Minimal-active-space multistate density functional theory for excitation energy involving local and charge transfer states

Ruoqi Zhao, Christian P. Hettich, Xin Chen, Jiali Gao

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4 Scopus citations


Multistate density functional theory (MSDFT) employing a minimum active space (MAS) is presented to determine charge transfer (CT) and local excited states of bimolecular complexes. MSDFT is a hybrid wave function theory (WFT) and density functional theory, in which dynamic correlation is first incorporated in individual determinant configurations using a Kohn–Sham exchange-correlation functional. Then, nonorthogonal configuration-state interaction is performed to treat static correlation. Because molecular orbitals are optimized separately for each determinant by including Kohn–Sham dynamic correlation, a minimal number of configurations in the active space, essential to representing low-lying excited and CT states of interest, is sufficient to yield the adiabatic states. We found that the present MAS-MSDFT method provides a good description of covalent and CT excited states in comparison with experiments and high-level computational results. Because of the simplicity and interpretive capability through diabatic configuration weights, the method may be useful in dynamic simulations of CT and nonadiabatic processes.

Original languageEnglish (US)
Article number148
Journalnpj Computational Materials
Issue number1
StatePublished - Dec 2021

Bibliographical note

Funding Information:
This work was partially supported by grants from the Shenzhen Municipal Science and Technology Innovation Commission (KQTD2017-0330155106581), the Key-area Research and Development Program of Guangdong Province (2020B0101350001), and the National Natural Science Foundation of China (Grant No. 21533003). The study was completed for the excimer complex relevant in photoreceptors at Minnesota, which was partially supported by the National Institutes of Health (Grant Number GM046736). The authors thank Dr. Peng Bao for discussion and assistance. Computing resources were provided by the computing facilities at Shenzhen Bay Laboratory, and part of the computations were performed in 2020 at the Minnesota Supercomputing Institute.

Publisher Copyright:
© 2021, The Author(s).


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