(8h) A Comprehensive DFT-Kmc Approach to Investigate Reaction Kinetics of Heterogeneous Catalytic Reactions

Understanding complex heterogeneous catalytic reactions is essential for developing new catalysts for industrial and environmental applications. However, such reactions are influenced by diverse factors, including the catalyst structure, its electronic properties, thermodynamic stability, and kinetic behavior. Because of this complexity, it is difficult to fully understand or accurately predict catalytic performance. To overcome this challenge, researchers often rely on computational methods such as density functional theory (DFT) and kinetic Monte Carlo (kMC) simulations. DFT provides valuable insights at the atomic scale, while kMC captures reaction dynamics over extended timescales and larger surface areas. Despite their strengths, each method on its own has limitations and cannot offer a complete understanding of catalytic processes. Hence, in this study, we addressed this gap by combining DFT and kMC simulations to gain a more comprehensive understanding of reaction kinetics. Specifically, DFT was employed to investigate the fundamental reaction steps in detail, examining reaction energies, activation barriers, and electronic features such as charge distribution and orbital characteristics. Further, we incorporated its results into a high-fidelity surface reaction kMC model. This integration allowed us to simulate the temporal and spatial evolution of surface reactions. As a result, we were able to trace key kinetic properties such as adsorbate diffusion, surface coverage variations, and turnover frequency (TOF) under realistic conditions, including temperature, pressure, and the influence of the surrounding environment. To demonstrate the utility of this approach, we applied it to the electrochemical nitrogen reduction reaction (NRR), a promising alternative to the energy-intensive Haber-Bosch process for ammonia production. Notably, NRR is a complex reaction that directly competes with the hydrogen evolution reaction (HER) in water solvent environments. By using the integrated DFT-kMC framework, we could extract critical kinetic insights, such as how surface coverage changes over time and how the competition between NRR and HER dynamically changes