Dataset
COMP6v2-wB97X-631Gd
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| Name | COMP6v2-wB97X-631Gd |
|---|---|
| Extended ID | COMP6v2-wB97X-631Gd_HuddlestonZubatyukSmithRoitbergIsayevPickeringDevereuxBarros__DS_15m7etw1om8a_0 |
| Description | COMP6v2-wB97X-631Gd is the portion of COMP6v2 calculated at the wB97X/631Gd level of theory. COmprehensive Machine-learning Potential (COMP6) Benchmark Suite version 2.0 is an extension of the COMP6 benchmark found in the following repository: https://github.com/isayev/COMP6. COMP6v2 is a data set of density functional properties for molecules containing H, C, N, O, S, F, and Cl. It is available at the following levels of theory: wB97X/631Gd (data used to train model in the ANI-2x paper); wB97MD3BJ/def2TZVPP; wB97MV/def2TZVPP; B973c/def2mTZVP. The 6 subsets from COMP6 (ANI-MD, DrugBank, GDB07to09, GDB10to13 Tripeptides, and s66x8) are contained in each of the COMP6v2 datasets corresponding to the above levels of theory. |
| Authors |
Kate Huddleston Roman Zubatyuk Justin Smith Adrian Roitberg Olexandr Isayev Ignacio Pickering Christian Devereux Kipton Barros |
| DOI |
None
https://commons.datacite.org/doi.org/None https://doi.datacite.org/dois/None https://doi.org/None Cite as: Huddleston, K., Zubatyuk, R., Smith, J., Roitberg, A., Isayev, O., Pickering, I., Devereux, C., and Barros, K. "COMP6v2-wB97X-631Gd." ColabFit, 2023. https://doi.org/None. For other citation formats, see the DataCite Fabrica page for this dataset. |
| Elements |
C (34.21%) Cl (0.62%) F (0.59%) H (50.17%) N (6.91%) O (6.19%) S (1.31%) |
| Number of Data Objects | 157,728 |
| Number of Configurations | 157,728 |
| Number of Atoms | 3,897,978 |
| Links |
https://doi.org/10.5281/zenodo.10126157 https://doi.org/10.1021/acs.jctc.0c00121 |
| Configuration Sets by Name | (None) |
| Configuration Sets by ID | (None) |
| Data Objects | Too many to display |
| ColabFit ID | DS_15m7etw1om8a_0 |
| Files | colabfitspec.json |
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