String-like collective motion and diffusion in the interfacial region of ice
Bibliographic record
Abstract
We investigate collective molecular motion and the self-diffusion coefficient Ds of water molecules in the mobile interfacial layer of the secondary prismatic plane (112¯0) of hexagonal ice by molecular dynamics simulation based on the TIP4P/2005 water potential and a metrology of collective motion drawn from the field of glass-forming liquids. The width ξ of the mobile interfacial layer varies from a monolayer to a few nm as the temperature is increased towards the melting temperature Tm, in accordance with recent simulations and many experimental studies, although different experimental methods have differed in their precise estimates of the thickness of this layer. We also find that the dynamics within this mobile interfacial ice layer is “dynamically heterogeneous” in a fashion that has many features in common with glass-forming liquids and the interfacial dynamics of crystalline Ni over the same reduced temperature range, 2/3 < T/Tm < 1. In addition to exhibiting non-Gaussian diffusive transport, decoupling between mass diffusion and the structural relaxation time, and stretched exponential relaxation, we find string-like collective molecular exchange motion in the interfacial zone within the ice interfacial layer and colored noise fluctuations in the mean square molecular atomic displacement 〈u2〉 after a “caging time” of 1 ps, i.e., the Debye-Waller factor. However, while the heterogeneous dynamics of ice is clearly similar in many ways to molecular and colloidal glass-forming materials, we find distinct trends between the diffusion coefficient activation energy Ea for diffusion Ds and the interfacial width ξ from the scale of collective string-like motion L than those found in glass-forming liquids.
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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) | 0.000 | 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 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".