Forrest Hyler
University of California, Davis
ABSTRACT
Development of structure-function correlations in energy conversion catalysts is critical to development of active, efficient, and selective catalysts. Exhaustive characterization of both electronic properties and material structure yields feedback towards targeting properties that show promise in electrocatalysis. X-ray absorption spectroscopy has been meticulously performed on Chevrel-phases (MxMo6T8 where M=transition metals, X=1-4, and T=S, Se, Te); which have shown encouraging results as a cathode material for CO2 reduction reaction. Due to the highly tunable structure, Chevrel-phases have been probed to understand how changes such as choice of metal intercalant or chalcogen result in narrowly divergent structures with unique electronic signatures, and structural properties. These results have allowed us to make rational choices towards improvement of catalyst design, and in tandem have habilitated the use of machine learning methods as a platform towards the design of new catalysts with selective properties and applications.
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