Name: 3BPA train mixed
License: CC-BY-4.0

Dataset

3BPA_train_mixed

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Species content of dataset

Name :

3BPA_train_mixed

Authors :

Dávid Péter Kovács, Cas van der Oord, Jiri Kucera, Alice E. A. Allen, Daniel J. Cole, Christoph Ortner, Gábor Csányi

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.

DOI :

https://doi.org/10.60732/1dbc6d0a https://commons.datacite.org/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.

ColabFit ID :

DS_v88913tvdxbr_0

Extended ID :

3BPA_train_mixed__Kovacs-Oord-Kucera-Allen-Cole-Ortner-Csanyi__DS_v88913tvdxbr_0

Date Added :

2023-03-07

License :

CC-BY-4.0

Downloads :

Num. Configurations :

500

Num. Atoms :

13,500

Calculated Property Types :

atomic_forces 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

Spec File :

colabfitspec.json

Configuration Sets by Name :

Configuration Sets by ID :

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