Ionic Liquid Modified Electrocatalysts: a STEM-EDX Approach for Identification of Local Distributions within Ionomer Containing Catalysts Layers

IF 6.1 Q1 CHEMISTRY, MULTIDISCIPLINARY Chemistry methods : new approaches to solving problems in chemistry Pub Date : 2023-03-27 DOI:10.1002/cmtd.202200084
Kai Brunnengräber, Katharina Jeschonek, Michael George, Prof. Dr. Gui-Rong Zhang, Prof. Dr. Bastian J. M. Etzold
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Abstract

Driven by the transition to a CO2-neutral energy economy, research on polymer electrolyte fuel cells gained much interest during the last decade, with researchers trying to overcome the sluggish kinetics of the oxygen reduction reaction (ORR) limiting their performance. Modification of existing ORR catalysts with small amounts of ionic liquids (IL) represents an innovative approach to altering the catalytic activity and stability. ILs are supposed to take effect by modifying the local microenvironment at electrochemical interfaces. Nevertheless, a thorough understanding about the local distribution of ILs over solid catalysts is still lacking, hindering the IL modification strategy to be a generic approach to rationally modulating the catalytic performance of a catalyst. In this study we employed STEM-EDS spectral imaging to locate the IL distribution on the catalyst in presence of NafionTM. To overcome the difficulties associated with low energy STEM-EDS we setup a sophisticated data processing routine based on machine learning.

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离子液体修饰的电催化剂:用STEM - EDX方法鉴定含离聚体催化剂层内的局部分布
在向二氧化碳中性能源经济转型的推动下,聚合物电解质燃料电池的研究在过去十年中获得了很大的兴趣,研究人员试图克服氧还原反应(ORR)的缓慢动力学限制其性能。用少量离子液体(IL)改性现有的ORR催化剂是一种改变催化活性和稳定性的创新方法。通过改变电化学界面的局部微环境,il被认为是有效的。然而,对于固体催化剂上IL的局部分布仍然缺乏深入的了解,这阻碍了IL修饰策略成为合理调节催化剂催化性能的通用方法。在本研究中,我们使用STEM-EDS光谱成像来定位在NafionTM存在下催化剂上IL的分布。为了克服与低能量STEM-EDS相关的困难,我们建立了一个基于机器学习的复杂数据处理程序。
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