Dataset
water_ice_JCP_2020
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| Name | water_ice_JCP_2020 |
|---|---|
| Extended ID | water_ice_JCP_2020__Schran-Brezina-Marsalek__DS_p2aaxa2vfnr6_0 |
| Description | Starting from a single reference ab initio simulation, we use active learning to expand into new state points and to describe the quantum nature of the nuclei. The final model, trained on 814 reference calculations, yields excellent results under a range of conditions, from liquid water at ambient and elevated temperatures and pressures to different phases of ice, and the air-water interface — all including nuclear quantum effects. |
| Authors |
Christoph Schran Kyrstof Brezina Ondrej Marsalek |
| DOI |
10.60732/d1024453
https://commons.datacite.org/doi.org/10.60732/d1024453 https://doi.datacite.org/dois/10.60732%2Fd1024453 https://doi.org/10.60732/d1024453 Cite as: Schran, C., Brezina, K., and Marsalek, O. "water ice JCP 2020." ColabFit, 2023. https://doi.org/10.60732/d1024453. For other citation formats, see the DataCite Fabrica page for this dataset. |
| Calculated Property Types |
atomic_forces cauchy_stress energy |
| Elements |
H (66.67%)
O (33.33%) |
| Number of Configurations | 8,814 |
| Number of Atoms | 2,304,144 |
| Publication Link | https://doi.org/10.1063/5.0016004 |
| Data Source Link | https://doi.org/10.5281/zenodo.4004590 |
| Configuration Sets by Name | |
| Configuration Sets by ID | |
| ColabFit ID | DS_p2aaxa2vfnr6_0 |
| Downloads | 14 |
| Files | colabfitspec.json |
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