Datasets:

colabfit
/

AFF_JCP_2022

configs:
  - config_name: default
    data_files: co/*.parquet
  - config_name: info
    data_files: ds.parquet
  - config_name: configuration_sets
    data_files: cs/*.parquet
  - config_name: config_set_mapping
    data_files: cs_co_map/*.parquet
license: gpl-3.0
tags:
  - molecular dynamics
  - mlip
  - interatomic potential
pretty_name: AFF JCP 2022

Cite this dataset
Li, H., Zhou, M., Sebastian, J., Wu, J., and Gu, M. AFF JCP 2022. ColabFit, 2023. https://doi.org/10.60732/82344f5c

This dataset has been curated and formatted for the ColabFit Exchange

This dataset is also available on the ColabFit Exchange:

https://materials.colabfit.org/id/DS_5lhmgnxhuia3_0

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Dataset Name

AFF JCP 2022

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.

Dataset authors

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

Publication

https://doi.org/10.1063/5.0088017

Original data link

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

License

GPL-3.0

Number of unique molecular configurations

143756

Number of atoms

1911045

Elements included

C, H, N, O

Properties included

energy, atomic forces

Usage

ds.parquet : Aggregated dataset information.
co/ directory: Configuration rows each include a structure, calculated properties, and metadata.
cs/ directory : Configuration sets are subsets of configurations grouped by some common characteristic. If cs/ does not exist, no configurations sets have been defined for this dataset.
cs_co_map/ directory : The mapping of configurations to configuration sets (if defined).

Cite this dataset Li, H., Zhou, M., Sebastian, J., Wu, J., and Gu, M. AFF JCP 2022. ColabFit, 2023. https://doi.org/10.60732/82344f5c