Dataset

CA-9_BR_training


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Name CA-9_BR_training
Extended ID CA-9_BR_training__Hedman-Rothe-Johansson-Sandin-Larsson-Miyamoto__DS_fw7m5d8b0fa9_0
Description Binning-random configurations from CA-9 dataset used for training NNP_BR 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 10.60732/07b7d297
https://commons.datacite.org/doi.org/10.60732/07b7d297
https://doi.datacite.org/dois/10.60732%2F07b7d297
https://doi.org/10.60732/07b7d297

Cite as: Hedman, D., Rothe, T., Johansson, G., Sandin, F., Larsson, J. A., and Miyamoto, Y. "CA-9 BR training." ColabFit, 2023. https://doi.org/10.60732/07b7d297.
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 20,013
Number of Atoms 1,072,779
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_fw7m5d8b0fa9_0
Files colabfitspec.json

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