Brittany Haas, an outstanding 5th-year graduate student in the Sigman Group, was recently published in the Journal of the American Chemical Society (JACS). The publication was on a method development project that was a collaborative effort of the Sigman Group at the University of Utah, the Toste Group at UC Berkeley, the Miller Group at Yale University, and Genentech.

The project used data science from the outset to streamline the identification of an optimal catalyst and explore substrate scope in order to assess the generality of the method. Haas states, “this is a great example of how computational/data science chemists can help experimental chemists in the lab.”