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Conical Intersections in Organic Molecules: Benchmarking Mixed-Reference Spin-Flip Time-Dependent DFT (MRSF-TD-DFT) vs Spin-Flip TD-DFT.
Lee, Seunghoon; Shostak, Svetlana; Filatov, Michael; Choi, Cheol Ho.
Afiliação
  • Lee S; Department of Chemistry , Seoul National University , Seoul 151-747 , South Korea.
  • Shostak S; Department of Chemistry , Kyungpook National University , Daegu 702-701 , South Korea.
  • Filatov M; Department of Chemistry , Kyungpook National University , Daegu 702-701 , South Korea.
  • Choi CH; Department of Chemistry , Kyungpook National University , Daegu 702-701 , South Korea.
J Phys Chem A ; 123(30): 6455-6462, 2019 Aug 01.
Article em En | MEDLINE | ID: mdl-31283235
ABSTRACT
The mixed-reference spin-flip time-dependent density functional theory (MRSF-TD-DFT) method eliminates the erroneous spin contamination of the SF-TD-DFT methodology, while retaining the conceptual and practical simplicity of the latter. The availability of the analytic gradient of the energy of the MRSF-TD-DFT response states enables automatic geometry optimization of the targeted states. Here, we apply the new method to optimize the geometry of several S1/S0 conical intersections occurring in typical organic molecules. We demonstrate that MRSF-TD-DFT is capable of producing the correct double-cone topology of the intersections and describing the geometry of the lowest-energy conical intersections and their relative energies with accuracy matching that of the best multireference wavefunction ab initio methods. In this regard, MRSF-TD-DFT differs from many popular single-reference methods, such as, e.g., the linear response TD-DFT method, which fail to produce the correct topology of the intersections. As the new methodology completely eliminates the ambiguity with the identification of the response states as proper singlets or triplets, which is plaguing the SF-TD-DFT calculations, it can be used for automatic geometry optimization and molecular dynamic simulations not requiring constant human intervention.

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2019 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2019 Tipo de documento: Article