Dataset
BOTnet_ACAC_2022_train_600K_MD
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| Name | BOTnet_ACAC_2022_train_600K_MD |
|---|---|
| Extended ID | BOTnet_ACAC_2022_train_600K_MD__Batatia-Batzner-Kovács-Musaelian-Simm-Drautz-Ortner-Kozinsky-Csányi__DS_632yputkfhpg_0 |
| Description | 500 decorrelated geometries sampled from 600 K xTB MD run. Acetylacetone dataset generated from a long molecular dynamics simulation at 300 K using a Langevin thermostat at the semi-empirical GFN2-xTB level of theory. Configurations were sampled at an interval of 1 ps and the resulting set of configurations were recomputed with density functional theory using the PBE exchange-correlation functional with D3 dispersion correction and def2-SVP basis set and VeryTightSCF convergence settings using the ORCA electronic structure package. |
| Authors |
Ilyes Batatia Simon Batzner Dávid Péter Kovács Albert Musaelian Gregor N. C. Simm Ralf Drautz Christoph Ortner Boris Kozinsky Gábor Csányi |
| DOI |
10.60732/7239a192
https://commons.datacite.org/doi.org/10.60732/7239a192 https://doi.datacite.org/dois/10.60732%2F7239a192 https://doi.org/10.60732/7239a192 Cite as: Batatia, I., Batzner, S., Kovács, D. P., Musaelian, A., Simm, G. N. C., Drautz, R., Ortner, C., Kozinsky, B., and Csányi, G. "BOTnet ACAC 2022 train 600K MD." ColabFit, 2023. https://doi.org/10.60732/7239a192. For other citation formats, see the DataCite Fabrica page for this dataset. |
| Calculated Property Types |
atomic_forces cauchy_stress energy |
| Elements |
C (33.33%) H (53.33%) O (13.33%) |
| Number of Configurations | 500 |
| Number of Atoms | 7,500 |
| Links |
https://github.com/davkovacs/BOTNet-datasets https://doi.org/10.48550/arXiv.2205.06643 |
| Configuration Sets by Name | (None) |
| Configuration Sets by ID | (None) |
| Calculated Properties | |
| ColabFit ID | DS_632yputkfhpg_0 |
| Files | colabfitspec.json |
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