Dr. Jurgens de Lange
University of Pretoria, South Africa
Quantum mechanical modelling of complex chemical systems has never been more accessible due to increasing algorithmic efficiency, hardware capabilities and wide-spread availability of computational skills and training. Unbelievably, coupled-cluster and other multi-determinant electronic structure calculations can presently be performed, almost routinely, on proteins.1 However, the interpretation of quantum chemical wavefunctions still remains a troublesome bottleneck to the wide-spread adoption of theory-first chemistry research. The prevalence of the molecular structure hypothesis (MST) – that molecules are comprised of atoms – are seemingly at odds with the molecular-wide nature of the wavefunction.2 Within the Born-Oppenheimer approximation, this philosophical divide between reductionist chemistry and holistic physics boils down to the mathematical treatment and interpretation of electron delocalization.
We introduce here the Fragment, Atomic, Localized, Delocalized and Interatomic (FALDI)3 density decomposition scheme as a theoretical instrument to bridge the language barrier between chemistry and physics. FALDI asserts that the electron density of an atom-in-a-molecule is simultaneously bounded and fuzzy. We present a mathematical framework for delocalized electron counting, population stockholding and visualization, thereby recovering the MST whilst including all of the information from the molecular wavefunction. FALDI thereby is both a fundamental theory of electronic structure and an interpretative tool with high utility for human and artificial chemists alike.
We present aspects of the theory in a series of fun case-studies to highlight the molecular-wide nature of chemical interactions, including non-covalent interactions in DNA, cooperativity in water clusters and CH---HC interactions in biphenyl.
Keywords: theoretical chemistry, electron delocalization, chemical bond theory, molecular orbitals, quantum chemical topology, non-covalent interactions
References:
[1] Szabó, P. B.; Csóka, J.; Kállay, M.; Nagy, P. R. J. Chem. Theory Comput., 2023, 19, 8166–8188.
[2] Boeyens, J. C. in Bond and Structure Models (pp. 65-101) 2005, Heidelberg: Springer Berlin-Heidelberg, Berlin.
[3] de Lange, J. H.; Cukrowski, I. J. Comp. Chem. 2018, 39, 1517–1530.
Recording:
Virtual Winter School on Computational Chemistry