Name: CGM-MLP_natcomm2023_screening_graphite_train Extended ID: CGM-MLP_natcomm2023_screening_graphite_train__Zhang-Yi-Lai-Peng-Li__DS_jasbxoigo7r4_0 Description: 40 graphite structures with different lattice constants ranging from 2.0 to 3.2 Å, with a 0.03 Å increment. This dataset was one of the datasets used in testing screening parameters during the process of producing an active learning dataset for Cu-C interactions for the purposes of exploring substrate-catalyzed deposition as a means of controllable synthesis of carbon nanomaterials. The combined dataset includes structures from the Carbon_GAP_20 dataset and additional configurations of carbon clusters on a Cu(111) surface. Authors: Di Zhang Peiyun Yi Xinmin Lai Linfa Peng Hao Li DOI: 10.60732/85590078 Calculated Property Types: atomic_forces cauchy_stress energy Elements: C (100.0%) Methods: DFT-PBE+D3 Software: CP2K Number of Configurations: 41 Number of Atoms: 1,968 Publication Link: https://doi.org/10.1038/s41467-023-44525-z Data Source Link: https://github.com/sjtudizhang/CGM-MLP