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Publication date: May 27, 2024
In this paper, we propose an extension to the approach of [Xi, C; et al. J. Chem. Theory Comput. 2022, 18, 6878] to calculate ion solvation free energies from first-principles (FP) molecular dynamics (MD) simulations of a hybrid solvation model. The approach is first re-expressed within the quasi-chemical theory of solvation. Then, to allow for longer simulation times than the original first-principles molecular dynamics approach and thus improve the convergence of statistical averages at a fraction of the original computational cost, a machine-learned (ML) energy function is trained on FP energies and forces and used in the MD simulations. The ML workflow and MD simulation times (≈200 ps) are adjusted to converge the predicted solvation energies within a chemical accuracy of 0.04 eV. The extension is successfully benchmarked on the same set of alkaline and alkaline-earth ions. The record includes all molecular-dynamics trajectories, energies and forces used to obtain the solvation energies of alkaline and alkaline-earth ions in water, as reported in Table 2 of referenced paper.
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File name | Size | Description |
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data.zip
MD5md5:29b2e63064a167602ffde561df889df6
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2.5 GiB | For each system (water cluster, Li, Na, ...), the LAMMPS MD trajectory, energies and forces are provided. See detailed description in README.txt. |
README.txt
MD5md5:4e3717bad64e1d6f49da299b4007dc72
|
384 Bytes | README file. |
2024.80 (version v1) [This version] | May 27, 2024 | DOI10.24435/materialscloud:a0-jh |