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is to develop RL controllers that can learn from data while guaranteeing stable and safe operation in complex, nonlinear systems such as chemical plants and energy processes. By validating the approach
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the largest FTD and AD patient-control cohorts, including neuropathologically well-characterized patient subgroups. The project will further leverage large publicly available and in-house generated single
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infrastructure and training in plasma science, advanced catalysis, digital process control, and sustainability assessment, carrying out cutting-edge research with academia and industry. PRIME LEAP offers
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applications which is hindered by the lack of a molecular understanding of their formation process. This is particularly true for zeolite synthesis which is characterized by a very complex reaction network in
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-metallic clusters that combine plasmonic and catalytic metals These clusters will be deposited with high control over size and composition using cluster beam deposition on morphologically engineered TiO2