Lipid nanoparticles (LNPs) are crucial for RNA delivery in gene therapies and vaccines. Our research investigates how LNPs respond to pH changes, with a focus on their structural transitions. By combining molecular dynamics simulations and X-ray scattering experiments, we gain detailed insights into the structural phase transitions between inverse lipid mesophases and explore how structural adaptability influences fusion and release efficiency. This integrated approach advances our molecular-level understanding of LNP dynamics, paving the way for designing more effective gene delivery systems.

Molecular transport through biomembranes allows for selective permeation of small molecules either across the lipid bilayer or through proteins, enabling cells to maintain hydration levels, receive nutrients, and expel metabolic waste while preserving their transmembrane potential and integrity. During controlled cell death the cellular membranes are porated in multiple steps. At first, nanopores allow for water and ion exchange, next inflammation-controlling proteins pass the bilayer, and in the final irreversible step, the membrane is completely ruptured. Molecular dynamics simulations allow us to understand the role of both proteins and lipids in these processes.

This project aims at designing new materials for photocatalytic water splitting. The computational project is closely interlinked with an experimental partner project within the Sonderforschungsbereich 1585. By splitting water into its components hydrogen and oxygen with the help of sunlight, the energy carrier hydrogen can be generated in a sustainable way. Attaching molecular complexes to a semiconductor surface is a key step in the material design. In quantum mechanical simulations that are conducted at NHR Erlangen, we explore material combinations and calculate, e.g., whether certain complexes bind properly to the surfaces. Successful combinations can then be realized in experiment.

Getting the signal across:
A crucial part of cellular physiology is the ability to transmit a variety of stimuli from outside the cell into the cell, triggering the right cellular response to the right stimuli. G-protein-coupled receptors (GPCRs) are a superfamily of proteins evolved precisely for this. Embedded on the cellular membrane, they sense the outside world and couple to G proteins on the inside of the cell. Combining molecular simulation with state-of-the-art biophysical and biochemical experiments we can know, with atomic precision, how this signal gets passed along, and the “routes” that it goes through, opening the possibility for better and newer drug development.

Catalysis at liquid interfaces (CLINT) provides a fascinating new research area with great potential to develop more efficient and sustainable catalytic processes. Since such kind of catalysis, especially those with supported catalytically active liquid metal solutions (SCALMS) and surface catalysis with ionic liquid layers (SCILL), is still quite new, much more understanding needs to be gained on the underlying microscopic steps, leading to the know-how required for a knowledge-based development of highly active catalysts for specific reactions. Periodic density-functional theory (DFT) simulations can shed light on the processes taking place at the catalyst at an atomistic level. Recently, a new approach to generate machine-learning force

Sodium-ion batteries (NIBs) have emerged as a sustainable and economic alternative to Li-ion batteries, addressing critical supply chain and resource challenges. Among the most promising cathode materials is the fluorophosphate Na3V2(PO4)2F3, which demonstrates remarkable capacity retention and rate capability. However, Vanadium creates supply chain issues, driving the exploration of transition metal (M) replacements according to Na3M2(PO4)2F3. Leveraging advanced computational methods such as DFT with r2SCAN functional and NEB calculations, we explore the stability, operating voltage, and crystal structure of such novel materials. Additionally, we explore the thermodynamic stability of different innovative synthesis routes.

Converging calculations is a common need in the ab initio materials-science community.
This tedious and resource-intensive process can be largely avoided if well-validated
recommendations are available. In order to create a recommender system to assist
users, benchmark data are required. This project addresses this need. It evaluates the
convergence behavior of electronic properties for a dataset of 10 materials that are
promising for optoelectronic applications.

IASI (Infrared Atmospheric Sounding Interferometer) and IASI-NG (IASI-Next Generation) are key satellite instruments of the EUMETSAT (European Organisation for the Exploitation of Meteorological Satellites) Polar System. The instruments measure thermal nadir spectra with high spectral and horizontal resolution, twice daily global coverage, and a multi decadal mission continuance. This project explores these excellent opportunities for atmospheric research on different scales by retrieving the distribution of multiple atmospheric trace gases from the measured IASI spectra. The large trace gas data sets are the basis for investigating manifold atmospheric processes on weather as well as climate scales.

The world surrounding us is made of atomic nuclei and nuclear matter. In this project, we investigate such strongly interacting systems under extreme conditions, given by large pressures and densities as they are found in neutron stars and along the edges of the three-dimensional hypernuclear chart, where there is a strong competition between attractive and repulsive forces, requiring high-precision calculations to understand the emergence of the drip lines when protons, neutrons or hyperons are added to a given atomic nucleus.

Photonic materials made of carefully designed structures can manipulate light in extraordinary ways, enabling applications in imaging, sensing, information processing, and beyond. Designing such materials involves solving inverse problems: instead of determining how a given structure interacts with light, we start with a desired optical response and work backward to find the optimal material configuration. This requires advanced numerical approaches, both model- and data-driven, and a high-performance computing infrastructure to efficiently explore vast design spaces and achieve precise control over light propagation. Our NHR project allows us to tackle these challenges.