Dataset

DFT_polymorphs_PNAS_2022_PBE0_MBD_glycine_train


Download Dataset XYZ file

Name DFT_polymorphs_PNAS_2022_PBE0_MBD_glycine_train
Extended ID DFT_polymorphs_PNAS_2022_PBE0_MBD_glycine_train_KapilEngel__DS_uk72hlukj3pf_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
Elements C (20.0%)
H (50.0%)
N (10.0%)
O (20.0%)
Number of Data Objects 3,582
Number of Configurations 3,582
Number of Atoms 109,570
Links https://doi.org/10.1073/pnas.2111769119
https://doi.org/10.24435/materialscloud:vp-jf
https://github.com/venkatkapil24/data_molecular_fluctuations
Configuration Sets by Name (None)
Configuration Sets by ID (None)
Data Objects
ColabFit ID DS_uk72hlukj3pf_0
Files colabfitspec.json

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.