Previously introduced Adaptive Natural Density Partitioning algorithm (AdNDP) is a novel approach for the analysis of electron density function. This method allows obtaining a compact, intuitively simple description of the chemical bonding in molecules with non-classical bonding pattern. This method has found wide application in various fields of chemical science, since by using that tool the researcher could obtain comprehensive chemical bonding picture for truly complicated cases.<br/>In the course of our work we extend an applicability of AdNDP method by the incorporation of novel features such as: distance restrictions, symmetric direct search, correction of the occupancy numbers, bonding analysis for open shell cases and excited states bonding analysis. All described improvements are successfully implemented in a novel AdNDP 2.0 code. Such extension of the method allowed us to decipher chemical bonding of various nontrivial systems. We separate our results on three main parts: the chemical bonding of the excited state molecules, spherical aromaticity of Zintl clusters, and local σ-aromaticity of metal clusters. For all those cases we obtain clear and comprehensive bonding patterns, which we are going to discuss further.

AdNDP 2.0: Flexible and efficient way of chemical bonding deciphering in novel clusters and solids

2019 Fall National Meeting

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