CO2 hydrogenation on Ni(111): microkinetic modelling vs. kinetic Monte Carlo simulations – choosing the right approach for unravelling reaction kinetics†
Abstract
While density functional theory (DFT) provides a very helpful tool for the microscopic domain, kinetic methods that study the evolution of the system with time are needed for the complete study of catalytic systems normally including complex reaction networks. Herein, we study the complex CO2 hydrogenation reaction over Ni(111) under different catalytic conditions by means of two kinetic methods, namely kinetic Monte Carlo (kMC) and Microkinetic Modelling (MkM) simulations. Predictions on relevant macroscopic magnitudes such as turnover frequencies and coverages have been obtained from analysing the two kinetic approaches. Moreover, the reaction mechanisms have been analysed scrutinizing where the differences between the two methods come from. The simulations suggest that, for systems with low coverage of adsorbed species, the MkM approach is a very suitable option. It provides results very similar to those of the more complex kMC simulations but with significantly lower computational cost. Nevertheless, for a deeper understanding of the system's behaviour, spatially resolved kMC simulations are a better choice. Precisely, the use of kMC simulations is of paramount importance when dealing with systems with high coverages in which adsorbate–adsorbate interactions and the topological arrangement of the adsorbates are more influential. MkM simulations that include a lateral potential yield results that align more closely with those of kMC. However, the local considerations in kMC lead to differences in macroscopic properties and reaction mechanisms. These findings are likely applicable to other catalytic systems and aim to guide theoreticians in selecting the most suitable kinetic approach.
- This article is part of the themed collections: UN Sustainable Development Goal 13: Climate Action and UN Sustainable Development Goal 7: Affordable and Clean Energy
 
                




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