| Abstract Scope |
This talk presents a comprehensive overview of our group’s two-decade-long effort to understand LCO- and LSM-based perovskites through integrated CALPHAD, DFT, and machine learning approaches. Key topics include the development of a thermodynamic database for LCO, LSM/YSZ compatibility, thermal cycle-induced shrinkage and weight loss in LSM, and defect chemistry-driven electrical conductivity prediction. We explore perovskite reactions with gas impurities and molten salts, highlighting equilibrium insights guiding core-shell structure formation. High-entropy mixing behaviors and their impact on conductivity are discussed, alongside A/B-site doping effects on phase stability, structure distortion, and transport properties. Advanced DFT studies incorporating various spin states and recent applications of zentropy theory shed new light on the intrinsic thermodynamics of LCO. Finally, we examine the perovskite/Ruddlesden-Popper phase interface and its implications for performance optimization. This talk underscores the value of integrated modeling in designing next-generation functional perovskites. |