CAREER: Computational Design of Single-Atom Sites in Alloy Hosts as Stable and Efficient Catalysts

Tulane University, New Orleans LA

Investigators

Abstract

Oxidation and alkane conversion reactions are widely used in the chemical process industry to produce a broad range of products. Collectively, those products amount to over $100B scale and produce hundreds of megatons CO2-equivalent of greenhouse gases (GHGs). The project focuses on the discovery and design of improved catalysts for these reactions, which translates to improvements in process efficiency, more favorable economics, and reduction in GHG emissions. Recently, single-atom alloy (SAA) catalysts have shown great promise for a number of reactions; however, conventional SAAs—which consist of one metal doped as isolated atoms into a second metal—comprise a fairly small design space, which limits our ability to tailor them for a given reaction. The project will address this limitation by employing computational and machine learning tools to theoretically screen alloy-host SAAs to identify stable and active catalysts for oxidation and alkane conversion reactions. The most promising candidates will be synthesized, characterized, and tested experimentally, thus avoiding tedious trial-and-error catalyst design, and opening the door to widespread application of alloy-host SAAs across a broad range of chemical reactions. Educational benefits include the development of learning modules that will enhance the technical writing skills of engineering students. In this project, machine learning and density functional theory will be used to screen alloy-host SAAs to identify stable and active catalysts for oxidation and alkane conversion reactions. This will be followed by collaborative surface-science studies with well-defined materials, and finally translation of the most promising candidates to nanoparticle catalysts. Notably, alloy-host SAAs can give both facile activation of reactants and weak binding of downstream intermediates; this desirable combination of properties is not achievable by many traditional metal catalysts. Therefore, developing and applying effective design strategies for achieving both attributes, as well as stability, can aid in developing improved catalysts for a wide variety of different reactions. The learning modules that will be developed for technical writing are critical because many surveys of engineering employers have clearly shown that technical communications skills (including technical writing) are lacking in recent engineering graduates. In particular, the modules will provide multiple levels and sources of feedback on drafts of technical writing, leveraging well-established principles from research on skill improvement. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.