Three-dimensional analysis of local and dominant habit planes in a lath martensitic stainless steel
Bibliographic record
Abstract
The three-dimensional (3D) morphology of lath martensite in a low-carbon 13Cr–4Ni stainless steel (CA6NM alloy) was reconstructed using large-volume Xe + plasma focused ion beam (PFIB) serial sectioning tomography in combination with electron backscatter diffraction (EBSD). This approach enabled a detailed analysis of both dominant and local habit planes (HPs), offering new insights into their spatial distribution and variation. The dominant HP, determined by averaging the normal directions of high-angle block boundaries (BBs) within packets and across multiple prior austenite grains (PAGs), was found to lie between {111}γ and {557}γ, with an orientation of (0.51,0.52,0.66)γ. However, local HP analysis at individual BBs revealed significant deviations from both orientations in certain regions of the microstructure. 3D morphological observations indicated that bending within specific blocks directly contributed to these local HP variations. It is suggested that interactions between adjacent growing blocks, either through spatial interference and growth competition within a single packet, or hard impingement between blocks from different packets, affect growth paths, ultimately leading to block bending and the macroscopic deflection of interface planes. These findings highlight the intricate interplay between microstructural evolution and crystallographic constraints during martensitic transformation, demonstrating the effectiveness of large-scale 3D characterization in capturing complex microstructural phenomena that are difficult to resolve through conventional 2D analyses.
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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 | 0.001 | 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".