The Challenge sought solutions for new uses of publicly accessible digital data to advance materials science and engineering knowledge to accelerate the transition to industrial applications. Kalidindi's winning project "Structure-based energy models from simulated Al grain boundary datasets" proposes new methods to extract information from atomistic simulations to predict the energy of defects in materials.