Project overview

Using a digital twin, the project aims to link the extraordinary properties of microstructures on different length scales. For example, particularly strong materials can be developed with less material input.

Prof. Dr. Frank Pothen, Professor of Economics at the EAH Jena, analyzes the availability of steel scrap as a raw material, among other things to conserve existing resources. His market model incorporates the effect of climate and trade policy.

The Prisma fund enables Prof. Dr. Philipp Seib, Professor of Pharmaceutical Technology and Biopharmacy at the University of Jena, to establish a tailor-made material testing machine for silk fibers in Jena.

The project investigates the mobility of AI specialists in Germany and Europe. Causes are being investigated and fields of action identified. This will lead to the development of effective measures to promote the German and European AI ecosystem.

Engineers with skills in sustainable development are crucial to overcoming future challenges. Eight Thuringian universities are cooperating to anchor sustainability in engineering education.

Dr. Jingyuan Xu is a mechanical engineering scientist in sustainable energy technologies. She holds a PhD from the Chinese Academy of Sciences. After stations at the University of Cambridge and Imperial College London, she moved to KIT in 2021.

How decentralised should data be stored to protect privacy, and how does that affect energy consumption? Conflicts of goals of this kind are analysed in a research centre for machine learning.

In the "Transfer and Competence Centre Industrial AI", potentials and possibilities of the use of AI in production processes of medium-sized companies are researched on the basis of industrial applications.

In the future, universities should increasingly teach "transformative skills for sustainability" - across disciplines and disciplinespecific. Regular expert meetings and curricular workshops are being promoted to anchor the topic in the curriculum.

The Research and Transfer Center bundles competencies between the university, non-university research institutions and industry. Areas are learning systems such as Big Data, Data Science, Machine Learning/AI and Robotics.