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Description of Conical Intersections with Density Functional Methods

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Nikiforov,  Alexander
Research Department Thiel, Max-Planck-Institut für Kohlenforschung, Max Planck Society;

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Thiel,  Walter
Research Department Thiel, Max-Planck-Institut für Kohlenforschung, Max Planck Society;

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Citation

Huix-Rotllant, M., Nikiforov, A., Thiel, W., & Filatov, M. (2016). Description of Conical Intersections with Density Functional Methods. In N. Ferré, M. Filatov, & M. Huix-Rotllant (Eds.), Topics in Current Chemistry (pp. 445-476). Berlin: Springer-Verlag. doi:10.1007/128_2015_631.


Cite as: https://hdl.handle.net/11858/00-001M-0000-0029-04A1-F
Abstract
Conical intersections are perhaps the most significant mechanistic features of chemical reactions occurring through excited states. By providing funnels for efficient non-adiabatic population transfer, conical intersections govern the branching ratio of products of such reactions, similar to what the transition states do for ground-state reactivity. In this regard, intersections between the ground and the lowest excited states play a special role, and the correct description of the potential energy surfaces in their vicinity is crucial for understanding the mechanism and dynamics of excited-state reactions. The methods of density functional theory, such as time-dependent density functional theory, are widely used to describe the excited states of large molecules. However, are these methods suitable for describing the conical intersections or do they lead to artifacts and, consequently, to erroneous description of reaction dynamics? Here we address the first part of this question and analyze the ability of several density functional approaches, including the linear-response time-dependent approach as well as the spin-flip and ensemble formalisms, to provide the correct description of conical intersections and the potential energy surfaces in their vicinity. It is demonstrated that the commonly used linear-response time-dependent theory does not yield a proper description of these features and that one should instead use alternative computational approaches.