Traditional methods of catalyst synthesis and testing are slow and inefficient, particularly in heterogeneous systems where the structure of the active sites is typically complex and the reaction mechanism is at best ill-defined. While theoretical modeling and a growing understanding of fundamental surface science help guide the chemist in designing and synthesizing targets, even in the most well understood areas of catalysis, the parameter space that one needs to explore experimentally is vast. The result is that the chemist using traditional methods must navigate a complex and unpredictable diversity space with a limited data set to make discoveries or to optimize known systems.
We describe here a mature set of synthesis and screening technologies that together form a workflow that breaks this traditional paradigm and allows for rapid and efficient heterogeneous catalyst discovery and optimization. We exemplify the power of these new technologies by describing their use in the development and commercialization of a novel catalyst for the hydrodesulfurization of gasoline distillates having 50% more selectivity and 30% more activity for sulfur removal than the state-of-the-art commercial reference.