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machine learning (ML) approaches offer a powerful framework for modeling complex catalytic materials with near ab initio accuracy while enabling simulations at significantly larger spatial and temporal
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providing reference spectroscopic line-shape data based on experimentally validated ab initio quantum scattering calculations. We will fully utilize capabilities to populate spectroscopic databases and