Texture Evolution of a 2.8 wt% Si Non-Oriented Electrical Steel during Hot Band Annealing
Bibliographic record
Abstract
To optimize the magnetic properties of non-oriented electrical steels, it is necessary to carefully control all the stages of thermomechanical processing during the production of the steel sheets, since the microstructure and crystallographic texture at an early step will usually affect those at the subsequent steps.Many studies have shown that hot band annealing may have a positive effect on the texture of the final sheet, but it is not clear what are the optimal annealing conditions to obtain the desired final textures.In this study, the evolution of microtexture and microstructure of a 2.8 wt% Si non-oriented electrical steel during hot band annealing is studied by using electron backscatter diffraction (EBSD) techniques.A region of the hot-rolled sample was marked by micro-indents so that the same area could be examined at various annealing times (under the same temperature) to investigate the evolution of the microstructure and microtexture during recrystallization.In this way, the mechanisms of texture evolution was elucidated, and optimal annealing conditions can be determined.
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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".