Catalysts are the materials that allow the production of critical substances that make modern life possible. The project team will focus on model reactions, relevant to hydrogen production and methanol synthesis, which can be promoted at multifunctional interfaces. This project will develop new molecular modeling strategies, relying primarily on ab-initio methods, to rapidly evaluate the catalytic properties of many combinations of metal/oxide interfaces for the reactions of interest. The team proposes to make accurate predictions from a combination of experiments with atomic-level resolution and modeling using large-scale computing. Such predictive techniques have been explored for simple classes of catalytic materials, such as highly ordered metal or oxide surfaces. Promising candidates to emerge from these computational screening studies will then be synthesized using techniques that permit control of the catalyst structure at the atomic level. The catalytic and structural properties of these catalysts will be verified experimentally at atomic resolution, and the resulting information will be used to improve the predictive models and to further refine the candidate materials. The end goal is a method of broad applicability that can be used to design breakthrough multifunctional catalytic materials for a variety of reactions of scientific and economic importance.