Interatomic potential for sodium and chlorine in both neutral and ionic states
Bibliographic record
Abstract
Molten salts could play an important role in energy storage, in the form of liquid batteries, and heat storage for solar and nuclear power. However, their widespread application is hindered by a limited understanding of the mechanisms by which they corrode metallic containers. This knowledge gap necessitates atomic-scale studies on salt-metal interactions. Molecular dynamics simulations are well suited for such research but require interatomic potential capable of accurately modeling both ionic and neutral states of salt and metal elements. Herein, we developed a moment tensor potential (MTP) with this capability, employing a small-cell training approach. The proposed MTP is compact: It is described by 449 parameters fitted on 609 configurations; 30% of these are one- or two-atom configurations. Extensive testing of our MTP points to a high-fidelity description of the structural and transport properties of solid/liquid Na, gaseous Cl, and crystalline/molten NaCl. Furthermore, we applied this MTP to calculate the standard reduction potential and solubility limit of Na in molten NaCl, achieving results that closely align with experimental and ab initio simulation data. This approach offers a robust framework for exploring the electrochemical and physical properties of molten salts across various compositions and solutes.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".