Project Manager:
Dr. Uwe Gerstmann

Photonic Materials from ab-initio Theory

Principal Investigators:
Prof. Dr. Wolf Gero Schmidt
Affiliation:
Paderborn University
HPC Platform used:
PC2: CPU cluster

Accurate parameter-free calculations of optical response functions for real materials and nanostructures still represent a major challenge for computational materials science. Our project focusses on the development and application of efficient but accurate ab-initio methods that give access to the linear and nonlinear optical spectra. We explore, on the atomistic level, how the material structure, its composition and defects, but also external parameters like stress, temperature or magnetic fields influence the optical response. It thus leads to a better understanding of existing materials and contributes to the design of new photonic materials.

Project Manager:
Prof. Dr. Christof Schütte

Machine Learning and Simulation for pH-Dependent Opioids

Principal Investigators:
Dr. Markus Weber
HPC Platform used:
NHR@ZIB: Lise

Strong painkillers (such as opioids) are essential to medicine. However, they are mostly addictive and have potentially deadly side effects. Simulation and machine learning techniques help in the search for tailor-made active substances that do not have these side effects. The interaction of the various algorithms raises questions about which computer architecture can support the calculations most effectively.

Project Manager:
Marius Trollmann

Resolving the Structure of mRNA-Vaccine Lipid Nanoparticles

Principal Investigators:
Prof. Dr. Rainer Böckmann
Affiliation:
Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen
HPC Platform used:
NHR@FAU: Alex GPU cluster

Lipid nanoparticles (LNPs) are very successfully employed as novel transport vehicles for mRNA vaccines. A major gap in our understanding and thus obstacle for future developments of nanoparticle-mRNA drugs, however, is the lack of a molecular picture and molecular insight into LNPs. In this project we aim to provide unique insight at the atomistic scale into the structure and mechanisms of these carriers.

Project Manager:
Harish Kumar Singh

High Throughput Screening for Spin-Polarized Current in Noncollinear Magnetic Materials

Principal Investigators:
Prof. Hongbin Zhang
Affiliation:
Technische Universität Darmstadt
HPC Platform used:
NHR4CES@TUDa: Lichtenberg Cluster Darmstadt

The spin-dependent transport phenomena in magnetic materials can provide spin-polarized charge current and large pure spin current, which could be achieved premised on two fundamental properties, i.e., anomalous Hall conductivity (AHC) and spin Hall conductivity [1]. The AHC is characterized as a generation of transverse voltage drop or current density (depending on the boundary conditions) originating from the longitudinal electric currents. The existence of finite AHC in noncollinear antiferromagnets has attracted noticeable attention due to possible applications in antiferromagnetic spintronics for information storage and data processing [2], where the kagome lattice turns out to be an intriguing prototypical lattice to host giant AHC

Atomistic Simulations abonnieren