Datasets:

colabfit
/

QM9x

configs:
  - config_name: default
    data_files: co/*.parquet
  - config_name: info
    data_files: ds.parquet
license: cc-by-4.0
tags:
  - molecular dynamics
  - mlip
  - interatomic potential
pretty_name: QM9x

Cite this dataset
Schreiner, M., Bhowmik, A., Vegge, T., Busk, J., and Winther, O. QM9x. ColabFit, 2023. https://doi.org/10.60732/1edbb6e0

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_d5ug96vla5xy_0

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Dataset Name

QM9x

Description

Dataset containing DFT calculations of energy and forces for all configurations in the QM9 dataset, recalculated with the ωB97X functional and 6-31G(d) basis set. Recalculating the energy and forces causes a slight shift of the potential energy surface, which results in forces acting on most configurations in the dataset. The data was generated by running Nudged Elastic Band (NEB) calculations with DFT on 10k reactions while saving intermediate calculations. QM9x is used as a benchmarking and comparison dataset for the dataset Transition1x.

Dataset authors

Mathias Schreiner, Arghya Bhowmik, Tejs Vegge, Jonas Busk, Ole Winther

Publication

https://doi.org/10.1038/s41597-022-01870-w

Original data link

https://doi.org/10.6084/m9.figshare.20449701.v2

License

CC-BY-4.0

Number of unique molecular configurations

133871

Number of atoms

2407494

Elements included

C, F, H, N, O

Properties included

energy, atomization 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 Schreiner, M., Bhowmik, A., Vegge, T., Busk, J., and Winther, O. QM9x. ColabFit, 2023. https://doi.org/10.60732/1edbb6e0