Effect of Nitrogen Content on the Formation of Inclusions in Fe-5Mn-3Al Steels
Bibliographic record
Abstract
The effect of N content on the characteristics and formation of inclusions in the Fe-5Mn-3Al steels was investigated in this study. Two synthetic steel melts were produced by two different methods—N2 gas purging and injecting—to introduce nitrogen into the melt. The N content of steel melt varied from 2 to 54 ppm. An increase in the N content to 47 ppm (for 533N-P) and 58 ppm (for 533N-I) increased the total amount of inclusions from 13 to 64 mm−2 and from 21 to 101 mm−2, respectively. The observed inclusions were Al2O3(pure), Al2O3-MnS, AlN(pure), AlN-MnS, AlON, AlON-MnS, and MnS. When the N content was less than 10 ppm, AlN-MnS inclusions were the primary type of inclusions and they formed as solidification products. With an increase in the N content, AlN(pure) inclusions became the dominant type of inclusions as AlN was stable in the liquid steel. These findings were confirmed by thermodynamic calculations. The influence of cooling rate on the types of inclusions was studied and a higher number of AlN-MnS inclusions were observed in samples with slow cooling rate.
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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".