Prof. Dr. Christopher Künneth, Chair of Computational Materials Science, and his team are working on the ERDF-funded project “EVIDENZ: Efficient Experimental Design through Intelligent Data Analysis and Experimental Collaboration”. The project focuses on AI-supported materials development. The goal is to create an AI platform that optimises materials development and production processes in companies. Using AI can significantly reduce experimental effort, waste, and resource consumption. The platform is designed to be user-friendly even for those without IT expertise, and will offer machine integration and a generative AI-based chat assistant. For maximum data security, the platform can be operated on company-owned servers. These more efficient development processes will substantially enhance the competitiveness of participating companies. Prof. Künneth has been awarded €500,000 in funding for the project.
The project “ASSiST – Automated Simulation Control through Intelligent Language and Text Models”, led by Prof. Dr.-Ing. Stephan Tremmel, Chair of Engineering Design and CAD, is receiving over €817,000 in funding. The multimodal AI model ASSiST aims to make complex simulation processes—such as stress analysis of components or materials optimisation—more accessible and efficient. The research focuses on automated simulation control using intelligent language and text models, which will simplify access for non-experts and support experts by enabling faster creation and evaluation of simulations. The particular strength of AI lies in its ability to be personalised to the individual needs and limitations of users. This is especially important in light of the general shortage of skilled workers and increasing pressure to innovate. Once the developed technologies are transferred into the business processes of partner companies, ASSiST is expected to help SMEs advance their digitalisation and create added value.
Prof. Dr. Thomas Scheibel’s Biomaterials research group is receiving approximately €1.3 million for the project Bi3DAN – Additive Manufacturing of Hierarchically Structured 3D Scaffolds for Biomedical Applications and Bioanalytics. By combining 3D bioprinting, light-controlled printing (xolography), the production of endless nanofibers (electrospinning), and self-organising nanohydrogels made from biotechnologically produced spider silk proteins, a versatile platform is being developed. This platform enables the construction of stable and functional hierarchically structured scaffold matrices that can be individually customised, making them particularly suitable for personalised medicine. The scaffolds can also be modified and used in new biosensor systems due to their high sensitivity and precision. The project is led by the Biomaterials research group at the University of Bayreuth, where the research, modification, analysis, and processing of spider silk proteins and the resulting scaffold structures take place. The research group is supported in its development efforts by SMEs from Bavaria (AMSilk, biovature, naddcon, Neue Materialien Bayreuth, PPprint), from across Germany (FoodQS, Senslab – EKF Diagnostics Company, Xolo), and from the cross-border Danube region (Fyscon/Czech Republic).
