With the increasing democratization of computational power, new techniques in data science are accessible to a growing contingent of researchers and hold great promise to accelerate engineering efforts on a variety of fronts. In this talk, I will discuss advancements that need to be made in photovoltaic and energy storage materials to enable solar energy deployment at scales relevant to the climate crisis, and contributions different computational techniques (including simulation such as density functional theory and device modeling as well as “big data” and machine learning approaches) can make to these advances. I will also emphasize the importance of incorporating domain expertise into the application of machine learning methods and maintaining close ties between the theory/computation and experimental communities.
