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The Heidelberg Academy of Sciences and Humanities awarded the 2026 Ecology Prize of the Viktor & Sigrid Dulger Foundation to Benjamin Schäfer. The sustainable transition of the energy system is challenging as the availability of renewable power sources like solar and wind energy fluctuates greatly. Benjamin Schäfer is therefore working to increase the stability and resilience of the power grid using transparent, explainable AI methods. He combines physical modeling, machine learning, and open data to quantify fluctuations in the energy system and explain their causes. Together with international researchers, he has developed a data-driven load profile that will make it easier to regulate the balance between supply and demand in the future.
Synthetic nanomaterials have emerged as promising alternatives to natural enzymes for catalytic and therapeutic applications. Yet, their limited stability, aqueous compatibility, and catalytic scope impede broader utilization. Pierre Picchetti and his group have now developed biocompatible nanoparticles that provide a robust and sustainable platform for enzyme-like catalysis in water. Their activity can be switched on and off in the presence of chemical signals similar to how nature regulates enzymes. As the nanoparticles are free of metal and well tolerated by living cells, they are suitable for intracellular applications.
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Artificial intelligence (AI) increasingly helps to make power grids more efficient and stable. Especially, in critical infrastructures such as the energy system, AI-supported predictions should be as precise and comprehensible as possible. The working group led by Benjamin Schäfer has, therefore, developed a new method and presented it in the journal Nature Communications: "SHAPformer" combines transformer models - known from modern language models - with explainable artificial intelligence methods and makes visible how individual factors, such as temperatures, holidays or wind forecasts, influence a forecast.
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