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Uncovering Clar's aromatic π ‐sextet rule in the Hubbard model using Maximum Probability Domain Partitions
Author(s) -
Van Hende Daria,
Lemmens Laurent,
De Baerdemacker Stijn,
Van Neck Dimitri,
Bultinck Patrick,
Acke Guillaume
Publication year - 2022
Publication title -
journal of computational chemistry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.907
H-Index - 188
eISSN - 1096-987X
pISSN - 0192-8651
DOI - 10.1002/jcc.26806
Subject(s) - domain (mathematical analysis) , quantum chemical , statistical physics , range (aeronautics) , quantum , electronic structure , dominance (genetics) , chemistry , molecule , computer science , computational chemistry , physics , mathematics , quantum mechanics , materials science , mathematical analysis , biochemistry , composite material , gene
Abstract Clar's aromatic π ‐sextet rule is a widely used qualitative method for assessing the electronic structure of polycyclic benzenoid hydrocarbons. Unfortunately, many of the quantum chemical concordances for this rule have a limited range of applicability. Here, we show that the fundamental probabilities associated with a distribution of electrons over domain partitions support Clar's rule in both mean‐field and static correlation regimes. In particular, domain partitions that maximize those probabilities reflect the dominance of Clar structures in the electronic structure of these molecules. These findings suggest that extending methods that aim to maximize probabilities by deforming domain partitions could lead to novel quantum chemical underpinnings for many chemical concepts.

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