Dataset
CGM-MLP_natcomm2023_screening_graphite_train
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| 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
https://commons.datacite.org/doi.org/10.60732/85590078 https://doi.datacite.org/dois/10.60732%2F85590078 https://doi.org/10.60732/85590078 Cite as: Zhang, D., Yi, P., Lai, X., Peng, L., and Li, H. "CGM-MLP natcomm2023 screening graphite train." ColabFit, 2024. https://doi.org/10.60732/85590078. For other citation formats, see the DataCite Fabrica page for this dataset. |
| Calculated Property Types |
atomic_forces cauchy_stress energy |
| Elements |
C (100.0%) |
| Number of Configurations | 41 |
| Number of Atoms | 1,968 |
| Links |
https://github.com/sjtudizhang/CGM-MLP https://doi.org/10.1038/s41467-023-44525-z |
| Configuration Sets by Name | (None) |
| Configuration Sets by ID | (None) |
| Calculated Properties | |
| ColabFit ID | DS_jasbxoigo7r4_0 |
| Files | colabfitspec.json |
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