Dataset

3BPA_train_mixed



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Name 3BPA_train_mixed
Extended ID 3BPA_train_mixed__Kovács-Oord-Kucera-Allen-Cole-Ortner-Csányi__DS_v88913tvdxbr_0
Description Training configurations with MD simulation performed at 300K, 600K and 1200K from 3BPA dataset, 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 10.60732/1dbc6d0a
https://commons.datacite.org/doi.org/10.60732/1dbc6d0a
https://doi.datacite.org/dois/10.60732%2F1dbc6d0a
https://doi.org/10.60732/1dbc6d0a

Cite as: Kovács, D. P., Oord, C., Kucera, J., Allen, A. E. A., Cole, D. J., Ortner, C., and Csányi, G. "3BPA train mixed." ColabFit, 2023. https://doi.org/10.60732/1dbc6d0a.
For other citation formats, see the DataCite Fabrica page for this dataset.
Calculated Property Types atomic_forces
cauchy_stress
energy
Elements C (44.44%)
H (44.44%)
N (7.41%)
O (3.7%)
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)
Calculated Properties
ColabFit ID DS_v88913tvdxbr_0
Files colabfitspec.json

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