Dataset

DFT_polymorphs_PNAS_2022_PBE0_MBD_glycine_train


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Name DFT_polymorphs_PNAS_2022_PBE0_MBD_glycine_train
Extended ID DFT_polymorphs_PNAS_2022_PBE0_MBD_glycine_train__Kapil-Engel__DS_b1n228x610dj_0
Description Glycine 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 10.60732/358cb5ee
https://commons.datacite.org/doi.org/10.60732/358cb5ee
https://doi.datacite.org/dois/10.60732%2F358cb5ee
https://doi.org/10.60732/358cb5ee

Cite as: Kapil, V., and Engel, E. A. "DFT polymorphs PNAS 2022 PBE0 MBD glycine train." ColabFit, 2023. https://doi.org/10.60732/358cb5ee.
For other citation formats, see the DataCite Fabrica page for this dataset.
Calculated Property Types atomic_forces
cauchy_stress
energy
Elements C (20.0%)
H (50.0%)
N (10.0%)
O (20.0%)
Number of Configurations 3,594
Number of Atoms 109,940
Links https://doi.org/10.24435/materialscloud:vp-jf
https://doi.org/10.1073/pnas.2111769119
https://github.com/venkatkapil24/data_molecular_fluctuations
Configuration Sets by Name (None)
Configuration Sets by ID (None)
Calculated Properties
ColabFit ID DS_b1n228x610dj_0
Files colabfitspec.json

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