Dataset

3BPA_train_300K

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Name :

3BPA_train_300K

Extended ID :

3BPA_train_300K__Kovacs-Oord-Kucera-Allen-Cole-Ortner-Csanyi__DS_hu0btdblv8x6_0

ColabFit ID :

DS_hu0btdblv8x6_0

Files :

colabfitspec.json

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.

Num. Configurations :

500

Num. Atoms :

13,500

Downloads :

Calculated Property Types :

atomic_forces cauchy_stress energy

Elements :

C (44.44%) H (44.44%) N (7.41%) O (3.7%)

Methods :

DFT-ωB97X

Software :

ORCA

Publication Link :

https://doi.org/10.1021/acs.jctc.1c00647

Data Source Link :

https://doi.org/10.1021/acs.jctc.1c00647

Configuration Sets by Name :

Configuration Sets by ID :

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