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-group strategies, stereochemical control, and structural optimization, thereby offering both challenge and creative freedom. Downstream, the monomers will be incorporated into PNA/γPNA oligomers
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remanufactured. The established process is optimized considering the chemical process solutions during electrode washing. Finally, the process is evaluated regarding potential for scaling to larger battery formats
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expertise from control theory, machine learning, optimization, and network science, spanning diverse application domains such as energy systems, biomedical systems, neuroscience, and safety and security
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advanced electrode materials for aqueous battery applications, and employ various physical characterization techniques (XRD, SEM/TEM, XPS) to investigate their structure and properties. Develop and optimize
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of the active material through an intrinsic buffer effect. The overall aim is to design new materials and optimize fundamental battery performance, as well as to achieve increased mechanistic understanding
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on the technical development and professional understanding of ship performance models and offshore renewable energy. Research topics include: Structural integrity assessment, fatigue, and fracture Collision
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the fundamental links between molecular-level structure and dynamics and the macroscopic properties of materials. Our research focuses on energy-related materials for next-generation batteries, with special
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while optimizing sequence properties. An emerging frontier focuses on designing proteins that act as templates for inorganic interfaces, forming symmetric oligomers that control inorganic material
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demands of both consumers and the food industry, plant proteins must exhibit high nutritional and functional quality, this includes optimal protein composition, a favorable amino acid profile, and
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of proteins with near-atomic accuracy. Models such as RFdiffusion, LigandMPNN, and hallucination-based frameworks can now generate symmetric oligomers, cages, and backbones while optimizing sequence properties