Dataset

DFT_polymorphs_PNAS_2022_PBE_TS_succinic_acid_train



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Name DFT_polymorphs_PNAS_2022_PBE_TS_succinic_acid_train
Extended ID DFT_polymorphs_PNAS_2022_PBE_TS_succinic_acid_train__Kapil-Engel__DS_0u0k9ghrlkpx_0
Description Succinic acid 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/e3efb796
https://commons.datacite.org/doi.org/10.60732/e3efb796
https://doi.datacite.org/dois/10.60732%2Fe3efb796
https://doi.org/10.60732/e3efb796

Cite as: Kapil, V., and Engel, E. A. "DFT polymorphs PNAS 2022 PBE TS succinic acid train." ColabFit, 2023. https://doi.org/10.60732/e3efb796.
For other citation formats, see the DataCite Fabrica page for this dataset.
Calculated Property Types atomic_forces
cauchy_stress
energy
Elements C (28.57%)
H (42.86%)
O (28.57%)
Number of Configurations 29,212
Number of Atoms 817,936
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_0u0k9ghrlkpx_0
Files colabfitspec.json

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