Driving force induced transition in thermal behavior of grain boundary migration in Ni
Why this work is in the frame
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Bibliographic record
Abstract
Grain boundary (GB) migration exhibits intriguing antithermal behavior (or non-Arrhenius behavior), with the temperature and driving force playing crucial roles. Through atomistic simulations on nickel bicrystals, we investigate the change in GB mobility with variations in both temperature and driving force. Our results reveal that the GB mobility initially increases with temperature and subsequently decreases after reaching the transition temperature (${T}_{\mathrm{trans}}$), and, notably, ${T}_{\mathrm{trans}}$ exhibits a linear relationship with the activation energy ($Q$) associated with GB migration. By modulating the driving force, we found that the driving force could effectively lower $Q$, resulting in the shift of ${T}_{\mathrm{trans}}$ towards lower temperatures. Additionally, higher driving forces were found to activate more migration modes at lower temperatures, potentially leading to a transition in the thermal behavior of GB migration. Our work supports the existing theoretical models for GB migration based on both classical thermal activation and disconnection nucleation. Furthermore, we refined the existing model by incorporating the influence of the driving force. The modified model can not only describe the effect of driving force on the thermal behavior of GB migration but also accounts for the observed ``antidriving force'' phenomenon in GB migration. Our research has the potential to offer valuable insights for investigating realistic GB migration under more intricate constraints and environments.
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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 | 0.001 | 0.000 |
| 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) | 0.000 | 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