LATEST RESEARCH RESULTS

Many promising solar and battery materials are not static crystals: their atoms constantly move around with locally breaking symmetries. In this project, Prof. David Egger’s team used the JUWELS computing facility and machine-learning-accelerated simulations to follow these atomic motions and show how they shape light absorption, ion transport and more. Simulating materials accurately from first principles could be a very computationally demanding task. This is where machine-learning algorithms come into play. The work helps explain experimental measurements and points to faster ways of screening energy materials under realistic conditions.

The THESAN-ZOOM project follows the birth and growth of galaxies during the first roughly two billion years of cosmic history, the era when the very first galaxies formed and their light gradually transformed the gas filling the Universe. Using a new generation of computer models that track both matter and radiation, the team followed 14 representative galaxies from their initial formation to their later, more settled states, resolving the individual clouds in which stars are born. The simulations, carried out on the SuperMUC-NG supercomputer at the Leibniz Supercomputing Centre, help astronomers interpret the distant galaxies now being observed in detail by the James Webb Space Telescope.

Predicting how long a drug stays bound to its protein target — the drug residence time — is one of the key challenges in computational pharmacology. Standard molecular dynamics (MD) simulations are inherently serial in time and therefore cannot exploit modern exascale supercomputers to their full potential. This project implemented, optimized, and benchmarked the Metadynamics of Paths (MoP) algorithm — a highly parallelizable path-sampling method — within the widely-used GROMACS biomolecular simulation package.

How can cleaner engines, recyclable fuels, and better battery materials be developed without costly trial-and-error experiments? Researchers at the University of Duisburg-Essen used the HAWK supercomputer to recreate combustion and particle formation processes in unprecedented detail. Their simulations explored hydrogen combustion in engines, recyclable iron fuels, cleaner coal and ammonia combustion, and the formation of nanoparticles for advanced batteries. The project also helped prepare scientific software for the next generation of supercomputers, opening new opportunities for sustainable energy and industrial technologies.

What if the familiar rules of water chemistry break down inside the tiny pockets of a living cell? A team at the University of Duisburg-Essen used the Hawk supercomputer at HLRS Stuttgart to track single protons inside reverse micelles — water droplets just a few nanometres across that mimic the confined environments found in enzymes, fuel-cell membranes and catalysts. The simulations reveal that confinement changes the rules: a proton can stick to the surfactant walls of the droplet, something that does not happen in ordinary bulk water, opening competing pathways that may explain why nature so often does its chemistry in tight spaces.

Roughly one in three new medicines contains fluorine — yet science still cannot fully explain why swapping hydrogen for fluorine in a molecule makes it shun water so strongly. A team at the University of Duisburg-Essen, led by Dr. Ana Vila Verde, used the Hawk supercomputer at HLRS Stuttgart to simulate, atom by atom, how water rearranges itself around fluorinated and non-fluorinated cousins of common solvents. The first results overturn a long-standing assumption: simple gases such as methane are not, in fact, reliable miniature models for understanding fluorine’s water-repelling effect in tomorrow’s drugs and materials.

The matter we are made of are atomic nuclei, which are hold together by the strong force. While the fundamental theory underlying the strong interactions, Quantum Chromodynamics, is well studied at high energies, in the realm of nuclear physics we are dealing with protons and neutrons, that are build of quarks and gluons. However, at the energy scales pertinent to nuclear physics, we can not resolve this substructure. Thus, the proper first principles description of these strongly-interacting many-body systems is based on protons and neutrons, with their interactions consistently given in terms of chiral effective field theory, as initiated by Nobel laureate Steven Weinberg more than three decades ago.

The formation and transport of gas bubbles are crucial in various electrolyzers, flow batteries, and catalytic reactors. Many of these applications employ porous materials, which serve as either catalyst supports or electrodes. Understanding the dynamics of bubble evolution and transport within these porous microstructures is key to optimizing the morphology of the porous materials and enhancing the overall efficiency of these devices. However, this understanding remains limited, largely due to the opacity and complexity of the microstructures, which make it difficult to observe and quantify bubble behavior in real-time.

The EU promotes research in “Green Photonics,” aiming to develop efficient and eco-friendly technologies for energy, lighting, and electronics, aligned with the 2030 target of a 55% cut in greenhouse gas emissions. This drives the search for better illumination systems. White inorganic LEDs, candidates to replace incandescent bulbs and harmful fluorescents, rely on toxic and rare-earth materials, raising sustainability concerns. As an alternative, we propose the bio-hybrid LED (Bio-HLED), which uses fluorescent proteins embedded in polymers. BLOP (theoretically assisted Bio-hLed OPtimization) focused on characterizing its structure and understanding heat-induced degradation to improve stability and performance.

