Dataset
water_ice_PNAS_2021
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| Name | water_ice_PNAS_2021 |
|---|---|
| Extended ID | water_ice_PNAS_2021__Schran-Thiemann-Rowe-Müller-Marsalek-Michaelides__DS_mz0vl4zs7bex_0 |
| Description | Dataset generated using a committee-based active learning strategy to build a training dataset for modeling complex aqueous systems. |
| Authors |
Christoph Schran Fabian L. Thiemann Patrick Rowe Erich A. Müller Ondrej Marsalek Angelos Michaelides |
| DOI |
10.60732/07d278f0
https://commons.datacite.org/doi.org/10.60732/07d278f0 https://doi.datacite.org/dois/10.60732%2F07d278f0 https://doi.org/10.60732/07d278f0 Cite as: Schran, C., Thiemann, F. L., Rowe, P., Müller, E. A., Marsalek, O., and Michaelides, A. "water ice PNAS 2021." ColabFit, 2023. https://doi.org/10.60732/07d278f0. For other citation formats, see the DataCite Fabrica page for this dataset. |
| Calculated Property Types |
atomic_forces cauchy_stress energy |
| Elements |
B (6.27%) C (12.97%) F (0.04%) H (39.05%) Mo (2.24%) N (6.27%) O (25.65%) S (4.53%) Ti (2.98%) |
| Number of Configurations | 1,786 |
| Number of Atoms | 681,912 |
| Links |
https://doi.org/10.5281/zenodo.5235246 https://doi.org/10.1073/pnas.2110077118 https://github.com/water-ice-group/simple-MLP |
| Configuration Sets by Name |
hexagonal_boron_nitride_nanotubes_water — Simulations of water confined in hexagonal boron nitride nanotubes carbon_nitride_nanotubes_water — Simulations of water confined in carbon nitride nanotubes fluoride_water — Simulations of fluoride ions in water molybdenum_disulphide_water — Simulations of water confined within molybdenum disulphide sulphate_water — Simulations of sulphate ions in water rutile_titaniom_dioxide_water — Simulations of water on a rutile titanium dioxide surface |
| Configuration Sets by ID |
CS_10l1mwswpaob_0 CS_3zyz2q9586gy_0 CS_co46bvkm7yib_0 CS_g54fkz9n30cq_0 CS_ls96j285ay32_0 CS_ydfozcry0l9t_0 |
| Calculated Properties | |
| ColabFit ID | DS_mz0vl4zs7bex_0 |
| Files | colabfitspec.json |
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