Computational modelling of CeO2-based catalysts for environmental applications

The global population surge after the second industrialization, coupled with rising living standards, has sharply increased energy demand, still largely met by fossil fuels. Concerns over resource depletion and environmental impact have prompted scientific efforts to find sustainable, alternative energy sources and technologies. Beyond renewables, optimizing industrial processes to reduce energy and emissions is widely supported, with catalysis—a method used in over 90% of chemical industrial processes—playing a key role. Transition metal oxides, particularly heterogeneous catalysts like cerium oxide (CeO₂), are highly valued for their efficiency and reusability. CeO₂ is a cheap and readily available "oxygen storage material" which can easily undergo changes in its oxidation states, making it ideal for catalytic processes. Since its introduction in 1970s automotive converters, CeO₂ has become essential in reducing emissions and is now used in various applications, such as CO oxidation and methane activation. Advances in computational methods, especially Density Functional Theory (DFT), have deepened understanding of the catalytic properties of CeO₂, enabling further research into more efficient catalysts. This thesis applies DFT to analyze CeO₂-based catalysts in three critical reactions of high industrial and environmental interest: methane-to-methanol conversion, CO oxidation, and deoxydehydration (DODH). This work highlights the remarkable properties of CeO₂-based materials, providing insights for developing sustainable catalytic materials for energy and environmental uses.