Dataset

CGM-MLP_natcomm2023_Cr-C_deposition


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Name :
CGM-MLP_natcomm2023_Cr-C_deposition
Extended ID :
CGM-MLP_natcomm2023_Cr-C_deposition__Zhang-Yi-Lai-Peng-Li__DS_392q5d027yja_0
ColabFit ID :
DS_392q5d027yja_0
Files :
colabfitspec.json
Description :
Training simulations from CGM-MLP_natcomm2023 of carbon deposition on a Cr 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/e25bae2e https://commons.datacite.org/doi.org/10.60732/e25bae2e https://doi.datacite.org/dois/10.60732%2Fe25bae2e https://doi.org/10.60732/e25bae2e Cite as: Zhang, D., Yi, P., Lai, X., Peng, L., and Li, H. "CGM-MLP natcomm2023 Cr-C deposition." ColabFit, 2024. https://doi.org/10.60732/e25bae2e.
For other citation formats, see the DataCite Fabrica page for this dataset.
Num. Configurations :
1,192
Num. Atoms :
298,114
Downloads :
19
Calculated Property Types :
atomic_forces cauchy_stress energy
Elements :
C (23.48%) Cr (76.52%)
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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