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_ZhangYiLaiPengLi__DS_392q5d027yja_0
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.
Elements C (23.48%)
Cr (76.52%)
Number of Data Objects 1,192
Number of Configurations 1,192
Number of Atoms 298,114
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)
Data Objects
ColabFit ID DS_392q5d027yja_0
Files colabfitspec.json

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