Crystallographic Relationships between FCC and BCC Crystals: A Study Using EBSD Techniques
Bibliographic record
Abstract
The mechanisms governing the formation of transformation textures during the austenite-to-ferrite transformation are the subject of major debate. In this study, two extreme cases were examined: those of undeformed and deformed austenite. The first involves the transformation of austenite into Widmanstätten ferrite under "equilibrium" conditions in the Gibeon iron-nickel meteorite. This meteorite passed through the transformation at the rate of a few degrees per million years. Such cooling rates cannot of course be reached under laboratory conditions. The second concerns the transformation of hot rolled austenite after a quench into the bainite temperature range. These two behaviors were investigated by means of optical microscopy and electron backscatter diffraction (EBSD) techniques. The orientations of both the parent and product phases were measured and the orientation relationships are represented in Rodrigues-Frank (R-F) space. From the orientation of a particular FCC crystal, the crystallographic orientations of the product BCC crystals can be predicted according to the Bain, Kurdjumov-Sachs (K-S) and Nishiyama- Wassermann (N-W) correspondence relationships. Comparison of the predicted and measured orientations reveals that the Bain rotation is never observed; the K-S and N-W relationships are both observed and there is a continuous distribution of orientations between the exact K-S and N-W positions. The formation of preferred orientations under non-equilibrium conditions is scrutinized. These results are compared to recent models accounting for variant selection.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".