Ulissi and Facebook AI Create World’s Largest Catalysis Dataset

For decades, the push toward renewable energy sources like solar and wind has necessitated the development of countless technologies. From generation techniques, to power grid infrastructure and storage methods, renewable power development requires innovation from all angles. Today, thanks to the tireless work of researchers and engineers all over the world, methods for generating renewable energy have come a long way. But there are still major barriers to the full implementation of renewables into the power grid. Now, Zack Ulissi has teamed up with Facebook AI Research (FAIR) to break down one of these barriers. Combining the expertise in machine learning, dataset development, and computing power of FAIR with Ulissi's years of prior research using machine learning techniques for novel catalyst discovery, the team is empowering researchers around the world to join in the effort through the Open Catalyst Project, an open effort to produce datasets and models designed to help researchers discover new catalysts for renewable energy storage. This simulation, magnified 108 times, models a typical relaxation between an adsorbate (in color) and a catalyst's surface.