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

Abstract

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

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.

Figures/Tables 9

References 42

[1]	付佩，周紫佳，兰利波，等.氢燃料电池汽车发动机关键技术研究现状及趋势展望［J］.汽车工程学报，2022，12（4）：388-398. FU Pei， ZHOU Zijia， LAN Libo， et al. Research status and development trends of key technologies for hydrogen fuel cell vehicle engines ［J］. Journal of Automotive Engineering， 2022， 12（4）： 388-398.
[2]	奥海尔，车硕源，Colella，等.燃料电池基础： Fuel cell fundamentals［M］.北京：电子工业出版社，2007.
	AO Haier， CHE Shuoyuan， COLELLA W， et al. Fuel cell fundamentals［M］. Beijing：Electronics Industry Press， 2007.
[3]	吴钊颖，罗夏爽，罗柳轩，等. 氢燃料电池阳极抗一氧化碳毒化催化剂的研究进展与展望［J］. 中国科学：技术科学， 2024， 54（4）： 567-583.
	WU Zhaoying， LUO Xiashuang， LUO Liuxuan， et al. Progress and prospects of anti-carbon monoxide poisoning catalysts for hydrogen fuel cell anodes［J］. Science in China： Technological Sciences， 2024， 54（4）： 567-583.
[4]	张鹏，李佳烨，潘原. 单原子催化剂在氢燃料电池阴极氧还原反应中的研究进展［J］. 太阳能学报， 2022， 43（6）： 306-320.
	ZHANG Peng， LI Jiaye， PAN Yuan. Progress of single-atom catalysts in the cathodic oxygen reduction reaction of hydrogen fuel cells［J］. Journal of Solar Energy， 2022， 43（6）： 306-320.
[5]	郝策，刘自若，刘炜，等. 用于氧还原反应的碳基负载金属单原子催化剂研究进展［J］. 无机材料学报， 2021， 36（8）： 820-834.
	HAO Ce， LIU Ziruo， LIU Wei， et al. Progress of carbon-based metal-loaded single-atom catalysts for oxygen reduction reactions［J］. Journal of Inorganic Materials， 2021， 36（8）： 820-834.
[6]	SONG Z， LI J， ZHANG Q， et al. Progress and perspective of single-atom catalysts for membrane electrode assembly of fuel cells［J］. Carbon Energy， 2023， 5（7）： 19.
[7]	TANG M， YANG T， YANG X， et al. Single-atom catalysts for proton exchange membrane fuel cell： anode anti-poisoning & characterization technology［J］. Electrochimica Acta， 2023， 446： 142120.
[8]	LIAO X， LU R， XIA L， et al. Density functional theory for electrocatalysis［J］. Energy & Environmental Materials， 2022， 5（1）： 157-185.
[9]	王甲一，车春霞，朱吉钦，等. 基于结构描述符的催化剂理论设计研究进展［J］. 中国科学：化学， 2024， 54（11）： 2071-2082.
	WANG Jiayi， CHE Chunxia， ZHU Jiqin， et al. Progress in theoretical design of catalysts based on structural descriptors［J］. Science in China： Chemistry， 2024， 54（11）： 2071-2082.
[10]	竹涛，韩一伟，刘帅，等. 单原子位点催化剂及其电催化应用研究进展［J］. 化工进展， 2022， 2： 41.
	ZHU Tao， HAN Yiwei， LIU Shuai， et al. Progress of single-site catalysts and their electrocatalytic applications［J］. Advances in Chemical Engineering， 2022， 2： 41.
[11]	TAMTAJI M， GAO H， HOSSAIN M D， et al. Machine learning for design principles for single atom catalysts towards electrochemical reactions［J］. Journal of Materials Chemistry A， 2022， 10（29）： 15309-15331.
[12]	LOPES P P， FREITAS K S， TICIANELLI E A. CO tolerance of PEMFC anodes： mechanisms and electrode designs［J］. Electrocatalysis， 2010， 1（4）： 200-212.
[13]	WEI K， WANG X， GE J. Towards bridging thermo/electrocatalytic CO oxidation： from nanoparticles to single atoms［J］. Chemical Society Reviews， 2024， 53（17）： 8903-8948.
[14]	YANG Z， CHEN C， ZHAO Y， et al. Pt single atoms on CrN nanoparticles deliver outstanding activity and CO tolerance in the hydrogen oxidation reaction［J］. Advanced Materials， 2023， 35（1）： 2208799.
[15]	HUANG Z， LU R， ZHANG Y， et al. A highly efficient pH-universal HOR catalyst with engineered electronic structures of single Pt sites by isolated Co atoms［J］. Advanced Functional Materials， 2023， 33（47）： 2306333.
[16]	LIN J， ZHANG Z， QIU J， et al. Synergy between single atom and nanoclusters promotes power and CO tolerant performance in PEMFCs［J］. Chemical Engineering Journal， 2025， 506： 160156.
[17]	LI H， WANG X， GONG X， et al. “One stone three birds” of a synergetic effect between Pt single atoms and clusters makes an ideal anode catalyst for fuel cells［J］. Journal of Materials Chemistry A， 2023， 11（27）： 14826-14832.
[18]	LONG D， LIU Y， PING X， et al. Constructing CO-immune water dissociation sites around Pt to achieve stable operation in high CO concentration environment［J］. Nature Communications， 2024， 15（1）： 8105.
[19]	WANG X， LI Y， WANG Y， et al. Proton exchange membrane fuel cells powered with both CO and H₂［J］. Proceedings of the National Academy of Sciences， 2021， 118（43）： e2107332118.
[20]	YANG X， WANG Y， WANG X， et al. CO‐tolerant PEMFC anodes enabled by synergistic catalysis between iridium single‐atom sites and nanoparticles［J］. Angew. Chem. Int. Ed.， 2021， 60（50）： 26177-26183.
