Charge transfer excitations from particle-particle random phase approximation-Opportunities and challenges arising from two-electron deficient systems.

Published

Journal Article

The particle-particle random phase approximation (pp-RPA) is a promising method for studying charge transfer(CT) excitations. Through a detailed analysis on two-electron deficient systems, we show that the pp-RPA is always able to recover the long-distance asymptotic -1/R trend for CT excitations as a result of the concerted effect between orbital energies and the pp-RPA kernel. We also provide quantitative results for systems with relatively short donor-acceptor distances. With conventional hybrid or range-separated functionals, the pp-RPA performs much better than time-dependent density functional theory (TDDFT), although it still gives underestimated results which are not as good as TDDFT with system-dependent tuned functionals. For pp-RPA, there remain three great challenges in dealing with CT excitations. First, the delocalized frontier orbitals in strongly correlated systems often lead to difficulty with self-consistent field convergence as well as an incorrect picture with about half an electron transferred. Second, the commonly used density functionals often underestimate the energy gap between the highest occupied molecular orbital and the lowest unoccupied molecular orbital (LUMO) for the two-electron deficient species, resulting in systems with delocalized orbitals. Third, the performance of pp-RPA greatly depends on the energy difference between the LUMO and a higher virtual orbital. However, the meaning of the orbital energies for higher virtual orbitals is still not clear. We also discuss the performance of an approximate pp-RPA scheme that uses density functional tight binding (pp-DFTB) as reference and demonstrate that the aforementioned challenges can be overcome by adopting suitable range-separated hybrid functionals. The pp-RPA and pp-DFTB are thus promising general approaches for describing charge transfer excitations.

Full Text

Duke Authors

Cited Authors

  • Yang, Y; Dominguez, A; Zhang, D; Lutsker, V; Niehaus, TA; Frauenheim, T; Yang, W

Published Date

  • March 2017

Published In

Volume / Issue

  • 146 / 12

Start / End Page

  • 124104 -

PubMed ID

  • 28388105

Pubmed Central ID

  • 28388105

Electronic International Standard Serial Number (EISSN)

  • 1089-7690

International Standard Serial Number (ISSN)

  • 0021-9606

Digital Object Identifier (DOI)

  • 10.1063/1.4977928

Language

  • eng