Confinement effects on microstructure length scale selection in chill-cast stainless steel
Bibliographic record
Abstract
This study reports experimental measurements of spacing selection of confined dendrite growth in chill-cast stainless steel under transient cooling conditions. This phenomenon is also explored using phase-field simulations under non-steady state cooling conditions. Two phase-field models are employed, a ternary phase-field (PF) model where Ni and Cr are explicitly simulated, and a pseudobinary model which acts as a special case. Simulations reveal a strong finite-size dependence in the primary arm spacing (PAS) of cells and dendrites. This behavior is also observed experimentally within individual grains, where dendritic fronts evolve within parent grains that impose constraints on the solidification front. Quantifying PAS by a characteristic length λ 1 , this metric is observed to exhibit a stick–slip behavior as the front advances, which corresponds to times in the solidification of slow (or no) change in λ 1 followed by a rapid increase in λ 1 caused by a succession of cell elimination events. The statistics of cell extinction are also analyzed, finding a correlation in the statistical time between extinction events and system size. Specifically, simulations reveal that the length of time of such PAS plateaus is stochastic, exhibiting a mean time that decays approximately exponentially with system size. As system size increases, this effect diminishes and a more monotonic relation between λ 1 vs. front speed is observed, consistent with classic geometric theories.
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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 | 0.000 | 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".