How can AI systems better apply their learned behavior to new and previously unknown situations? This is a question to be addressed by Dr. André Biedenkapp in his future research at the Karlsruhe Institute of Technology (KIT). Biedenkapp has been awarded funding for an Emmy Noether Group from the German Research Foundation (DFG) for his research on improved generalizability in reinforcement learning methods and will receive EUR 1.2 million over the next three years. The DFG has committed to further funding of EUR 920,000 for three more years subject to a successful interim evaluation after the initial period.

This research presents a high-performance near-infrared polarized photodetector based on a 1T'-MoTe₂/2H-MoTe₂ homologous polymorphic van der Waals heterojunction. It underscores the significant advantages of utilizing different phases of the same material for designing advanced optoelectronic devices. The findings provide a valuable and generalizable design strategy for developing future integrated, multifunctional sensing, and imaging systems.

Photocatalytic conversion of carbon dioxide to methane offers a promising route for carbon recycling, but its low efficiency and unclear mechanisms limit its practical use. Researchers at Chiba University have now examined how light-driven and heat-driven processes work together in Ru–Ni–ZrO₂ catalysts, achieving record methane production rates. This work clarifies the reaction pathway and highlights new strategies for designing more efficient systems to convert CO₂ into fuels and valuable chemicals.