Name: water ice PNAS 2021
License: CC-BY-SA-4.0

Dataset

water_ice_PNAS_2021

Download Original Data Files 13.3 MB

Download Dataset Parquet Files 47.9 MB

Download Dataset XYZ Files 67.5 MB

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Species content of dataset

Name :

water_ice_PNAS_2021

Authors :

Christoph Schran, Fabian L. Thiemann, Patrick Rowe, Erich A. Müller, Ondrej Marsalek, Angelos Michaelides

Description :

Dataset generated using a committee-based active learning strategy to build a training dataset for modeling complex aqueous systems.

DOI :

https://doi.org/10.60732/07d278f0 https://commons.datacite.org/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.

ColabFit ID :

DS_mz0vl4zs7bex_0

Extended ID :

water_ice_PNAS_2021__Schran-Thiemann-Rowe-Muller-Marsalek-Michaelides__DS_mz0vl4zs7bex_0

Date Added :

2023-10-30

License :

CC-BY-SA-4.0

Downloads :

Num. Configurations :

1,786

Num. Atoms :

681,912

Calculated Property Types :

atomic_forces 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%)

Methods :

DFT-optB88-vdW DFT-PBE+D3 DFT-revPBE0+D3 DFT-BLYP+D3

Software :

CP2K

Publication Link :

https://doi.org/10.1073/pnas.2110077118

Data Source Link :

https://doi.org/10.5281/zenodo.5235246

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