Dataset
DFT_polymorphs_PNAS_2022_PBE_TS_glycine_train
Download Dataset XYZ file
| Name | DFT_polymorphs_PNAS_2022_PBE_TS_glycine_train |
|---|---|
| Extended ID | DFT_polymorphs_PNAS_2022_PBE_TS_glycine_train_KapilEngel__DS_op9kvcm7ui6l_0 |
| Description | Glycine 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 |
10.60732/76aa925f
https://commons.datacite.org/doi.org/10.60732/76aa925f https://doi.datacite.org/dois/10.60732%2F76aa925f https://doi.org/10.60732/76aa925f Cite as: Kapil, V., and Engel, E. A. "DFT polymorphs PNAS 2022 PBE TS glycine train." ColabFit, 2023. https://doi.org/10.60732/76aa925f. For other citation formats, see the DataCite Fabrica page for this dataset. |
| Elements |
C (20.0%) H (50.0%) N (10.0%) O (20.0%) |
| Number of Data Objects | 29,070 |
| Number of Configurations | 29,070 |
| Number of Atoms | 952,650 |
| 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) |
| Data Objects | Too many to display |
| ColabFit ID | DS_op9kvcm7ui6l_0 |
| Files | colabfitspec.json |
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