Abstract
Ceria (CeO(2)) is renowned for its exceptional oxygen storage capacity, which makes it highly valuable in various applications. Central to its functionality is the migration of oxygen vacancies (V(O)'s). While previous studies have extensively examined the distribution of V(O)'s and Ce(3+) polarons, their kinetic behaviors and interactions, especially in the presence of multiple vacancies, are not yet fully understood. In this study, we employ density functional theory (DFT), ab initio molecular dynamics (AIMD) simulations, and machine-learning methods to investigate these phenomena. Our findings reveal a nonmonotonic temperature dependence of the migration rate of V(O)'s at the CeO(2)(111) surface. Our theoretical model further demonstrates that the migration of V(O)'s and the hopping of polarons are intricately coupled. Notably, frequent polaron hopping at high temperatures hinders V(O) migration, indicating a non-Arrhenius mechanism. This finding is further validated through long-time molecular dynamics simulation enhanced with neural network potentials. Our results provide a microscopic understanding of the interplay between V(O)'s and Ce(3+) polarons, offering crucial insights into the complex dynamics governing oxygen vacancy migration in ceria. This knowledge paves the way for improved material design and functionality.