DFT polymorphs PNAS 2022 PBE0 MBD glycine train

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.

本数据集为从《苯、琥珀酸和甘氨酸聚合物形态的热平衡快照的半局部和混合功能DFT数据》中提取的甘氨酸训练PBE0-MBD数据集。其中，使用Quantum Espresso v6.3计算了DFT参考能量和力。计算过程中采用了半局部PBE交换关联泛函、Tkatchenko-Scheffler色散校正、优化后的范德瓦尔斯赝势、 Monkhorst-Pack k点网格，最大间距为0.06 x 2π A^-1，以及100 Ry的平面波能量截断值。