Prof. Dr.-Ing. habil. Benjamin Klusemann

Innovative lightweight, high-strength, tailored and cost-efficient materials are demanded for the future. Processing conditions play a crucial role for the resulting properties, i.e. formation of microstructure and defects. In this regard, the understanding of process-microstructure-property-performance relations for different materials and processes is of crucial importance in order to develop tailor-made (lightweight) materials, to optimize component properties in a targeted manner, to predict product reliability, to reduce development costs and, last but not least, to provide climate- and resource-friendly solution for components along the entire value chain. The incorporation of computer simulations is a key element to accelerate these development processes.

Within the department “Solid State Materials Processing”, we address basic and applied research topics in the fields of solid state joining, processing, additive manufacturing and extrusion. Some of these processes were developed and patented within the department. In this regard, we develop new materials and processes for metallic lightweight materials, especially aiming for sustainable use in the transportation sector. A close correlation between modeling, especially in the context of solid mechanics, and experimental investigations is essential in order to achieve a sound understanding of the process-microstructure-property-performance relationships.

Within my research, the various technological processes represent a core element, where a suitable continuum mechanical description of the material behavior is essential. The chosen modeling approach is based on the specific application, which leads to modeling at different length scales depending on the scientific question. Multiscale modelling, process simulations and machine learning approaches are central elements of my research activities in order to make findings from the micro level usable for the description of macroscopic component properties after processing.

In this regard, we try to shed light on scientific questions from a theoretical point of view by investigating them experimentally, numerically as well as via machine learning approaches, etc. and to apply the gained knowledge to technological problems at the structural level. Only through a combination of the different approaches, the complex interplay of process, microstructure and component properties can be comprehensively understood and applied to industrial relevant technological problems to provide sustainable solutions.