Introducing DDEC6 atomic population analysis: part 2. Computed results for a wide range of periodic and nonperiodic materials†
Abstract
Net atomic charges (NACs) are widely used throughout the chemical sciences to concisely summarize key information about charge transfer between atoms in materials. The vast majority of NAC definitions proposed to date are unsuitable for describing the wide range of material types encountered across the chemical sciences. In this article, we show the DDEC6 method reproduces important chemical, theoretical, and experimental properties across an extremely broad range of material types including small and large molecules, organometallics, nanoclusters, porous solids, nonporous solids, and solid surfaces. Some important comparisons we make are: (a) correlations between various NAC models and spectroscopically measured core-electron binding energy shifts for Ti-, Fe-, and Mo-containing solids, (b) comparisons between DDEC6 and experimentally extracted NACs for formamide and natrolite, (c) comparisons of accuracy of different NAC methods for reproducing the electrostatic potential surrounding a material across one and multiple system conformations, (d) comparisons between calculated and chemically expected electron transfer trends for atoms in numerous dense solids, solid surfaces, and molecules, (e) an assessment of NAC transferability between three crystal phases of the diisopropylammonium bromide organic ferroelectric, and (f) comparisons between DDEC6 and polarized neutron diffraction atomic spin moments for the Mn12-acetate single-molecule magnet. We find the DDEC6 NACs are ideally suited for constructing flexible force-fields and give reasonable agreement with force-fields commonly used to simulate biomolecules and water. We find the DDEC6 method is more accurate than the DDEC3 method for analyzing a broad range of materials. This broad applicability to periodic and non-periodic materials irrespective of the basis set type makes the DDEC6 method suited for use as a default atomic population analysis method in quantum chemistry programs.
- This article is part of the themed collection: Computational chemistry