The critical challenges related to climate change and energy security could be solved if we can find the champion materials to build sustainable and environment-friendly devices. With this aim in mind, my research leverages leading-edge computational techniques and a multidisciplinary approach to understand the behavior of complex electrolytes currently used in solid oxide fuel cells (SOFCs) and optimize them for next-generation fuel cell devices. The electrolytes used in SOFCs are generally polycrystalline with different grain sizes, grain orientations, dopant segregation, and defects distribution. In addition, they are typically characterized by a high density of grain boundaries and interfaces. All these features can substantially affect their ionic conductivity. In this talk, I will discuss our recent findings on the microstructural, ionic, and electronic behavior of grain boundaries and interfaces present in commonly used ceramic electrolytes used in SOFCs. By integrating the classical and quantum simulations, this work prepared realistic models of the working-class materials and provided the long-sought explanation for the experimentally observed phenomenons. Finally, in this talk, I will discuss some of the challenges in identifying the overall impact of all the microstructural defects present in polycrystalline materials and the role of machine learning in resolving them.