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Assessment of approximate computational methods for conical intersections and branching plane vectors in organic molecules

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

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Gamez,  Jose A.
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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Zitation

Nikiforov, A., Gamez, J. A., Thiel, W., Huix-Rotllant, M., & Filatov, M. (2014). Assessment of approximate computational methods for conical intersections and branching plane vectors in organic molecules. The Journal of Chemical Physics, 141, 124122/1-124122/16. doi:10.1063/1.4896372.


Zitierlink: http://hdl.handle.net/11858/00-001M-0000-0024-07E3-4
Zusammenfassung
Quantum-chemical computational methods are benchmarked for their ability to describe conical intersections in a series of organic molecules and models of biological chromophores. Reference results for the geometries, relative energies, and branching planes of conical intersections are obtained using ab initio multireference configuration interaction with single and double excitations (MRCISD). They are compared with the results from more approximate methods, namely, the state-interaction state-averaged restricted ensemble-referenced Kohn-Sham method, spin-flip time-dependent density functional theory, and a semiempirical MRCISD approach using an orthogonalization-corrected model. It is demonstrated that these approximate methods reproduce the ab initio reference data very well, with root-mean-square deviations in the optimized geometries of the order of 0.1 Å or less and with reasonable agreement in the computed relative energies. A detailed analysis of the branching plane vectors shows that all currently applied methods yield similar nuclear displacements for escaping the strong non-adiabatic coupling region near the conical intersections. Our comparisons support the use of the tested quantum-chemical methods for modeling the photochemistry of large organic and biological systems.