Velazquez Musgrave JACS

Machine learning-assisted discovery of chevrel phase tellurides

In a recent JACS article, the Velázquez lab, in collaboration with the Musgrave lab from the Department of Chemical and Biological Engineering at University of Colorado Boulder, showcased an interpretable machine-learned descriptor (Hd) capable of estimating decomposition enthalpy (ΔHd) to identify synthetically accessible molybdenum chalcogenides within the Chevrel Phase (CP) family from a set of 205,548 different CP compositions. Five new CP tellurides were identified with this descriptor and successfully synthesized using a microwave-assisted solid-state approach, doubling the number of previously identified metal-intercalated phases for the CP tellurides. The Velázquez lab was also able to experimentally confirm computational predictions regarding cavity occupancy as a function of metal intercalant for the CP tellurides synthesized. The results of this work provide a joined computational and experimental approach that can be applied for the discovery of other multinary materials that have shown promise in energy conversion and storage applications.

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