The performance and commercial viability of proton exchange membrane fuel cells (PEMFCs) are constrained by key limitations in the membrane electrode assembly, including Nafion membrane swelling, low catalyst utilization, and inadequate water management in gas diffusion layers. Electrospinning has emerged as a promising technique for optimizing electrode components due to its unique capability to tailor fiber morphology, pore structure, and surface chemistry. Recent advances have incorporated artificial intelligence (AI) to assist in the design and optimization of porous materials, enabling efficient prediction of structural properties and performance. However, a systematic integration of AI into electrospinning processes to fabricate porous PEMFC components remains underdeveloped. This review comprehensively summarizes the application of electrospun materials in PEMFCs, emphasizing the structure–performance relationships in catalyst layers, gradient‐designed gas diffusion layers, and reinforced proton exchange membranes. Furthermore, it offers a forward‐looking perspective on the potential of AI‐assisted manufacturing strategies for advancing next‐generation high‐performance membrane electrodes.
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Jiang et al. (2026) studied this question.
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