Crystal structures of model lithium halides in bulk phase and in clusters
Bibliographic record
Abstract
We employ lattice energy calculations and molecular dynamics simulations to compare the stability of wurtzite and rock salt crystal structures of four lithium halides (LiF, LiCl, LiBr, and LiI) modeled using the Tosi-Fumi and Joung-Cheatham potentials, which are models frequently used in simulation studies. Both infinite crystals and finite clusters are considered. For the Tosi-Fumi model, we find that all four salts prefer the wurtzite structure both at 0 K and at finite temperatures, in disagreement with experiments, where rock salt is the stable structure and wurtzite exists as a metastable state. For Joung-Cheatham potentials, rock salt is more stable for LiF and LiCl, but the wurtzite structure is preferred by LiBr and LiI. It is clear that the available lithium halide force fields need improvement to bring them into better accord with the experiment. Finite-size clusters that are more stable as rock salt in the bulk phase tend to solidify as small rock salt crystals. However, small clusters of salts that prefer the wurtzite structure as bulk crystals tend to form structures that have hexagonal motifs, but are not finite-size wurtzite crystals. We show that small wurtzite structures are unstable due to the presence of a dipole and rearrange into more stable, size-dependent structures. We also show that entropic contributions can act in favor of the wurtzite structure at higher temperatures. The possible relevance of our results for simulation studies of crystal nucleation from melts and/or aqueous solutions is discussed.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".