Crystal growth investigations of ice/water interfaces from molecular dynamics simulations: Profile functions and average properties
Bibliographic record
Abstract
Attempts to simulate crystal growth of ice from liquid water and to provide a consistent microscopic description of this process have been challenging tasks. In this paper we have adapted our previously developed molecular dynamics simulation methodology to enable the investigation of steady-state directional crystal growth∕melting of ice. Specifically, we examine ice∕water systems of the (001), (110), and (111) faces of ice Ic and the (0001), (1010), and (1120) faces of ice Ih, where the TIP4P, TIP4P-Ew, and SPC∕E water models have been utilized. The influence of different growth∕melting conditions (temperature gradients and growth velocities) is investigated. Profile functions of properties of interest across the interface are obtained from nonequilibrium steady-state simulations and provide consistent descriptions of ice∕water interfaces. The widths of the various crystallographic faces are found to increase in the apparent order Ic111, Ih0001 < Ih1010 < Ih1120 < Ic001 < Ic110. The observed growth rates were in agreement with experimental values and the possible dependence on the various faces is explored. The melting temperatures obtained with the present methodology for the different models are in good agreement with estimates from other work.
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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 | 0.001 |
| 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".