Digital Technologies

Programme area V - Digital Technologies was founded at the Leibniz-IWT in 2025. Its aim is to implement digital technologies in materials-oriented production and accelerate the development of new materials. The associated team deals with various digitization-relevant topics and forms a cross-section of the existing program areas I - Materials Engineering, II - Process Engineering, III - Manufacturing Technologies and IV - Materials Testing.

The focus is on
 

• Materials modeling and simulation 
  This includes the application of multi-scale modeling methods (from nano to macroscopic level) along the entire process chain, with a particular focus on additive manufacturing. The approach of computer-aided high-throughput screening is pursued, which is combined with the institute's existing expertise in experimental methods. This allows existing parameters, including those of materials used in industry for many years, to be further optimized and new materials and processes to be developed. 
   
• Digitalization 
  Digitalization is an important process in today's world and has the potential to massively accelerate materials development through the access, organization and use of data, including historical information. This topic is already a focus of research at the institute and is thus an integral part of awareness along the entire process chain. The outlook lies in the development of digital shadows and twins as well as in the analysis, control and optimization of production-relevant processes, which will enable significant improvements in material properties.  
   
• Machine learning and artificial intelligence 
  In order to use existing research data effectively, artificial intelligence methods, in particular machine learning, are applied in combination with the Institute's expertise. The focus of the research is on understanding the relationships between the manufacturing processes, the material structure and its properties. Various approaches are used here, with symbolic regression playing a special role in this research focus due to its methodological characteristics.

The area is currently undergoing major expansion and is looking forward to collaborations with research and industry!
 

D05: Symbolic Regression for Materials Science and Engineering" at MSE 2026 - register now and join in!

The project, which is funded by the Leibniz Professorship Program, relies on simulation to reduce experiments and save resources in the development of new materials. A particular focus is on the integration of innovative AI-based modeling for material design, for example in additive manufacturing.