When modeling inorganic/organic interfaces with density functional theory (DFT), the outcome often depends on the chosen functional. Hybrid functionals, which employ a fraction of Hartree-Fock exchange α, tend to give better results than the more commonly applied semilocal functionals, because they remove or at least mitigate the unphysical electron self-interaction. However, the choice of α is not straightforward, as its effect on observables depends on the physical properties of the investigated system, such as the size of the molecule and the polarizability of the substrate. In this contribution, we demonstrate this impact exemplarily for tetrafluoro-1,4-benzoquinone on semiconducting (copper-I-oxide Cu2O) and metallic (Cu) substrates and explore how the simulated charge transfer depends on α. We determine the value α∗ that marks the transition point between spurious over-localization and over-delocalization of charges. This allows us to shed light on the interplay between the value of α∗ and the physical properties of the interface. We find that on the inert semiconducting substrate, α∗ strongly depends on surface screening. Furthermore, α has a significant impact on the amount of charge transfer and, in particular, the charge localization. Conversely, for the adsorption on Cu, α affects only the amount of transferred charge, but not its localization, which is a consequence of strong hybridization. Finally, we discuss limitations to the predictive power of DFT for modeling charge transfer at inorganic/organic interfaces and explain why the choice of a "correct" amount of Hartree-Fock exchange is difficult, if not impossible. However, we argue why simulations still provide valuable insights into the charge-transfer mechanism at organic/inorganic interfaces and describe how α can be chosen sensibly to simulate any given system.
ASJC Scopus subject areas
- !!Electronic, Optical and Magnetic Materials
- !!Physical and Theoretical Chemistry
- !!Surfaces, Coatings and Films
Fields of Expertise
- Advanced Materials Science