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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