Effect of nitrogen content on corrosion behavior of high-nitrogen austenitic stainless steel
Bibliographic record
Abstract
Abstract A series of electrochemical tests combined with the techniques of scanning electron microscopy (SEM), electron backscatter diffraction (EBSD) and X-ray photoelectron spectroscopy (XPS) were used to study the effect of nitrogen content on the composition, structure and protectiveness of passive films, which were formed on the surfaces of high-nitrogen austenitic stainless steels (HNSS) in 0.5 mol/L NaCl solution. The results showed that the HNSS with higher nitrogen content had a larger proportion of low-angle grain boundaries, and it also had a lower corrosion current density in 0.5 mol/L NaCl solution and thus a lower corrosion rate. The existence of a larger proportion of stable oxides (e.g., Cr 2 O 3 ) in the passive films facilitates the passivation/repassivation process and contributes to the high corrosion resistance of HNSS.
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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 | 0.001 |
| 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".