Dataset

AFF_JCP_2022

Download Original Data Files 86.1 MB

Download Dataset Parquet Files 134.5 MB

Find on Hugging Face 🤗

Species content of dataset

Dataset viewer powered by Hugging Face

Name :

AFF_JCP_2022

Extended ID :

AFF_JCP_2022__Li-Zhou-Sebastian-Wu-Gu__DS_5lhmgnxhuia3_0

ColabFit ID :

DS_5lhmgnxhuia3_0

Files :

colabfitspec.json

Description :

Approximately 145,000 configurations of alkane, aspirin, alpha-glucose and uracil, partly taken from the MD-17 dataset, used in training an 'Atomic Neural Net' model.

Authors :

Hao Li, Musen Zhou, Jessalyn Sebastian, Jianzhong Wu, Mengyang Gu

DOI :

10.60732/82344f5c https://commons.datacite.org/doi.org/10.60732/82344f5c https://doi.datacite.org/dois/10.60732%2F82344f5c https://doi.org/10.60732/82344f5c Cite as: Li, H., Zhou, M., Sebastian, J., Wu, J., and Gu, M. "AFF JCP 2022." ColabFit, 2023. https://doi.org/10.60732/82344f5c.
For other citation formats, see the DataCite Fabrica page for this dataset.

Num. Configurations :

143,756

Num. Atoms :

1,911,045

Downloads :

Calculated Property Types :

atomic_forces cauchy_stress energy

Elements :

C (33.33%) H (36.89%) N (14.0%) O (15.78%)

Methods :

DFT-PBE-vdW-TS

Software :

Q-Chem

Publication Link :

https://doi.org/10.1063/5.0088017

Data Source Link :

https://github.com/UncertaintyQuantification/AFF/tree/master

Configuration Sets by Name :

Configuration Sets by ID :

Report an issue with this dataset

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.