DFT_polymorphs_PNAS_2022_PBE_TS_glycine_train

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.

本数据集为出自论文《苯、琥珀酸与甘氨酸多晶型热平衡快照的半局域及杂化泛函DFT数据》的甘氨酸训练用PBE-TS数据集。研究采用Quantum Espresso v6.3软件计算了DFT（Density Functional Theory，密度泛函理论）参考能量与原子受力。本次计算采用了以下参数：半局域PBE交换关联泛函、Tkatchenko-Scheffler色散校正、优化后的模守恒范德堡赝势、最大间距为0.06×2π Å⁻¹的蒙霍斯特-帕克k点网格，以及用于波函数计算的100 Ry平面波能量截断能。