reduction in driving the crevice corrosion of these Ni alloys was found to be quite significant; greater than 50% of the corrosion damage is caused by proton reduction inside the crevice.
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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 | 0.001 | 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".