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
ColabFit ID :
DS_jasbxoigo7r4_0
Files :
colabfitspec.json
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.
Num. Configurations :
41
Num. Atoms :
1,968
Downloads :
36
Calculated Property Types :
atomic_forces cauchy_stress energy
Elements :
C (100.0%)
Methods :
DFT-PBE+D3
Software :
CP2K
Publication Link :
https://doi.org/10.1038/s41467-023-44525-z
Data Source Link :
https://github.com/sjtudizhang/CGM-MLP
Configuration Sets by Name :
Configuration Sets by ID :
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