Kai Brunnengräber, Katharina Jeschonek, Michael George, Prof. Dr. Gui-Rong Zhang, Prof. Dr. Bastian J. M. Etzold
{"title":"Ionic Liquid Modified Electrocatalysts: a STEM-EDX Approach for Identification of Local Distributions within Ionomer Containing Catalysts Layers","authors":"Kai Brunnengräber, Katharina Jeschonek, Michael George, Prof. Dr. Gui-Rong Zhang, Prof. Dr. Bastian J. M. Etzold","doi":"10.1002/cmtd.202200084","DOIUrl":null,"url":null,"abstract":"<p>Driven by the transition to a CO<sub>2</sub>-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 Nafion<sup>TM</sup>. To overcome the difficulties associated with low energy STEM-EDS we setup a sophisticated data processing routine based on machine learning.</p>","PeriodicalId":72562,"journal":{"name":"Chemistry methods : new approaches to solving problems in chemistry","volume":null,"pages":null},"PeriodicalIF":6.1000,"publicationDate":"2023-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cmtd.202200084","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Chemistry methods : new approaches to solving problems in chemistry","FirstCategoryId":"1085","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/cmtd.202200084","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CHEMISTRY, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0
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.