Influence of Al Addition Strategy on the Microstructure of a Low‐Cr Oxide Dispersion‐Strengthened Ferritic Steel
Bibliographic record
Abstract
Herein, two kinds of Fe–9Cr–8Al oxide dispersion‐strengthened (ODS) steels (prealloyed and postalloyed) are fabricated via mechanical alloying (MA), hot isostatic pressing (HIP), and subsequent hot forging. Microstructures of the milled powder and forged bulk materials are carefully characterized. The results show that the adding sequence of Al has a significant impact on the microstructure. For the postalloyed sample (adding Al during ball milling), a dual‐phase structure composed of reticular Al‐rich regions and a steel matrix is formed in the milled powder due to the highly mismatched deformability between the Al powder and the Fe–9Cr powder during ball milling. For the prealloyed sample (adding Al prior to ball milling), Al is solid solutionized into the steel matrix before ball milling, and there is no dual‐phase structure in the milled powder. In the final bulk materials, the average grain size of the prealloyed sample is much larger than that of the postalloyed sample. Moreover, the matrix of the postalloyed sample has a bimodal grain structure consisting of coarse grains closely surrounded by fine grains, whereas the prealloyed sample has a relatively uniform distribution of coarse grains. The coarsening mechanisms of Al addition on the microstructure are also discussed.
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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".