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Performance of density functional theory and orbital-optimised second-order perturbation theory methods for geometries and singlet–triplet state splittings of aryl-carbenes

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Ghafarian Shirazi,  Reza
Research Group Pantazis, Max-Planck-Institut für Kohlenforschung, Max Planck Society;

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Pantazis,  Dimitrios A.
Research Group Pantazis, Max-Planck-Institut für Kohlenforschung, Max Planck Society;

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Neese,  Frank
Research Department Neese, Max-Planck-Institut für Kohlenforschung, Max Planck Society;

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Citation

Ghafarian Shirazi, R., Pantazis, D. A., & Neese, F. (2020). Performance of density functional theory and orbital-optimised second-order perturbation theory methods for geometries and singlet–triplet state splittings of aryl-carbenes. Molecular Physics, 118(21-22): e1764644. doi:10.1080/00268976.2020.1764644.


Cite as: http://hdl.handle.net/21.11116/0000-0007-64F6-3
Abstract
Carbenes are challenging molecular species for quantum chemistry because of the energetic proximity of their singlet and triplet spin states and the sensitive dependence of spin-state energetics on the geometry of the carbene site. Here we use an extended set of aryl-carbenes to evaluate the performance of density functional theory (DFT) approximations as well as of wave function based perturbation theory approaches (orbital-optimised perturbation theory methods OO-MP2 and OO-SCS-MP2) against reference coupled cluster calculations with singles, doubles and perturbative triples conducted with the aid of the domain-based local pair natural orbitals approach, DLPNO-CCSD(T). In addition to the expected functional dependence, our results document a remarkable discordance in the performance of DFT methods in the sense that the functionals that yield the best geometries do not coincide with those that provide the best spin-state energetics. Analysis of the results allows us to propose a series of methods that are expected to perform reliably within certain confidence limits for the title systems. Additionally, methodological issues regarding the reference singlet–triplet gaps obtained by the DLPNO-CCSD(T) approach are discussed.