In Situ Investigation of Microscale Deformation Mechanisms of Individual Phases in Silicon Stainless Steel with Varied Si Content
Bibliographic record
Abstract
This research aims to understand the influence of silicon content (1.79 and 6.06 wt% Si) on the microscale deformation behavior of stainless steels for potential cryogenic applications, by means of in situ tensile testing within a scanning electron microscope. The investigation focuses on how silicon‐induced solid solution strengthening and ferrite phase stabilization affect mechanical response through strain partitioning between γ‐austenite and δ‐ferrite phases. As the silicon content increases, the microstructure transforms from a single‐phase γ to a dual‐phase microstructure comprising both γ and δ. Quantitative analysis of local misorientation, image quality, and deformed volume fraction reveals that the δ‐phase in the high‐silicon alloy exhibits delayed slip line formation and higher resistance to plastic deformation. This is further supported by nanohardness measurements, where the γ and δ phases in the high‐silicon alloy show significantly higher values (6.06% Si, γ ≈ 3.4 GPa; δ ≈ 4.96 GPa) compared to the γ‐phase in the low‐silicon alloy (1.79% Si, γ ≈ 2.7 GPa). Orientation mapping and misorientation profiles indicate that deformation occurs through heterogeneous mechanisms, including both slip and twinning, providing critical insights into the strain partitioning behavior and texture evolution in stainless steels.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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) | 0.000 | 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 teacher head, 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".