An Investigation of Friction Coefficient on Microstructure and Texture Evolution of Interstitial-Free Steel during Warm Rolling and Subsequent Annealing
Bibliographic record
Abstract
A Ti bearing interstitial-free steel was finishing rolled in the ferrite region with and without lubrication and microstructures, mechanical properties and textures evolution during warm rolling and subsequent annealing were investigated by OM, SEM, tensile test and ODF. The results show that the surface microstructure of the as-rolled specimen without lubrication is composed of dense shear bands, while the microstructures of the central layer of the as-rolled specimen without lubrication and the whole cross section of the as-rolled specimen with lubrication are elongated ferrite. Short-time annealing can make the non-lubricated rolling sample recrystallize, but the lubricated rolling sample cannot. After complete recrystallization, the microstructure of the surface layer of the as-annealed specimen without lubrication is finer than that of the center layer of the as-annealed specimen without lubrication and the whole section of the as-annealed specimen with lubrication. The mechanical properties of as-annealed sample without lubrication change significantly in the initial annealing stage, while that of as-annealed sample with lubrication remain unchanged until the end stage of annealing. The surface layers of the as-rolled samples have strong Goss component and weak γ fibre components, while the central layers have strong γ fibre components and moderate rotated cubic components. As annealing proceeds, the Goss components of the surface layer decrease and the γ fibre components increase. The rotated cubic components in the central layer are gradually transformed into γ texture.
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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".