Dataset

DFT_polymorphs_PNAS_2022_PBE0_MBD_benzene_train




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Name :
DFT_polymorphs_PNAS_2022_PBE0_MBD_benzene_train
ColabFit ID :
Description :
Benzene 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 :
10.60732/8d563e8a https://commons.datacite.org/doi.org/10.60732/8d563e8a https://doi.datacite.org/dois/10.60732%2F8d563e8a https://doi.org/10.60732/8d563e8a Cite as: Kapil, V., and Engel, E. A. "DFT polymorphs PNAS 2022 PBE0 MBD benzene train." ColabFit, 2023. https://doi.org/10.60732/8d563e8a.
For other citation formats, see the DataCite Fabrica page for this dataset.
Num. Configurations :
1,799
Num. Atoms :
49,512
Downloads :
14
Calculated Property Types :
atomic_forces cauchy_stress energy
Elements :
C (50.0%) H (50.0%)
Methods :
DFT-PBE+TS
Software :
Quantum ESPRESSO v6.3
Configuration Sets by Name :
Configuration Sets by ID :

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