{"title":"Catalytic CO−O coupling on high-entropy alloys: A composition optimization dependent on the reaction assumptions","authors":"Jack K. Pedersen, Giona Mainardis, Jan Rossmeisl","doi":"10.1016/j.jcat.2025.115983","DOIUrl":null,"url":null,"abstract":"Catalytically joining carbon monoxide and oxygen atoms is crucial for various environmental and industrial applications. However, the reaction environments for this process vary significantly across different applications. In this paper, we demonstrate how reaction environments and associated modeling assumptions influence the predictions of optimal disordered alloy catalysts for CO-O coupling. Our analysis is based on a dataset comprising several hundred *CO, *OH, and *O simulated adsorption energies on atomically disordered face-centered cubic (111) surfaces composed of Ag, Au, Cu, Pd, Pt, and Ru. This dataset is provided alongside this publication to support further machine learning-based searches for optimal CO-O coupling catalysts within this composition space for any CO-O coupling application. We illustrate the impact of different modeling assumptions on the identification of CO-O coupling catalysts through two key examples: electrochemical methanol oxidation and CO-tolerant hydrogen fuel cells.","PeriodicalId":346,"journal":{"name":"Journal of Catalysis","volume":"17 1","pages":""},"PeriodicalIF":6.5000,"publicationDate":"2025-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Catalysis","FirstCategoryId":"92","ListUrlMain":"https://doi.org/10.1016/j.jcat.2025.115983","RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"CHEMISTRY, PHYSICAL","Score":null,"Total":0}
引用次数: 0
Abstract
Catalytically joining carbon monoxide and oxygen atoms is crucial for various environmental and industrial applications. However, the reaction environments for this process vary significantly across different applications. In this paper, we demonstrate how reaction environments and associated modeling assumptions influence the predictions of optimal disordered alloy catalysts for CO-O coupling. Our analysis is based on a dataset comprising several hundred *CO, *OH, and *O simulated adsorption energies on atomically disordered face-centered cubic (111) surfaces composed of Ag, Au, Cu, Pd, Pt, and Ru. This dataset is provided alongside this publication to support further machine learning-based searches for optimal CO-O coupling catalysts within this composition space for any CO-O coupling application. We illustrate the impact of different modeling assumptions on the identification of CO-O coupling catalysts through two key examples: electrochemical methanol oxidation and CO-tolerant hydrogen fuel cells.
期刊介绍：
The Journal of Catalysis publishes scholarly articles on both heterogeneous and homogeneous catalysis, covering a wide range of chemical transformations. These include various types of catalysis, such as those mediated by photons, plasmons, and electrons. The focus of the studies is to understand the relationship between catalytic function and the underlying chemical properties of surfaces and metal complexes.
The articles in the journal offer innovative concepts and explore the synthesis and kinetics of inorganic solids and homogeneous complexes. Furthermore, they discuss spectroscopic techniques for characterizing catalysts, investigate the interaction of probes and reacting species with catalysts, and employ theoretical methods.
The research presented in the journal should have direct relevance to the field of catalytic processes, addressing either fundamental aspects or applications of catalysis.
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