​​Medicines, chemicals, microplastics: even ordinary products can leave a dangerous mark on our environment. “Wastewater is like a mirror of our society,” says Prof. Dr. Matthias Kohl, head of the Data Science for Life Sciences research group at Furtwangen University. Together with PolymerActive GmbH, his team investigates how artificial intelligence can transform microplastic particles into precise “pollutant magnets” that selectively remove harmful substances from water. A new research project led by Prof. Dr. Magnus Schmidt takes this idea even further. The aim is to design the particle surface in a way that certain pollutants bind particularly well, while others hardly attach at all. “Ideally, we want to build a pollutant magnet that only likes certain adhesive partners,” says Schmidt. In this way, AI can help to remove pollutants from water more precisely – contributing to the protection of both the ecosystem and human health. 

Find out more here.

​The research project “MoDe_ProBio” revolutionizes biochemical processes for a sustainable future. Using digital twins and artificial intelligence, innovative methods are developed to utilize biogenic raw materials and waste more efficiently. The aim is to significantly reduce development times and resource consumption while evaluating the sustainability of new processes early. A key example is using engineered E. coli to produce PETase enzymes that break down plastics. Coordinated by Prof. Dr. Volker C. Hass at Furtwangen University, a strong network of universities and industry partners is working together to advance the bioeconomy. The results could serve as a model for the circular economy and trigger sustainable changes in industry and education. This will set new standards for the environmentally friendly production of enzymes, biohydrogen, and specialty chemicals and demonstrates how digital tools can transform biotechnological process design for a greener future. 

Find out more here.

In industry, many machines exist twice: once in reality and once as a digital copy—the so-called digital twin. For companies to use these digital twins safely, their data must be reliable and tamper-proof. A recent research project of Prof. Dr. Christoph Reich at Furtwangen University is tackling exactly this challenge. The project team is developing a digital machine passport that uses the Ethereum blockchain to protect key information such as technical data, maintenance history and, as a special feature, also detailed CO2 emission data over the entire life cycle. This makes data exchange between companies more trustworthy, transparent and sustainable. 

You can learn more about the project here.