Controlled fabrication of Fe3N@NG composites as superior oxygen evolution reaction electrocatalysts

IF 6.4 3区环境科学与生态学 Q2 ENERGY & FUELS

Carbon Resources Conversion Pub Date : 2023-12-21 DOI:10.1016/j.crcon.2023.100207

Yang Song , Tongya Tian , Changming Li , Xi Zeng , Sen Zhang , Li Chen , Zhenghua Yang , Qizhe Ji , Xianglong Zhao , Feiyong Chen

引用次数: 0

Abstract

We report the controlled fabrication of nitrogen doped graphene (NG) nanoplates, which are uniformly decorated with iron nitride (Fe₃N) nanoparticles, via ball milling of mixtures of graphite and iron nitrates and the following ammonia annealing. The obtained Fe₃N@NG composites demonstrate excellent electrocatalytic activity and durability for oxygen evolution reaction, both of which outperform those of the state-of-the-art iridium oxide catalysts. This may be attributed to nitrogen doping as well as the synergistic effect between Fe₃N and graphene nanoplates.

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受控制备 Fe3N@NG 复合材料，作为优异的氧进化反应电催化剂

我们报告了通过球磨石墨和硝酸铁的混合物以及随后的氨化退火，受控制备氮掺杂石墨烯（NG）纳米板的过程，这些纳米板上均匀地装饰着氮化铁（Fe3N）纳米颗粒。获得的 Fe3N@NG 复合材料在氧进化反应中表现出优异的电催化活性和耐久性，这两项性能均优于最先进的氧化铱催化剂。这可能归功于氮掺杂以及 Fe3N 和石墨烯纳米板之间的协同效应。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Carbon Resources Conversion Materials Science-Materials Science (miscellaneous)

CiteScore

9.90

自引率

11.70%

发文量

审稿时长

10 weeks

期刊介绍： Carbon Resources Conversion (CRC) publishes fundamental studies and industrial developments regarding relevant technologies aiming for the clean, efficient, value-added, and low-carbon utilization of carbon-containing resources as fuel for energy and as feedstock for materials or chemicals from, for example, fossil fuels, biomass, syngas, CO2, hydrocarbons, and organic wastes via physical, thermal, chemical, biological, and other technical methods. CRC also publishes scientific and engineering studies on resource characterization and pretreatment, carbon material innovation and production, clean technologies related to carbon resource conversion and utilization, and various process-supporting technologies, including on-line or off-line measurement and monitoring, modeling, simulations focused on safe and efficient process operation and control, and process and equipment optimization.