Dataset

DFT_polymorphs_PNAS_2022_PBE_TS_benzene_train




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Name :
DFT_polymorphs_PNAS_2022_PBE_TS_benzene_train
ColabFit ID :
Description :
Benzene training PBE-TS 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 :
10.60732/6b905ba8 https://commons.datacite.org/doi.org/10.60732/6b905ba8 https://doi.datacite.org/dois/10.60732%2F6b905ba8 https://doi.org/10.60732/6b905ba8 Cite as: Kapil, V., and Engel, E. A. "DFT polymorphs PNAS 2022 PBE TS benzene train." ColabFit, 2023. https://doi.org/10.60732/6b905ba8.
For other citation formats, see the DataCite Fabrica page for this dataset.
Num. Configurations :
54,990
Num. Atoms :
1,601,760
Downloads :
50
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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