Abstract
The valuable information of catalysis for the past century has been the composition and structure of high-performing catalytic materials. But a new class of programmable catalysts that change the electronic characteristics of their active sites on the time scale of the surface reaction are changing the catalyst design process by requiring additional information describing the input program that directs the temporal changes in the catalyst surface. Catalyst programs vary in complexity associated with the number of combined waveforms required to optimize surface chemistry rates and selectivity to products. The path forward for writing and optimizing catalyst programs will combine together the methods of parameter screening, rational design based on molecular models, and machine learning. This new approach to catalysis will change the nature of catalysis science, with researchers pursuing dynamic catalytic programs with improved catalytic performance over static catalyst compositions.