[21]	ZHU L， LI Z， YANG M， et al. An effective approach to enhance hydrogen evolution reaction and hydrogen oxidation reaction by Ni doping to MoO₃［J］. Small， 2023， 19（49）： 2303481.
[22]	WANG M， ZHANG H， LIU Y， et al. Research progress of precise structural regulation of single atom catalyst for accelerating electrocatalytic oxygen reduction reaction［J］. Journal of Energy Chemistry， 2022， 72： 56-72.
[23]	WANG F， YANG J， LI J， et al. Which is best for ORR： single atoms， nanoclusters， or coexistence？［J］. ACS Energy Letters， 2024， 9（1）： 93-101.
[24]	LAI W H， ZHANG L， YAN Z， et al. Activating inert surface Pt single atoms via subsurface doping for oxygen reduction reaction［J］. Nano Letters， 2021， 21（19）： 7970-7978.
[25]	LIU B， FENG R， BUSCH M， et al. Synergistic hybrid electrocatalysts of platinum alloy and single-atom platinum for an efficient and durable oxygen reduction reaction［J］. ACS Nano， 2022， 16（9）： 14121-14133.
[26]	XIAO M， ZHU J， LI G， et al. A single-atom iridium heterogeneous catalyst in oxygen reduction reaction［J］. Angewandte Chemie International Edition， 2019， 58（28）： 9640-9645.
[27]	QIN J， LIU H， ZOU P， et al. Altering ligand fields in single-atom sites through second-shell anion modulation boosts the oxygen reduction reaction［J］. Journal of the American Chemical Society， 2022， 144（5）： 2197-2207.
[28]	MEHMOOD A， GONG M， JAOUEN F， et al. High loading of single atomic iron sites in Fe-NC oxygen reduction catalysts for proton exchange membrane fuel cells［J］. Nature Catalysis， 2022， 5（4）： 311-323.
[29]	XU H， JIA H， LI H， et al. Dual carbon-hosted Co-N₃ enabling unusual reaction pathway for efficient oxygen reduction reaction［J］. Applied Catalysis B： Environmental， 2021， 297： 120390.
[30]	YU Z， XU H， CHENG D. Design of single atom catalysts［J］. Advances in Physics： X， 2021， 6（1）： 1905545.
[31]	LUO J， ZHANG Y， LU Z， et al. Oxygen-coordinated Cr single-atom catalyst for oxygen reduction reaction in proton exchange membrane fuel cells［J］. Angewandte Chemie International Edition， 2025， 137（17）： 202500500.
[32]	BACK S， BAGHERZADEH MOSTAGHIMI A H， SIAHROSTAMI S. Enhancing oxygen reduction reaction activity using single atom catalyst supported on tantalum pentoxide［J］. ChemCatChem， 2022， 14（11）： e202101763.
[33]	CHEN Z， ZHENG H， ZHANG J， et al. Covalent organic frameworks derived single-atom cobalt catalysts for boosting oxygen reduction reaction in rechargeable Zn-air batteries［J］. Journal of Colloid and Interface Science， 2024， 670： 103-113.
[34]	YANG Z， QIAN S， WANG Y， et al. Graphene benefits penta-nitrogen coordinated iron and catalytic stability of oxygen reduction reaction［J］. Chemical Engineering Journal， 2024， 496： 154141.
[35]	KULKARNI A， SIAHROSTAMI S， PATEL A， et al. Understanding catalytic activity trends in the oxygen reduction reaction［J］. Chemical Reviews， 2018， 118（5）： 2302-2312.
[36]	CALLE-VALLEJO F， TYMOCZKO J， COLIC V， et al. Finding optimal surface sites on heterogeneous catalysts by counting nearest neighbors［J］. Science， 2015， 350（6257）： 185-189.
[37]	XIA G， TAN Y， CHEN X， et al. Monodisperse magnesium hydride nanoparticles uniformly self-assembled on graphene［J］. Advanced Materials， 2015， 27（39）： 5981-5988.
[38]	JING H， ZHU P， ZHENG X， et al. Theory-oriented screening and discovery of advanced energy transformation materials in electrocatalysis［J］. Advanced Powder Materials， 2022， 1（1）： 14-26.
[39]	SUN H， GAO L， LI Y， et al. Screening of single-atomic catalysts loaded on two-dimensional transition metal dichalcogenides for electrocatalytic oxygen reduction via high throughput ab initio calculations［J］. Journal of Colloid and Interface Science， 2025， 684： 251-261.
[40]	WANG S， MENG K， QIN L， et al. High-throughput screening of transition metal phthalocyanine electrocatalysts for oxygen reduction reactions［J］. International Journal of Hydrogen Energy， 2024， 88： 850-857.
[41]	LIN S， XU H， WANG Y， et al. Directly predicting limiting potentials from easily obtainable physical properties of graphene-supported single-atom electrocatalysts by machine learning［J］. Journal of Materials Chemistry A， 2020， 8（11）： 5663-5670.
[42]	ZHU Y， XU B， HAN C， et al. Potential correlation between thermal transport and catalytic performance in single metal atom cata

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