Our research uses computational chemistry to model transition metal-based electrocatalysts that convert greenhouse gases such as CO2 into valuable products and synthetic precursors, like CO. Electrocatalytic CO2 conversion is promising for climate change mitigation and sustainable energy production, but has yet to reach industrial viability. To design a catalyst with excellent activity, selectivity, efficiency, and stability, we use computational methods to further understand electrocatalysts synthesized by experimentalists and use those insights to guide the design of future catalysts. 

Part of this approach involves taking inspiration from nature - microorganisms contain enzymes that perform these conversions remarkably, and have been studied as exemplary models for catalyst engineering. These enzymes contain multilayered structures with various components that synergistically facilitate catalysis. Computational chemistry is a valuable tool for exploring how to emulate and incorporate these elements when developing electrocatalysts.