Understanding the ionic conductivity maximum in doped ceria: trapping and blocking.

Area of Science:

• Materials Science
• Electrochemistry
• Computational Physics

Background:

• Solid oxide fuel cells (SOFC) and solid oxide electrolysis (SOEC) require electrolytes with high oxygen ion conductivity and low electronic conductivity.
• Rare-earth doped ceria are promising candidates for these electrolytes due to their potential ionic conductivity.
• Predicting ionic conductivity and understanding atomistic mechanisms are crucial for advancing sustainable energy technologies.

Purpose of the Study:

• To investigate the relationship between microscopic defect interactions and macroscopic oxygen ion conductivity in doped ceria.
• To predict oxygen ion conductivity as a function of doping concentration using advanced simulation techniques.
• To elucidate the roles of 'blocking' and 'trapping' effects of dopants on ionic conductivity.

Main Methods:

• Utilized ab initio density functional theory (DFT) to calculate migration barriers and energy contributions.
• Employed Kinetic Monte Carlo (KMC) simulations to predict ionic conductivity based on DFT results.
• Analyzed dopant-vacancy interactions and their influence on oxygen vacancy migration.

Main Results:

• Quantified the 'blocking' effect, which influences the dopant concentration for maximum ionic conductivity.
• Characterized the 'trapping' effect, which limits the achievable maximum ionic conductivity.
• Developed a more accurate prediction of ionic conductivity by considering these microscopic interactions.

Conclusions:

• Deeper understanding of dopant influence on ionic conductivity in doped ceria achieved.
• Accurate prediction of ionic conductivity is possible by accounting for blocking and trapping mechanisms.
• Findings are generalizable to other ion conductors for SOFCs, SOECs, and solid-state batteries.