Dataset
CA-9_test
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Name | CA-9_test |
---|---|
Extended ID | CA-9_test__Hedman-Rothe-Johansson-Sandin-Larsson-Miyamoto__DS_h0mshvvbxlai_0 |
Description | Test configurations from CA-9 dataset used to evaluate trained NNPs.CA-9 consists of configurations of carbon with curated subsets chosen to test the effects of intentionally choosing dissimilar configurations when training neural network potentials |
Authors |
Daniel Hedman Tom Rothe Gustav Johansson Fredrik Sandin J. Andreas Larsson Yoshiyuki Miyamoto |
DOI |
10.60732/5a57f6ad
https://commons.datacite.org/doi.org/10.60732/5a57f6ad https://doi.datacite.org/dois/10.60732%2F5a57f6ad https://doi.org/10.60732/5a57f6ad Cite as: Hedman, D., Rothe, T., Johansson, G., Sandin, F., Larsson, J. A., and Miyamoto, Y. "CA-9 test." ColabFit, 2023. https://doi.org/10.60732/5a57f6ad. For other citation formats, see the DataCite Fabrica page for this dataset. |
Calculated Property Types |
atomic_forces cauchy_stress energy |
Elements |
C (100.0%)
|
Number of Configurations | 2,726 |
Number of Atoms | 206,238 |
Publication Link | https://doi.org/10.1016/j.cartre.2021.100027 |
Data Source Link | https://doi.org/10.24435/materialscloud:6h-yj |
Configuration Sets by Name | |
Configuration Sets by ID | |
ColabFit ID | DS_h0mshvvbxlai_0 |
Downloads | 10 |
Files | colabfitspec.json |
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