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) information on pore distribution and (ii) computational domains to simulate CVI cycles. • Materials studied: Simple and pre-infiltrated fibrous textures using PIP, provided by project partners. • Acquisitions
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experiments, and machine learning (ML) to understand and predict multiscale transport phenomena in fuel cell systems. In particular, the postdoc will bridge pore-scale simulations and macroscale performance
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