Dataset

CGM-MLP_natcomm2023_screening_deposited-carbon@Cu_train




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Name :
CGM-MLP_natcomm2023_screening_deposited-carbon@Cu_train
ColabFit ID :
Description :
1090 structures uniformly selected from the MD/tfMC simulation during the training process of CGM-MLPs. 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 :
10.60732/535052eb https://commons.datacite.org/doi.org/10.60732/535052eb https://doi.datacite.org/dois/10.60732%2F535052eb https://doi.org/10.60732/535052eb Cite as: Zhang, D., Yi, P., Lai, X., Peng, L., and Li, H. "CGM-MLP natcomm2023 screening deposited-carbon@Cu train." ColabFit, 2024. https://doi.org/10.60732/535052eb.
For other citation formats, see the DataCite Fabrica page for this dataset.
Num. Configurations :
1,091
Num. Atoms :
362,898
Downloads :
21
Calculated Property Types :
atomic_forces cauchy_stress energy
Elements :
C (13.42%) Cu (86.58%)
Methods :
DFT-PBE+D3
Software :
CP2K
Configuration Sets by Name :
Configuration Sets by ID :

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