Dataset

3BPA_train_300K



Download Dataset XYZ file

Name 3BPA_train_300K
Extended ID 3BPA_train_300K__Kovács-Oord-Kucera-Allen-Cole-Ortner-Csányi__DS_hu0btdblv8x6_0
Description Training configurations with MD simulations performed at 300K from 3BPA, used to showcase the performance of linear atomic cluster expansion (ACE) force fields in a machine learning model to predict the potential energy surfaces of organic molecules.
Authors Dávid Péter Kovács
Cas van der Oord
Jiri Kucera
Alice E. A. Allen
Daniel J. Cole
Christoph Ortner
Gábor Csányi
DOI 10.60732/5f5bae68
https://commons.datacite.org/doi.org/10.60732/5f5bae68
https://doi.datacite.org/dois/10.60732%2F5f5bae68
https://doi.org/10.60732/5f5bae68

Cite as: Kovács, D. P., Oord, C., Kucera, J., Allen, A. E. A., Cole, D. J., Ortner, C., and Csányi, G. "3BPA train 300K." ColabFit, 2023. https://doi.org/10.60732/5f5bae68.
For other citation formats, see the DataCite Fabrica page for this dataset.
Property Types atomic_forces
cauchy_stress
energy
Elements C (44.44%)
H (44.44%)
N (7.41%)
O (3.7%)
Number of Property Objects 500
Number of Configurations 500
Number of Atoms 13,500
Links https://doi.org/10.1021/acs.jctc.1c00647
https://doi.org/10.1021/acs.jctc.1c00647
Configuration Sets by Name (None)
Configuration Sets by ID (None)
Property Objects
ColabFit ID DS_hu0btdblv8x6_0
Files colabfitspec.json

No uploaded content is transferred in ownership from the original creators to ColabFit. All content is distributed under the license specified by its contributor who has stated that he or she has the authority to share it under the specified license.