Can range-separated functionals be optimally tuned to predict spectra and excited state dynamics in photoactive iron complexes?

J. Patrick Zobel, Ayla Kruse, Omar Baig, Stefan Lochbrunner, Sergey I. Bokarev, Oliver Kühn, Leticia González, Olga S. Bokareva

Research output: Contribution to journalArticlepeer-review

11 Scopus citations

Abstract

Density functional theory is an efficient computational tool to investigate photophysical and photochemical processes in transition metal complexes, giving invaluable assistance in interpreting spectroscopic and catalytic experiments. Optimally tuned range-separated functionals are particularly promising, as they were created to address some of the fundamental deficiencies present in approximate exchange-correlation functionals. In this paper, we scrutinize the selection of optimally tuned parameters and its influence on the excited state dynamics, using the example of the iron complex [Fe(cpmp)2]2+ with push-pull ligands. Various tuning strategies are contemplated based on pure self-consistent DFT protocols, as well as on the comparison with experimental spectra and multireference CASPT2 results. The two most promising sets of optimal parameters are then employed to carry out nonadiabatic surface-hopping dynamics simulations. Intriguingly, we find that the two sets lead to very different relaxation pathways and timescales. While the set of optimal parameters from one of the self-consistent DFT protocols predicts the formation of long-lived metal-to-ligand charge transfer triplet states, the set in better agreement with CASPT2 calculations leads to deactivation in the manifold of metal-centered states, in better agreement with the experimental reference data. These results showcase the complexity of iron-complex excited state landscapes and the difficulty of obtaining an unambiguous parametrization of long-range corrected functionals without experimental input.

Original languageEnglish
Pages (from-to)1491-1502
Number of pages12
JournalChemical Science
Volume14
Issue number6
DOIs
StatePublished - 12 Jan 2023

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