We investigate the transport of mobile ions within solid-state ion conductors and their grain boundaries. Our goal is to gain insights into structure-property relations and the behavior of ions at internal and external interfaces.

We develop machine-learning methods to describe the vibrational properties of solid-state ion conductors via Raman spectroscopy.
Hereby, we can understand the effects of mobile ions and defects on experimental Raman spectra, giving atomistic insights that can aid the understanding and development of new materials!

We are interested in developing an understanding of the physics of high-entropy solid-state ion conductors. Herefore, we develop new machine-learning techniques to gain insights into the role of entropy on the functional properties.