Research Topics

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Together with our experimental colleagues, we investigate the underlying atomic-scale mechanisms leading to macroscopic properties like formability and toughness. For instance, we can directly probe impact of solute segregation on grain boundary embrittlement, study how dislocations interact with other defects, or investigate precipitate nucleation. Both motivated by and helping to explain experimental observations, we move from the "guess and check" metallurgy of past centuries towards intentional and guided designs for materials withs structural applications. [more]
A prerequisite towards the design of novel materials in the fields of energy efficient optoelectronics, power electronics, catalysis, or superconductivity, is to understand, describe and predict the complex interplay between their structural, thermodynamic, magnetic, optoelectronic and electronic properties. Apart from bulk, interfaces (solid-solid, solid-liquid, and solid-gas) and surfaces, both at the nano- and the micro-meter scales, are of paramount importance in the design and the properties of these materials. Density functional theory calculations constitute the working horse in addressing and exploring the aforementioned interplay. [more]
Defects are crucial in determining materials properties and occur on a wide range of time and length scales, from point defects to extended ones. To simulate the rich world of phase stability, defects, and microstructure, from interstitial doping towards grain boundary mobility, requires advanced and diverse simulation techniques from electronic structure calculations, machine learning, thermodynamic integration and molecular dynamics simulations. [more]
Preventing the failure of structures and components is at the heart of materials science. Failure can take different forms, including corrosion, brittle fracture and ductile failure as well as combinations thereof, and strongly depends on the loading regime (e.g., creep, fatigue) and the surrounding media as evidenced e.g., by liquid metal or hydrogen embrittlement. We utilize and combine various methods such as ab initio based modelling (DFT, ab initio MD, ab initio thermodynamics) and semi-empirical as well as machine learning potentials for large-scale atomistic simulation methods (e.g., MD, kMC, NEB) to study the fundamental failure mechanisms at the atomic and microstructure level. The so-gained understanding not only enables a targeted design for improved materials performance and weight reduction, but also contributes to better material models and design guidelines, thereby laying the foundations for a more sustainable use of materials. [more]
The digitalization of materials science and engineering is currently addressed with high priority worldwide. The FAIR handling of data, i.e. making them findable, accessible, interoperable and reusable, is also within the CM department a major driving force for novel digitial concepts and software developments. The employment of the integrated development pyiron is a central activity in this regard. The activities of the CM department are embedded in large-scale collaborative initiatives like Plattform MaterialDigital and NFDI-MatWerk. [more]
Most phenomena relevant for material science are best targeted by specific theoretical frameworks and simulation methods. For realistic description of material behavior, the department develops new schemes to couple elementary approaches and study their interplay in a systematic way. [more]
This is an unsorted list of older projects. [more]
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