Abstract
Proton conducting solid oxide cells (P-SOCs) operating at intermediate temperature, working in both fuel cell mode for power generation and electrolysis mode for hydrogen production, gain much attention due to their unique advantages. However, the lack of efficient air electrode is the main obstacle to get high-performance P-SOCs, moreover, developing such materials relies on the high-cost and time-waste traditional way. The application of artificial intelligence (AI) to the field of P-SOCs can solve the problems that the traditional way faced. In this perspective, we discussed the current reports relating to the development of air electrode materials of P-SOC by constructing machine learning models. Finally, the future directions of AI guiding the discovery of key materials and high-performance P-SOCs are proposed.
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