journal article Nov 28, 2019

Recent developments in symmetry‐adapted perturbation theory

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Abstract
AbstractSymmetry‐adapted perturbation theory (SAPT) is a well‐established method to compute accurate intermolecular interaction energies in terms of physical effects such as electrostatics, induction (polarization), dispersion, and exchange. With many theory levels and variants, and several computer implementations available, closed‐shell SAPT has been applied to produce numerous intermolecular potential energy surfaces for complexes of experimental interest, and to elucidate the interactions in various complexes relevant to catalysis, organic synthesis, and biochemistry. In contrast, the development of SAPT for general open‐shell complexes is still a work in progress. In the last decade, new developments from several research groups, including the author's, have greatly enhanced the capabilities of SAPT. The new and emerging approaches are designed to make SAPT more widely applicable (including interactions involving multireference systems, complexes in arbitrary spin states, and intramolecular noncovalent interactions), more accurate (enhanced description of intramolecular correlation, a better account of exchange effects, relativistic SAPT, and explicitly correlated SAPT), and more efficient (enhanced density‐fitted implementations, linear‐scaling variants, empirical dispersion, and an implementation on graphics processing units). The new developments open up avenues for SAPT applications to an unprecedented variety of weakly interacting complexes.This article is categorized under:
Electronic Structure Theory > Ab Initio Electronic Structure Methods
Electronic Structure Theory > Density Functional Theory
Molecular and Statistical Mechanics > Molecular Interactions
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Cited By
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International Journal of Quantum Ch...
International Journal of Molecular...
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167
Citations
425
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Published
Nov 28, 2019
Vol/Issue
10(3)
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Cite This Article
Konrad Patkowski (2019). Recent developments in symmetry‐adapted perturbation theory. WIREs Computational Molecular Science, 10(3). https://doi.org/10.1002/wcms.1452
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