Research

ESPResSo is a free, open-source software package for simulations of soft-matter systems, which is co-developed and used in the working group for most of its research.

In many systems consisting of soft and biological matter, electrostatic interactions play an important role. For example, synthetic polyelectrolytes (charged polymers), as well as biopolymers such as DNA and many proteins, are highly charged. We develop and employ various coarse-grained simulation methodologies to understand the behavior of charged soft matter systems. A particular focus is the study of weak polyelectrolytes, i.e. polyelectrolytes consisting of weak acid or base groups.

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We apply machine learning to develop interatomic potentials and intelligent solutions to multi-agent reinforcement tasks. Moreover, we investigate neural networks through the lens of physics principles to understand how computers learn and we explore the capabilities of quantum neural networks for time-series predictions.

Biological macromolecules are indispensable for the human body. They serve as energy sources, metabolic helpers, tiny "robots" or means of communication and are crucial for many metabolic processes. Researching them helps to understand diseases and develop medicines more precisely.

Over the last ten years, researchers have developed methods to accurately sequence DNA and RNA at the molecular level. The nanodiag BW future cluster is now endeavouring to extend these techniques to proteins and peptides.

The substance to be analysed is placed in a salt solution that is separated by a lipid membrane with a nanopore. This pore enables the transport of atoms, ions and molecules. An applied electrical voltage causes the transport of ions and the analyte through the pore. The interaction of the analyte in the pore leads to a temporary reduction in the ion current, which is used for the analysis.

The EuroHPC Center of Excellence MultiXscale develops and provides infrastructure, software, and training for multiscale simulations, emphasizing scalable and high-performance coupling of simulation schemes across various length and time scales. The Stuttgart team acts as work package lead and prepares the ESPResSo package for particle-based and lattice-based models at the coarse-grained scale, targeting pre-exascale HPC systems, with a focus on energy materials applications.