Dresden 2017 – wissenschaftliches Programm

Bereiche | Tage | Auswahl | Suche | Aktualisierungen | Downloads | Hilfe

O: Fachverband Oberflächenphysik

O 92: Gerhard Ertl Young Investigator Award

O 92.4: Vortrag

Donnerstag, 23. März 2017, 12:00–12:30, TRE Ma

Towards Accurate Electronic Structure Predictions for Hybrid Interfaces — •David A. Egger — Department of Materials and Interfaces, Weizmann Institute of Science, Rehovoth 76100, Israel

A highly relevant physical quantity for nanostructured molecule-metal interfaces is the energy level alignment of the molecular electronic states with respect to the Fermi level of the metal. Typical density functional theory (DFT) calculations, especially those using local and semi-local functionals, often underestimate level alignment and lead to inaccurate descriptions of electronic structure and charge transport properties of interfaces. Here, we introduce an efficient theoretical method that is based on DFT, but in contrast to common approximations fulfills physically motivated criteria for exchange-correlation interactions relevant for surfaces and interfaces. To this end, we combine the optimally-tuned range-separated hybrid (OT-RSH) functional with a DFT-derived image-charge model to accurately determine level alignment at molecule-metal interfaces in a non-empirical but system-dependent manner.[1,2] We apply our fully self-consistent approach to several physisorbed and chemisorbed molecule-metal interface systems. For both the level alignment and work-function changes, we find that our calculated results are in very good agreement with reference data from photoemission spectroscopy. Our findings indicate new ways of accurate and efficient electronic structure predictions for hybrid interfaces. [1] Egger, D. A.; Liu, Z.-F.; Neaton, J. B.; Kronik, L.: Nano. Lett. 15, 2448 (2015). [2] Liu, Z.-F.; Egger, D. A.; Refaely-Abramson, S.; Kronik, L.; Neaton, J. B.: under review.

100% | Mobil-Ansicht | English Version | Kontakt/Impressum/Datenschutz
DPG-Physik > DPG-Verhandlungen > 2017 > Dresden