Dataset

DFT_polymorphs_PNAS_2022_PBE0_MBD_succinic_acid_train




Species content of dataset


Dataset viewer powered by Hugging Face

Name :
DFT_polymorphs_PNAS_2022_PBE0_MBD_succinic_acid_train
ColabFit ID :
Description :
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 :
20
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
Configuration Sets by Name :
Configuration Sets by ID :

No uploaded content is transferred in ownership from the original creators to ColabFit. All content is distributed under the license specified by its contributor who has stated that he or she has the authority to share it under the specified license.