Anisotropy in the crystal growth of hexagonal ice, I<i>h</i>
Bibliographic record
Abstract
Growth of ice crystals has attracted attention because ice and water are ubiquitous in the environment and play critical roles in natural processes. Hexagonal ice, I(h), is the most common form of ice among 15 known crystalline phases of ice. In this work we report the results of an extensive and systematic molecular dynamics study of the temperature dependence of the crystal growth on the three primary crystal faces of hexagonal ice, the basal {0001} face, the prism {1010} face, and the secondary prism {1120} face, utilizing the TIP4P-2005 water model. New insights into the nature of its anisotropic growth are uncovered. It is demonstrated that the ice growth is indeed anisotropic; the growth and melting of the basal face are the slowest of the three faces, its maximum growth rates being 31% and 43% slower, respectively, than those of the prism and the secondary prism faces. It is also shown that application of periodic boundary conditions can lead to varying size effect for different orientations of an ice crystal caused by the anisotropic physical properties of the crystal, and results in measurably different thermodynamic melting temperatures in three systems of similar, yet moderate, size. Evidence obtained here provides the grounds on which to clarify the current understanding of ice growth on the secondary prism face of ice. We also revisit the effect of the integration time step on the crystal growth of ice in a more thorough and systematic way. Careful evaluation demonstrates that increasing the integration time step size measurably affects the free energy of the bulk phases and shifts the temperature dependence of the growth rate curve to lower temperatures by approximately 1 K when the step is changed from 1 fs to 2 fs, and by 3 K when 3 fs steps are used. A thorough investigation of the numerical aspects of the simulations exposes important consequences of the simulation parameter choices upon the delicate dynamic balance that is involved in ice crystal growth.
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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 | 0.000 |
| 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) | 0.001 | 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".