Computational approaches have been used effectively in material design for solid oxide fuel cells (SOFCs). As a way to improve the performance and stability of anode materials in SOFCs, the exsolution phenomenon has been extensively taken advantage of. In the exsolution process, highly active and stable nanoparticles (NPs) are formed uniformly over the surface of the host oxide due to the anchoring effects of exsolved NPs in the host’s structure. In this review, we particularly focus on how computational approaches such as density functional theory calculation, phase field modeling, and analytic methods can be used to understand the exsolution phenomenon; this knowledge can then be exploited to design enhanced anode materials for SOFCs. We first review the nature of exsolution and then look into catalytic applications of exsolved NPs. From this point, we investigate how to engineer exsolved nanoparticles to maximize their catalytic activity with a view that any enhanced performance will aid future applications.

Exsolution Solid Oxide Fuel Cells (SOFCs) Perovskite Oxides Computational Modeling Density Functional Theory (DFT)

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