Dataset

DFT_polymorphs_PNAS_2022_PBE0_MBD_benzene_train



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Name DFT_polymorphs_PNAS_2022_PBE0_MBD_benzene_train
Extended ID DFT_polymorphs_PNAS_2022_PBE0_MBD_benzene_train_KapilEngel__DS_ox9uuun3mzav_0
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
Elements C (50.0%)
H (50.0%)
Number of Data Objects 1,800
Number of Configurations 1,800
Number of Atoms 49,536
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_ox9uuun3mzav_0
Files colabfitspec.json

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