Succinic acid training PBE0-MBD dataset from "Semi-local and hybrid functional DFT data for thermalised snapshots of polymorphs of benzene, succinic acid, and glycine". DFT reference energies and forces were calculated using Quantum Espresso v6.3. The calculations were performed with the semi-local PBE xc functional, Tkatchenko-Scheffler dispersion correction, optimised norm-conserving Vanderbilt pseudopotentials, a Monkhorst-Pack k-point grid with a maximum spacing of 0.06 x 2π A^-1, and a plane-wave energy cut-off of 100 Ry for the wavefunction.

Authors :

Venkat Kapil, Edgar A. Engel

DOI :

10.60732/45375ebf https://commons.datacite.org/doi.org/10.60732/45375ebf https://doi.datacite.org/dois/10.60732%2F45375ebf https://doi.org/10.60732/45375ebf Cite as: Kapil, V., and Engel, E. A. "DFT polymorphs PNAS 2022 PBE0 MBD succinic acid train." ColabFit, 2023. https://doi.org/10.60732/45375ebf.
For other citation formats, see the DataCite Fabrica page for this dataset.

Num. Configurations :

1,800

Num. Atoms :

50,400

Downloads :

Calculated Property Types :

atomic_forces cauchy_stress energy

Elements :

C (28.57%) H (42.86%) O (28.57%)

Methods :

DFT-PBE+TS

Software :

Quantum ESPRESSO v6.3

Publication Link :

https://doi.org/10.1073/pnas.2111769119

Data Source Link :

https://doi.org/10.24435/materialscloud:vp-jf

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