单原子催化剂赋能下一代燃料电池：从计算筛选到实际应用

doi:10.19562/j.chinasae.qcgc.2025.11.012

摘要/Abstract

摘要：

质子交换膜燃料电池是能源领域中备受关注的绿色发电技术，具有能量转换效率高、环境友好等优点。然而，高成本的贵金属催化剂限制了其规模化应用。单原子催化剂凭借其高原子利用率、低成本、选择性好等优点在燃料电池的催化反应中展现出巨大应用潜力，是未来燃料电池催化剂的重要发展方向。本文系统阐述了单原子催化剂在质子交换膜燃料电池阳极抗毒化与阴极氧还原中的构效关系及实际应用，详细介绍了铂基和非铂基单原子催化剂的结构特点与应用优势；总结了基于第一性原理和机器学习的高通量计算方法，为燃料电池催化剂的高效筛选和从原子尺度的精准设计提供了思路借鉴；并对燃料电池单原子催化剂的未来发展机遇和挑战进行了总结和展望，可为质子交换膜燃料电池单原子催化剂的未来发展应用提供理论依据和技术参考。

关键词: 单原子催化剂, 质子交换膜燃料电池, 阳极抗毒化, 阴极氧还原, 第一性原理计算, 机器学习

Abstract:

Proton exchange membrane fuel cell is a green power generation technology that has attracted much attention in today's energy field， with the advantages of high-energy conversion efficiency and environmental friendliness. However， the high-cost precious metal catalysts have limited its large-scale application. Single-atom catalysts， with the high atom utilization， low cost， and good selectivity， show great potential for application in the catalytic reaction of fuel cells， and are an important direction for the development of fuel cell catalysts in the future. In this paper， the constitutive relationship and practical application of single-atom catalysts in proton exchange membrane fuel cells are systematically elaborated， particularly focusing on their roles in anodic antitoxicity and cathodic oxygen reduction. The structural characteristics and application advantages of both platinum-based and non-platinum-based single-atom catalysts are introduced in details， with high-throughput computational methodologies summarized integrating first-principle calculations with machine learning， which offers innovative approaches for efficient catalyst screening and atomic-scale precise design in fuel cell development. Furthermore， opportunities and remaining challenges in advancing single-atom catalysts for next-generation fuel cell technologies are outlined， providing theoretical foundation and technical reference for the future development and application of single-atom catalysts for proton exchange membrane fuel cells.

Key words: single-atom catalysts, proton exchange membrane fuel cells, anodic antitoxicity, cathodic oxygen reduction, first-principles calculation, machine learning

刘好年,蔡鑫,Harenbrock Michael,林瑞. 单原子催化剂赋能下一代燃料电池：从计算筛选到实际应用[J]. 汽车工程, 2025, 47(11): 2178-2186.

Haonian Liu,Xin Cai,Michael Harenbrock,Rui Lin. Single-Atom Catalysts Empowering Next-Generation Fuel Cells: From Computational Screening to Application[J]. Automotive Engineering, 2025, 47(11): 2178-2186.

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