CDS&E: Deconvoluting the Competing Effects of Amorphous Metal Catalysts for CO2 Electrochemical Reduction

Heterogeneous catalysts are solid materials that facilitate the transformation of raw chemicals into useful products. Commonly, catalysts are metals with atoms arranged in ordered, repeating patterns—called crystalline structures. However, recent findings show that when these atoms are arranged randomly, in a so-called amorphous structure, the catalysts more effectively convert the raw chemicals into the desired product. This discovery opens the door to more energy-efficient and cost-effective chemical production, yet scientists still do not fully understand why the lack of atomic order improves the reaction rates. This project seeks to uncover how atomic disorder in amorphous catalysts increases reaction rates and selectivity, using the hydrogenation of carbon dioxide, i.e. the conversion of carbon dioxide and water into valuable fuels, over copper as a test case. By exploring how carbon dioxide and water interact with both ordered (crystalline) and disordered (amorphous) copper surfaces, the project aims to identify the atomic structures that make reactions faster and more efficient. Highly accurate computer simulations of atomic behavior and molecular transformation will map copper atom structure characteristics to chemical reactions and their barriers. Thus, it will provide the structure-activity relationships needed to develop new high performance amorphous catalysts. This work supports the NSF mission by deepening our understanding of fundamental chemical processes on complex materials and contributes to national interest by providing strategies to reduce the energy and cost of chemical manufacturing. It also advances education through the training of graduate students in catalysis and computational modeling and the organization of outreach activities that introduce students to engineering research. Despite their promise, amorphous catalysts are far less studied than their crystalline counterparts due to the difficulty of analyzing their complex disordered structures. This project aims to determine how disordered surfaces, water arrangement on said surfaces, and metal composition affect the activity and selectivity of amorphous copper catalysts in the electrocatalytic reductive conversion of carbon dioxide into valuable, higher-order (C2+) hydrocarbons. Using a machine-learning-accelerated computational approach, the researchers will develop highly accurate models based on quantum mechanical calculations. These models will calculate the minimum energy pathways of elementary reaction steps of electrochemical CO2 hydrogenation. The resulting minimum energy path reaction energetics and product distributions will reveal the effects of amorphous copper surface structures and the associated local water arrangements on catalytic performance. This data will be used to build structure–activity relationships, guiding the design of next-generation amorphous catalysts. This project will advance the broader field of catalysis by clarifying how catalytic site distribution of amorphous materials, and water structure influence reaction pathways. These findings have significant implications for the many reactions where water is present, and structures are disordered. Even more broadly, the computational approach developed here provides a generalizable method for studying amorphous materials, supporting their study and use in a wide range of applications such as energy storage, low-energy separations, and corrosion-resistant systems. 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.