Dataset

CGM-MLP_natcomm2023_Cu-C_metal_surface


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Name :
CGM-MLP_natcomm2023_Cu-C_metal_surface
Extended ID :
CGM-MLP_natcomm2023_Cu-C_metal_surface__Zhang-Yi-Lai-Peng-Li__DS_mo7q9ajg1lw8_0
ColabFit ID :
DS_mo7q9ajg1lw8_0
Files :
colabfitspec.json
Description :
Training simulations from CGM-MLP_natcomm2023 of carbon on a Cu metal surface. This dataset was one of the datasets used in training during the process of producing an active learning dataset for the purposes of exploring substrate-catalyzed deposition on metal surfaces such as Cu(111), Cr(110), Ti(001), and oxygen-contaminated Cu(111) 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, Cr and Ti surfaces.
Authors :
Di Zhang, Peiyun Yi, Xinmin Lai, Linfa Peng, Hao Li
DOI :
10.60732/76552006 https://commons.datacite.org/doi.org/10.60732/76552006 https://doi.datacite.org/dois/10.60732%2F76552006 https://doi.org/10.60732/76552006 Cite as: Zhang, D., Yi, P., Lai, X., Peng, L., and Li, H. "CGM-MLP natcomm2023 Cu-C metal surface." ColabFit, 2024. https://doi.org/10.60732/76552006.
For other citation formats, see the DataCite Fabrica page for this dataset.
Num. Configurations :
520
Num. Atoms :
122,294
Downloads :
39
Calculated Property Types :
atomic_forces cauchy_stress energy
Elements :
C (8.04%) Cu (91.96%)
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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