colabfit/sGDML_Ethanol_ccsdt_NC2018_train

Cite this dataset

Chmiela, S., Sauceda, H. E., Müller, K., and Tkatchenko, A. sGDML Ethanol ccsdt NC2018 train. ColabFit, 2023. https://doi.org/10.60732/c254fdb2

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Dataset Name

sGDML Ethanol ccsdt NC2018 train

Description

The train set of a train/test pair from the ethanol dataset from sGDML. To create the coupled cluster datasets, the data used for training the models were created by running ab initio MD in the NVT ensemble using the Nosé-Hoover thermostat at 500 K during a 200 ps simulation with a resolution of 0.5 fs. Energies and forces were recalculated using all-electron coupled cluster with single, double and perturbative triple excitations (CCSD(T)).The Dunning correlation-consistent basis set cc-pVTZ was used for ethanol. All calculations were performed with the Psi4 software suite.

Dataset authors

Stefan Chmiela, Huziel E. Sauceda, Klaus-Robert Müller, Alexandre Tkatchenko

Publication

https://doi.org/10.1038/s41467-018-06169-2

Original data link

http://sgdml.org/

License

MIT

Number of unique molecular configurations

998

Number of atoms

8982

Elements included

C, H, O

Properties included

energy, atomic forces

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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).
  

ColabFit Exchange documentation includes descriptions of content and example code for parsing parquet files:

• Parquet parsing: example code
• Dataset info schema
• Configuration schema
• Configuration set schema
• Configuration set to configuration mapping schema