nLMF training data for LDH

These datasets were generated using a modified version of Turbomole, employing the def2-QZVPPD basis set, RI-DFT approximation, and the ωDH25 functional with gridsize 3. They were utilized for training neural-network local mixing function (LMF) models, specifically in the development of the first double local hybrid functionals. Each data entry has the following structure: ra, gax, gay, gaz, la, ta, haxx, haxy, haxz, hayy, hayz, hazz, rb, gbx, gby, gbz, lb, tb, hbxx, hbxy, hbxz, hbyy, hbyz, hbzz, exx_sra+exx_lra, exx_srb+exx_lrb, exx_sra, exx_srb, XXX, XXX, XXX, XXX Each feature is represented in scientific notation (E24.17). XXX columns represent part of trained functional and were not used in training of n-LMF. Data were used as input for training with: https://github.com/awodynski/nLMFs/本数据集基于修改版Turbomole程序生成，计算过程采用def2-QZVPPD基组、RI-DFT近似，以及网格尺寸为3的ωDH25泛函。本数据集被用于训练神经网络局部混合函数（LMF，Neural-network Local Mixing Function）模型，尤其适用于首款双局域杂化泛函的开发工作。 每条数据条目具有如下格式：ra、gax、gay、gaz、la、ta、haxx、haxy、haxz、hayy、hayz、hazz、rb、gbx、gby、gbz、lb、tb、hbxx、hbxy、hbxz、hbyy、hbyz、hbzz、exx_sra+exx_lra、exx_srb+exx_lrb、exx_sra、exx_srb、XXX、XXX、XXX、XXX 所有特征均采用科学计数法（格式为E24.17）进行表征。 XXX列为训练所得泛函的组成部分，未被用于n-LMF的训练流程。 本数据集被用作如下训练脚本的输入数据：https://github.com/awodynski/nLMFs/