Dataset

CA-9_BB_training




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Name :
CA-9_BB_training
ColabFit ID :
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.
Num. Configurations :
20,006
Num. Atoms :
1,053,753
Downloads :
29
Calculated Property Types :
atomic_forces cauchy_stress energy
Elements :
C (100.0%)
Methods :
DFT-PBE
Software :
VASP
Configuration Sets by Name :
Configuration Sets by ID :

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