Tailored Porous Carbon Xerogels for Fe-N-C Catalysts in Proton Exchange Membrane Fuel Cells

Laura Alvarez-Manuel,Cinthia Alegre,David Sebastian, Pedro F. Napal,Maria Jesus Lazaro

NANOMATERIALS(2024)

引用 0|浏览1
暂无评分
摘要
Atomically dispersed Fe-N-C catalysts for the oxygen reduction reaction (ORR) have been synthesized with a template-free method using carbon xerogels (CXG) as a porous matrix. The porosity of the CXGs is easily tunable through slight variations in the synthesis procedure. In this work, CXGs are prepared by formaldehyde and resorcinol polymerization, modifying the pH during the process. Materials with a broad range of porous structures are obtained: from non-porous to micro-/meso-/macroporous materials. The porous properties of CXG have a direct effect on Fe-N-CXG activity against ORR in an acidic medium (0.5 M H2SO4). Macropores and wide mesopores are vital to favor the mass transport of reagents to the active sites available in the micropores, while narrower mesopores can generate additional tortuosity. The role of microporosity is investigated by comparing two Fe-N-C catalysts using the same CXG as the matrix but following a different Fe and N doping procedure. In one case, the carbonization of CXG occurs rapidly and simultaneously with Fe and N doping, whereas in the other case it proceeds slowly, under controlled conditions and before the doping process, resulting in the formation of more micropores and active sites and achieving higher activity in a three-electrode cell and a better durability during fuel cell measurements. This work proves the feasibility of the template-free method using CXG as a carbon matrix for Fe-N-C catalysts, with the novelty of the controlled porous properties of the carbon material and its effect on the catalytic activity of the Fe-N-C catalyst. Moreover, the results obtained highlight the importance of the carbon matrix's porous structure in influencing the activity of Fe-N-C catalysts against ORR.
更多
查看译文
关键词
carbon xerogels,Fe-N-C catalysts,oxygen reduction reaction,fuel cells
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要