Optimization-Based Design of Active and Stable Nanostructured Surfaces

Advances in heterogeneous catalysis are being enabled by ever-growing control over the structure of surfaces at the atomic scale. To propose new defected catalytic surfaces, there is a need to systematically search through a combinatorial number of possible atom arrangements. Mathematical optimization is well suited to search this design space with algorithms that provide guarantees of optimality that are not possible with sampling algorithms. In this work, we develop several formulations for catalytic activity and stability as part of mathematical optimization models for designing nanostructured surfaces. Using the oxygen reduction reaction as an example, we show how optimization-based design can be used to efficiently explore the trade-off of activity against stability of surfaces. We furthermore demonstrate how nanostructuring can be applied to increase the expected activity of surfaces under various constraints on the coverage and overbinding of adsorbates. Our approach can be generally applied to other chemistries of interest and is suitably parameterized such that a wide array of systems can be considered, enabling evaluation of the sensitivity of different systems to constraints on the design space.