Energetically-favorable distribution of oxygen vacancies and metal atoms in perovskite BaCexZr0.85−xY0.15O2.925 solid solutions using a genetic algorithm and lattice statics

• Published in: Computational materials science Vol. 170
• Main Authors: Choi, In-Gyu, Kim, Yurie, Kim, Ki-Yung, Jo, Junyeong, Song, Sun-Ju, Kim, Yeong-Cheol
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01.12.2019
• Subjects: Fuel cell electrolyte; Genetic algorithm; Lattice statics; Solid solution; Fuel cell electrolyte; Lattice statics; Solid solution; Genetic algorithm
• ISSN: 0927-0256; 1879-0801
• DOI: 10.1016/j.commatsci.2019.109184

[Display omitted] We studied the energetically-favorable distribution of oxygen vacancies and metal atoms in perovskite BaCexZr1−xY0.15O2.925 solid solution structures using a genetic algorithm and lattice statics. The solid solution structures were made by mixing Ce, Zr, and Y at site B and removing O at site O in ABO3. Because of the huge number of configurational solid solution structures in the 3 × 3 × 3 ABO3 supercell, we employed a genetic algorithm and lattice statics to help identify energetically-favorable solid solution structures. Oxygen vacancies in the solid solution structures preferred Zr when the Ce composition was small, and the preference changed to Y with an increase in the Ce composition.