Predicting NO_x Catalysis by Quantifying Ce³⁺ from Surface and Lattice Oxygen

Our work introduces a novel technique based on the magnetic response of Ce³⁺ and molecular oxygen adsorbed on the surface of nanoceria and ceria-based catalysts that quantifies the number and type of defects and demonstrates that this information is the missing link that finally enables predictive design of NO_x catalysis in ceria-based systems. The new insights into ceria catalysis are enabled by quantifying the above for different ceria nanoparticle shapes (i.e., surface terminations) and O₂ partial pressure. We used ceria nanorods, cubes, and spheres and evaluated them for catalytic reduction of NO by CO. We then demonstrated the quantitative prediction of the reactivity of nanomaterials via their magnetism in different atmospheric environments. We find that the observed enhancement of reactivity for ceria nanocubes and nanorods is not directly due to improved reactivity on those surface terminations but rather due to the increased ease of generating lattice defects in these materials. Finally, we demonstrate that the method is equally applicable to highly topical and industrially relevant ceria mixed oxides, using nanoscale alumina-supported ceria as a representative case-a most ill-defined catalyst. Because the total oxide surface is a mixture of active ceria and inactive support and ceria is not likely present as crystallographically well-defined phases, reactivity does not easily scale with surface area or a surface termination. The key parameter to design efficient NO reduction in ceria-based catalysts is knowing and controlling the surface localized excess Ce³⁺ ion areal density.