Project Manager:
Prof. Maria Fyta, PhD

NanoMLmatDesign: Computational design of complex materials: from nanopores to alloys

Principal Investigators:
Prof. Maria Fyta, PhD
Affiliation:
University of Stuttgart
HPC Platform used:
NHR@KIT: HoreKa

An optimum and selective materials design based on computational approaches is essential in order to avoid time-consuming and expensive experiments and drive novel applications in sensing, catalysis, and electronic components. Within this concept, (a) the optimization of nanoporous materials made of functionalized gold surfaces with self-assembled monolayers, as well as (b) the design of alloying materials were investigated. The investigations are directed towards (a) heterocatalysis and biosensing, as well as (b) alloys for strong and highly conducting electronic components were seeked. This research was performed using quantum-mechanical and atomistic simulations occasionally in combination with Machine Learning approaches.

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

Project Manager:
Marcel Sadowski

Ab-initio Modeling of Battery Materials

Principal Investigators:
Prof. Dr. rer. nat. Karsten Albe
Affiliation:
Technische Universität Darmstadt
HPC Platform used:
NHR4CES@TUDa: Lichtenberg Cluster Darmstadt

One approach to the realization of safer batteries relies on all solid-state batteries (ASSB) which use a non-flammable solid electrolyte (SE) instead of the commercial flammable liquid organic electrolytes. While many obstacles to the successful production of these batteries have already been overcome, the inner and outer interfaces in a real battery setup remain a major challenge. Thus, a thorough understanding of the interfacial atomistic processes is crucial, highlighting the value of interface simulations on the atomic scale. Currently, these are only possible via ab-initio methods, such as density functional theory (DFT) calculations, because no classical interatomic potentials exist, which can simultaneously describe the SE and

Materials Science and Engineering abonnieren