Designing materials acceleration platforms for heterogeneous CO₂ photo(thermal)catalysis

Materials acceleration platforms (MAPs) combine automation and artificial intelligence to accelerate the discovery of molecules and materials. They have potential to play a role in addressing complex societal problems such as climate change. Solar chemicals and fuels generation via heterogeneous CO2 photo(thermal)catalysis is a relatively unexplored process that holds potential for contributing toward an environmentally and economically sustainable future and is therefore a very promising application for MAP science and engineering. Here, we present a brief overview of how design and innovation in heterogeneous CO2 photo(thermal)catalysis, from materials discovery to engineering and scaleup, could benefit from MAPs. We discuss relevant design and performance descriptors and the level of automation of state-of-the-art experimental techniques, and we review examples of artificial intelligence in data analysis. Based on these precedents, we finally propose a MAP outline for autonomous and accelerated discoveries in the emerging field of solar chemicals and fuels sourced from CO2 photo(thermal)catalysis.