Microstructure Evolution of Cold-Rolled Carbide-Free Bainite Steel Sheets During Continuous Annealing Process
Bibliographic record
Abstract
A modified carbide-free bainite (CFB) steel has been developed, building on existing alloys for compatibility with commercial continuous annealing lines (CALs), featuring a low austenitization temperature and short overaging time. The microstructural features of such candidate CFB sheets are compared with those of conventional CFB steel sheets that require higher reheating temperatures and longer overaging times. The effects of annealing parameters such as reheating temperatures and overaging temperatures on phase transformation kinetics and microstructure evolution are presented. The annealing process was simulated in a Gleeble thermomechanical processing simulator, and the microstructural characterization was carried out using XRD, SEM, and EBSD. Reconstruction of parent austenite grains from EBSD data did not reveal any variant selection, regardless of changes in the austenitization temperature, overaging temperature, or carbon content. It was observed that the V1–V2 variant pairing is the most common at the lower overaging temperature for reheating at 950 °C; however, this pairing decreases as the isothermal overaging temperature increases, with variant pairings involving low misorientation boundaries—such as V1–V4 and V1–V8—becoming more frequent. Steels with higher carbon content exhibit no significant changes in their variant pairing, regardless of variations in the austenitizing or isothermal temperatures. The XRD results show that the retained austenite fraction is reduced by increasing the isothermal transformation temperature.
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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".