Name: COMP6v2-wB97MV-def2TZVPP Extended ID: COMP6v2-wB97MV-def2TZVPP__Huddleston-Zubatyuk-Smith-Roitberg-Isayev-Pickering-Devereux-Barros__DS_m6etjqhlu40m_0 Description: COMP6v2-wB97MV-def2TZVPP is the portion of COMP6v2 calculated at the wB97MV/def2TZVPP 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: 10.60732/e98b76e7 Calculated Property Types: cauchy_stress energy Elements: C (34.19%) Cl (0.64%) F (0.61%) H (50.15%) N (6.93%) O (6.15%) S (1.35%) Methods: DFT-ωB97M-V Software: ORCA 4.2.1 Number of Configurations: 156,338 Number of Atoms: 3,786,615 Publication Link: https://doi.org/10.1021/acs.jctc.0c00121 Data Source Link: https://doi.org/10.5281/zenodo.10126157