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Principal interacting orbital: A chemically intuitive method for deciphering bonding interaction

出版社

WILEY
DOI: 10.1002/wcms.1469

关键词

bonding theory; electronic structure; orbital interaction; principal interacting orbital

资金

  1. Research Grants Council, University Grants Committee [HKUST 16305119]

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Modular bonding picture is a central part of chemical understanding as exemplified by the wide usage of Lewis structure as a chemical language to describe molecular electronic structures. A chemically intuitive bonding picture requires the descriptors to be localized and transferable. Molecular orbitals directly derived from quantum calculations are too delocalized to interpret in this regard, hence many efforts have been devoted to the development of bonding analysis methods. After a brief overview of various bonding analysis methods, this review outlines the framework of principal interacting orbital (PIO) analysis and presents its role in recovering intuitive chemical concepts and producing modular bonding pictures. The PIO analysis identifies the most important fragment orbitals that are involved in fragment interactions and characterizes a one-to-one orbital interaction pattern that underlies a unique set of bonding and anti-bonding orbitals derived from pairwise orbital interactions between two fragments. By making use of the principal component analysis (PCA), PIO analysis can effectively combine complex delocalized interaction patterns involved in numerous molecular orbitals into a handful of localized PIOs to provide easily interpretable results with intimate connection to localized chemical concepts, while maintaining necessary delocalized features when dealing with systems that involve mutlicentered interactions such as cluster compounds and various reactions. Such adaptability guarantees the robustness of PIO analysis with respect to change of substituents and the transferability of obtained PIOs across different systems. This article is categorized under: Structure and Mechanism > Molecular Structures

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