To understand and deliberately control the complex relationships between composition, structure, defect chemistry, properties, and functionality of advanced materials, we develop and apply computational methods across the entire materials design chain – from atomic-scale modeling to mesoscale phenomena and macroscopic material response.

At the core of our research lies a fundamental understanding of key mechanisms such as electronic structure, bonding behavior, phase stability, diffusion, dislocation motion, and reaction kinetics. We combine electronic structure calculations based on density functional theory (DFT) with molecular dynamics (MD), Monte Carlo simulations, phase-field modeling, and continuum mechanics approaches. These are further complemented by machine learning techniques for the accelerated exploration of complex materials spaces.

This integrative modeling approach enables us to systematically design novel materials with tailored properties – particularly in the fields of functional thin-film systems, high-entropy materials, energy materials, and oxide or nitride-based diffusion barriers. We view computational materials science not as a replacement, but as a complementary tool to guide the interpretation of experimental results and to efficiently identify promising material combinations.

We need to compute nano!

An atomic-level understanding of the processes occurring under mechanical, thermal, or chemical load is essential for designing hard coatings with precisely tunable properties. Using density functional theory (DFT), molecular dynamics (MD), and other atomistic simulation techniques, we investigate electronic structure, defect mechanisms, phase stability, dislocation motion, and interface reactions at the highest resolution.

We place particular emphasis on the development and optimization of superlattices, high-entropy hard coatings, and nanoscale multiphase coatings. DFT-based predictions of bonding strength, lattice mismatch, and stacking fault energetics enable the rational design of interface architectures that simultaneously enhance strength, hardness, toughness, and thermal stability. Atomistic fracture simulations and failure analyses further provide insights into local mechanisms such as brittle fracture, shear band initiation, or intergranular weakening.

These coating systems are already applied in highly demanding environments – for instance, in cutting tools, engine components, or microelectronic devices – and offer significant potential for emerging applications with added functional requirements, such as hydrogen environments or integrated layer systems in active devices.

Future research will focus on combining DFT, machine learning, and high-throughput experimental approaches to accelerate the discovery and validation of novel material combinations – aiming to develop hard coatings as multifunctional, structurally stable, and application-specific adaptable systems.