Dataset

CGM-MLP_natcomm2023_Cu-C_deposition



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Name CGM-MLP_natcomm2023_Cu-C_deposition
Extended ID CGM-MLP_natcomm2023_Cu-C_deposition_ZhangYiLaiPengLi__DS_vgy50b4qz4p7_0
Description Training simulations from CGM-MLP_natcomm2023 of carbon deposition on a Cu 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
Elements C (12.79%)
Cu (87.21%)
Number of Data Objects 1,177
Number of Configurations 1,177
Number of Atoms 204,591
Links https://doi.org/10.1038/s41467-023-44525-z
https://github.com/sjtudizhang/CGM-MLP
Configuration Sets by Name (None)
Configuration Sets by ID (None)
Data Objects
ColabFit ID DS_vgy50b4qz4p7_0
Files colabfitspec.json

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