Datasets:

colabfit
/

Carbon_GAP_JCP_2020_train

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: cc-by-4.0
tags:
  - molecular dynamics
  - mlip
  - interatomic potential
pretty_name: Carbon GAP JCP 2020 train

Cite this dataset
Rowe, P., Deringer, V. L., Gasparotto, P., Csányi, G., and Michaelides, A. Carbon GAP JCP 2020 train. ColabFit, 2023. https://doi.org/10.60732/9d095830

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This dataset is also available on the ColabFit Exchange:

https://materials.colabfit.org/id/DS_sz9me9r61581_0

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Dataset Name

Carbon GAP JCP 2020 train

Description

Training data generated for GAP-20. GAP-20 describes the properties of the bulk crystalline and amorphous phases, crystal surfaces, and defect structures with an accuracy approaching that of direct ab initio simulation, but at a significantly reduced cost. The final potential is fitted to reference data computed using the optB88-vdW density functional theory (DFT) functional.

Dataset authors

Patrick Rowe, Volker L. Deringer, Piero Gasparotto, Gábor Csányi, Angelos Michaelides

Publication

https://doi.org/10.1063/5.0005084

Original data link

https://www.repository.cam.ac.uk/handle/1810/307452

License

CC-BY-4.0

Number of unique molecular configurations

6088

Number of atoms

400275

Elements included

Properties included

energy, atomic forces, cauchy stress

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 Rowe, P., Deringer, V. L., Gasparotto, P., Csányi, G., and Michaelides, A. Carbon GAP JCP 2020 train. ColabFit, 2023. https://doi.org/10.60732/9d095830