Dataset
AFF_JCP_2022
Download Dataset XYZ files Download Dataset Parquet files
| Name | AFF_JCP_2022 |
|---|---|
| Extended ID | AFF_JCP_2022__Li-Zhou-Sebastian-Wu-Gu__DS_5lhmgnxhuia3_0 |
| Description | Approximately 145,000 configurations of alkane, aspirin, alpha-glucose and uracil, partly taken from the MD-17 dataset, used in training an 'Atomic Neural Net' model. |
| Authors |
Hao Li Musen Zhou Jessalyn Sebastian Jianzhong Wu Mengyang Gu |
| DOI |
10.60732/82344f5c
https://commons.datacite.org/doi.org/10.60732/82344f5c https://doi.datacite.org/dois/10.60732%2F82344f5c https://doi.org/10.60732/82344f5c Cite as: Li, H., Zhou, M., Sebastian, J., Wu, J., and Gu, M. "AFF JCP 2022." ColabFit, 2023. https://doi.org/10.60732/82344f5c. 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 (36.89%) N (14.0%) O (15.78%) |
| Number of Configurations | 143,770 |
| Number of Atoms | 1,911,240 |
| Links |
https://github.com/UncertaintyQuantification/AFF/tree/master https://doi.org/10.1063/5.0088017 |
| Configuration Sets by Name |
AFF_JCP_2022-aspirin — Aspirin configurations from AFF_JCP_2022 dataset AFF_JCP_2022-uracil — Uracil configurations from AFF_JCP_2022 dataset AFF_JCP_2022-alkane — Alkane configurations from AFF_JCP_2022 dataset AFF_JCP_2022-alpha-glucose — alpha-glucose configurations from AFF_JCP_2022 dataset |
| Configuration Sets by ID |
CS_0khowajhl1dt_0 CS_0qqpkmn13elf_0 CS_ljltnmxl5kbx_0 CS_prz0q62dqk8n_0 |
| Calculated Properties | |
| ColabFit ID | DS_5lhmgnxhuia3_0 |
| Files | colabfitspec.json |
No uploaded content is transferred in ownership from the original creators to ColabFit. All content is distributed under the license specified by its contributor who has stated that he or she has the authority to share it under the specified license.