Thermally activated defect tolerance of the oxygen vacancies in CeO2 revealed by machine-learning molecular dynamics
Abstract
Thermal instability and uncontrolled defect dynamics continue to be major obstacles to the reliable functioning of oxide-based energy materials under practical operating conditions. Due to its propensity for reversibly producing oxygen vacancies, cerium dioxide (CeO2) is widely used in energy-related applications; nevertheless, the finite-temperature stability mechanisms leading to vacancy tolerance are still poorly understood. In this work, machine-learning molecular dynamics has been applied to thoroughly examine the dynamical and thermodynamic stability of oxygen vacancies in bulk CeO2 at device-relevant temperatures (300–500 K). By directly linking vacancy formation energetics with finite-temperature lattice dynamics, a quantitative vacancy stability paradigm that encompasses both dynamic resilience and energetic accessibility has been presented. According to our findings, the oxygen vacancies in CeO2 dynamically accommodate lattice distortions and intrinsically modest formation energies, which allow thermal disorders without long-range structural deterioration. Even at high temperatures, the root-mean-square displacement, mean-square displacement, and radial distribution analyses show reduced defect-driven diffusion and maintained crystallinity. We create a hierarchical vacancy stability phase map that outlines a wide defect-tolerant operating window for CeO2 by integrating these descriptors. These findings establish the physical origin of defect tolerance in ceria and provide a material-level framework for the rational design and thermal optimization of defect-engineered oxide energy materials.

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