Dataset

CA-9_BB_training


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Name CA-9_BB_training
Extended ID CA-9_BB_training__Hedman-Rothe-Johansson-Sandin-Larsson-Miyamoto__DS_l7inbtql4ea9_0
Description Binning-binning configurations from CA-9 dataset used for training NNP_BB potential. 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/f3bbbd36
https://commons.datacite.org/doi.org/10.60732/f3bbbd36
https://doi.datacite.org/dois/10.60732%2Ff3bbbd36
https://doi.org/10.60732/f3bbbd36

Cite as: Hedman, D., Rothe, T., Johansson, G., Sandin, F., Larsson, J. A., and Miyamoto, Y. "CA-9 BB training." ColabFit, 2023. https://doi.org/10.60732/f3bbbd36.
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 20,012
Number of Atoms 1,054,055
Links https://doi.org/10.24435/materialscloud:6h-yj
https://doi.org/10.1016/j.cartre.2021.100027
Configuration Sets by Name (None)
Configuration Sets by ID (None)
Calculated Properties
ColabFit ID DS_l7inbtql4ea9_0
Files colabfitspec.json

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