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Electrochemically converting carbon dioxide to useful fuels and chemicals could contribute to a circular economy that will curtail unsustainable fossil fuel burning and decrease future greenhouse gas emissions. However, the lack of practical electrocatalysts impedes the further development of this carbon-neutral technology. Our group use quantum mechanics (density functional theory, high-level embedded correlated wavefunction theory, and machine learning) to design electrocatalysts, including single-atom catalysts embedded in graphene, single atom alloys, and metal surfaces, for electrochemical CO2 reduction reaction (CO2RR). We also combine state-of-the-art computational tools to enable accurate and high-throughput mechanistic analysis of CO2RR. 

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Ammonia is a critical component in fertilizers and an ideal zero-carbon energy carrier, yet the conventional energy-intensive Haber-Bosch production process consumes enormous fossil fuel resources and generates massive carbon dioxide emissions. An alternative and environmentally sustainable way to produce ammonia is through electrochemical nitrogen reduction reaction (NRR) using excess renewable electricity, either from a direct electrocatalytic reduction or lithium-mediated electroreduction. We use computational methodologies to understand the fundamental chemistry in lithium-mediated NRR and develop design principles to improve its reactivity. We also work on designing novel multifunctional catalysts for direct electrocatalytic NRR. 

Heterogeneous catalysts are crucially important in many practical chemical applications. Rational design of efficient catalysts necessitates a fundamental understanding of reaction mechanisms. Short-lived reaction intermediates and active sites challenge the resolution of spectroscopy, making mechanistic analysis from quantum mechanical simulations essential. However, the conventional computational tool (i.e., density functional theory or DFT) to simulate heterogeneous catalysis suffers from self-interaction error, electron delocalization error, and single-reference description of the electronic structure, which are especially problematic for modeling charge transfer processes and the most compelling materials with transition metals involved. We are working on developing more qualitatively and quantitatively reliable quantum mechanical methods that goes beyond conventional DFT to enable rigorous prediction of kinetics in heterogeneous catalysis. 


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