Dataset

CGM-MLP_natcomm2023_Ti-C_deposition


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Name CGM-MLP_natcomm2023_Ti-C_deposition
Extended ID CGM-MLP_natcomm2023_Ti-C_deposition__Zhang-Yi-Lai-Peng-Li__DS_8frq3jczb0dt_0
Description Training simulations from CGM-MLP_natcomm2023 of carbon deposition on a Ti 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 10.60732/4e8857ac
https://commons.datacite.org/doi.org/10.60732/4e8857ac
https://doi.datacite.org/dois/10.60732%2F4e8857ac
https://doi.org/10.60732/4e8857ac

Cite as: Zhang, D., Yi, P., Lai, X., Peng, L., and Li, H. "CGM-MLP natcomm2023 Ti-C deposition." ColabFit, 2024. https://doi.org/10.60732/4e8857ac.
For other citation formats, see the DataCite Fabrica page for this dataset.
Calculated Property Types atomic_forces
cauchy_stress
energy
Elements C (27.4%)
Ti (72.6%)
Number of Configurations 1,309
Number of Atoms 259,636
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_8frq3jczb0dt_0
Files colabfitspec.json

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