We employ advanced scattering techniques like SANS, Neutron-Spin-echo and 3D-scanning SAXS to investigate the structure of proteins and biomimetic lipids and the interplay between them.
We are interested in the fundamental principles behind self-assembly of amphiphilic molecules/materials and how they can be controlled to give rise to emergent properties that enable novel functionalities in nanotechnology, drug delivery systems, and responsive materials.
We synthesize and study polymers with self-healing properties, ion and proton conduction, membrane translocation, and responsiveness to environmental triggers. These advanced materials have applications in automotive transport, energy devices, and smart materials.
In our group, we investigate the parameters and kinetics of different nanoparticle synthesis methods using SAXS/WAXS and TEM.
We develop and apply machine learning/AI methods with the objective of extracting physically and chemically relevant structural and dynamic information from neutron scattering data. Our approach incorporates a diverse range of techniques, including classical machine learning approaches such as Gaussian processes as well as diffusion and large language models.
