Dataset

CGM-MLP_natcomm2023_screening_deposited-carbon@Cu_train


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Name CGM-MLP_natcomm2023_screening_deposited-carbon@Cu_train
Extended ID CGM-MLP_natcomm2023_screening_deposited-carbon@Cu_train__Zhang-Yi-Lai-Peng-Li__DS_j6w4ru800ukq_0
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.
Calculated Property Types atomic_forces
cauchy_stress
energy
Elements C (13.42%)
Cu (86.58%)
Number of Configurations 1,091
Number of Atoms 362,898
Links https://github.com/sjtudizhang/CGM-MLP
https://doi.org/10.1038/s41467-023-44525-z
Configuration Sets by Name (None)
Configuration Sets by ID (None)
Calculated Properties
ColabFit ID DS_j6w4ru800ukq_0
Files colabfitspec.json

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