Analysis of the self-consistency of nucleation in the diffuse interface limit of binary alloy phase field models
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Bibliographic record
Abstract
Abstract This paper examines the process of nucleation in phase field (PF) models, with the aim of elucidating how the use of diffuse interfaces often employed for quantitative modelling of solidification affects nucleation rates and distribution statistics in relation to the predictions of classical nucleation theory. Nucleation is simulated through the use of noise in a quantitative binary alloy PF model using different interface widths. Our results reveal that the rate of nucleation in the PF model is found to be strongly dependent on the scale of the interface width and the numerical discretization, but that careful control of these quantities offers the possibility of a consistent interpretation of nucleation rate. The paper ends by assessing some of the practical merits of seeded versus noise-induced nucleation in PF modelling in the diffuse-interface limit, while also emphasizing how nucleation in this limit is fundamentally flawed from a quantitative perspective.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 it