2D materials are one of the important material classes with potential to address problems with conventional semiconducting materials. They possess inherently a thin structure which can be used to manufacture even smaller electronic devices. Even if we know many different 2D materials, the ultimate use of them requires comprehensive knowledge about them and how one can expand their properties. Strain is a versatile tool to adjust 2D materials properties. It can be applied to many 2D materials intentionally, or it can be simply introduced during their synthesis. Understanding the influence of strain in this class provides important information for its employment in novel devices such as spin straintronics.

Quarks and gluons combine in many different ways to form states called hadrons. In recent years, experiments have uncovered exotic hadrons, which do not fit into traditional classifications. Hadrons can be studied using ab initio theory calculations called lattice quantum chromodynamics. In this project, investigations were performed of two different tetraquarks (four-quark systems) containing heavy ‘charm’ quarks.

Materials are made of electrons (negative charges) and nuclei (positive charges). The hydrogen atom is the simplest case: one nucleus and one electron. The behavior of a single electron attracted by a positively charged nucleus is complex, but also well understood: it is the quantum-mechanical version of a planet rotating around the sun. Materials contain many electrons, however. When the number of electrons increases the behavior of a system can radically change. This is because electrons strongly interact with each other: they are all negative charges and thus they try to avoid one another. When electron-electron repulsion effects dominate their behavior, electrons lose their individuality, forming cooperative emergent states.…

In this project, researchers from Fraunhofer IWM and the University of Freiburg explored how materials respond when exposed to harsh mechanical or chemical conditions altering the chemical structure close to the surface. This can lead to high friction and wear but also to unexpected effects or even to beneficial materials modifications. Applications range from machine tools, triboelectricity to functional materials for solar water splitting devices. Large scale quantum mechanical simulations revealed, among other findings, how to predict and understand friction under high pressure - where chemical bonds continuously break and reform - how to hydrogenate titanium dioxide (TiO2) efficiently at room temperature to enhance its functional…

The SunGANBoost project developed advanced deep learning models capable of generating realistic synthetic solar images from multi-wavelength observations. By training large Generative Adversarial, Autoencoder and Diffusion models on data from NASA’s Solar Dynamics Observatory using the JUWELS Booster GPU supercomputer, the team achieved unprecedented fidelity in reproducing solar structures across wavelengths. The resulting models will support future solar physics research, helping scientists better understand and predict solar activity and its effects on space weather.

Researchers from Jülich and University of Milan Bicocca investigated how microorganisms protect themselves from the toxic effects of fluoride. They focused on a protein called Fluc, which creates a tunnel in the membrane to pump fluoride out from bacterial cells. One of the tunnel stations for fluoride contains a protein amino acid, glutamate, which can be negatively charged, as fluoride is. However, two close negative charges would repel each other and bring Fluc to a halt. Such jam could be resolved by either lifting the glutamate barrier out of the way or paying the toll of protonating the glutamate. Preliminary results from multiscale molecular dynamics simulations suggest that both options are feasible.

Researchers at the Institute of Theoretical Physics, Chinese Academy of Sciences, used the JUWELS supercomputer at Jülich Supercomputing Centre to explore how intense laser pulses interacting with plasma can produce spin-polarized particle beams. By performing large-scale particle-in-cell simulations that track both particle motion and spin dynamics, the project uncovered how magnetic fields, radiation effects, and plasma inhomogeneities shape spin polarization—insights that may guide future experiments and applications in high-energy physics and astrophysics.

Zinc(II)-binding proteins play essential roles in biology, but their complex metal coordination is difficult to model accurately. Using an accurate Quantum Mechanics/Molecular Mechanics (QM/MM) molecular dynamics (MD) approach, this study explored the zinc(II) site of the Histone deacetylase protein, revealing detailed electronic and coordination dynamics. Leveraging our in-house MiMiC software on the JUWELS supercomputer, large-scale QM/MM MD simulations were performed efficiently providing insights into metal-ligand interactions that advance our understanding of metalloproteins.

This project uses quantum-powered computer simulations to improve how new drugs are discovered. Traditional simulation methods often fail for complex proteins, especially those with metals or chemical reactions. By combining quantum and classical physics in the newly developed MiMiC framework and running on the JUWELS supercomputer at Jülich, a new Quantum HPC Virtual Screening (QHPC–VS) method was developed. Applied to the mutant IDH1 enzyme linked to brain cancer, it identified 15 potential PET imaging tracers, offering new tools for faster, non-invasive diagnosis.

Within the project we numerically investigated the two-dimensional Bose-Hubbard model with local onsite disorder, where the competition between disorder and short-range interactions leads to the emergence of a Bose Glass (BG) phase between the Mott Insulator (MI) and superfluid (SF) phases [1]. To solve the inhomogeneous system, we employed real-space bosonic dynamical mean-field theory [2], which maps the complicated many-body problem to a collection of numerically solvable impurity models. Within our approach we always find an intermediate BG phase between the SF and MI. Analyzing the spectral function in the strong coupling regime reveals evidence for analytically predicted damped localized modes in the dispersion relation [5].