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This AI-driven methodology goes beyond traditional trial and error by examining vast sets of parameters, collecting data, and then allowing AI to search the material genome to find the best materials for a given application. While the initial application of the data factory will be used to discover new catalysts to make fuel cell vehicles more efficient, TRI and Northwestern believe this method of material discovery will have broad applications in the future, such as clean hydrogen production, CO2 removal from air and high-efficiency solar cells .
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