QM-sym, a symmetrized quantum chemistry database of 135 kilo molecules.

ABSTRACT: Applying deep learning methods in materials science research is an important way of solving the time-consuming problems of typical ab initio quantum chemistry methodology, but due to the size of large molecules, large and uncharted fields still exist. Implementing symmetry information can significantly reduce the calculation complexity of structures, as they can be simplified to the minimum symmetric units. Because there are few quantum chemistry databases that include symmetry information, we constructed a new one, named QM-sym, by designing an algorithm to generate 135k organic molecules with the C_nh symmetry composite. Those generated molecules were optimized to a stable state using Gaussian 09. The geometric, electronic, energetic, and thermodynamic properties of the molecul

SUBMITTER: Liang J 

PROVIDER: S-EPMC6802082 | biostudies-literature | 2019 Oct

REPOSITORIES: biostudies-literature