Molecular structures with spectroscopic accuracy at DFT cost by the templating synthon approach and the PCS141 database

Abstract

The computation of accurate geometric parameters at density functional theory cost for large molecules in the gas phase is addressed through a novel strategy that combines quantum chemical models with machine learning techniques. The first key step is the expansion of a database of accurate semi-experimental equilibrium structures with additional molecular geometries optimized by version 2 of the Pisa composite scheme. Then, the templating synthon approach is used to improve the accuracy of structures optimized by a hybrid density functional paired with a double zeta basis set, leveraging chemical similarity to cluster different molecular environments and refine bond lengths and valence angles. A set of prototypical biomolecular building blocks is used to demonstrate that it is possible to achieve spectroscopic accuracy for molecular systems too large to be treated by state-of-the-art composite wavefunction methods. In addition, a freely accessible web-based tool has been developed to facilitate the post-processing of geometries optimized using standard electronic structure codes, thereby providing an accurate and efficient tool for the computational study of medium- to large-sized molecules, also accessible to experiment-oriented researchers.