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We are an interdisciplinary computational research group in the Department of Materials Design and Innovation at the University at Buffalo. We build physics-informed, data-driven machine-learning methods to capture the fundamental laws of materials thermodynamics and surface kinetics from atomistic simulations and characterization data and empower all group members to construct materials-centric solutions for the most urgent societal challenges, such as climate change, pollution, energy poverty, and food insecurity.
