Mayer Francis D, Hosseini-Benhangi Pooya, Sánchez-Sánchez Carlos M, Asselin Edouard, Gyenge Előd L
Department of Chemical and Biological Engineering, Clean Energy Research Centre, The University of British Columbia, 2360 East Mall, Vancouver, BC, V6T 1Z4, Canada.
Department of Materials Engineering, The University of British Columbia, 6350 Stores Road, Vancouver, BC, V6T 1Z4, Canada.
Commun Chem. 2020 Nov 6;3(1):155. doi: 10.1038/s42004-020-00399-6.
The electroreduction of CO is one of the most investigated reactions and involves testing a large number and variety of catalysts. The majority of experimental electrocatalysis studies use conventional one-sample-at-a-time methods without providing spatially resolved catalytic activity information. Herein, we present the application of scanning electrochemical microscopy (SECM) for simultaneous screening of different catalysts forming an array. We demonstrate the potential of this method for electrocatalytic assessment of an array consisting of three Sn/SnO catalysts for CO reduction to formate (CO2RF). Simultaneous SECM scans with fast scan (1 V s) cyclic voltammetry detection of products (HCOO, CO and H) at the Pt ultramicroelectrode tip were performed. We were able to consistently distinguish the electrocatalytic activities of the three compositionally and morphologically different Sn/SnO catalysts. Further development of this technique for larger catalyst arrays and matrices coupled with machine learning based algorithms could greatly accelerate the CO electroreduction catalyst discovery.
CO的电还原是研究最多的反应之一,涉及测试大量种类繁多的催化剂。大多数实验性电催化研究采用传统的一次一个样品的方法,没有提供空间分辨的催化活性信息。在此,我们展示了扫描电化学显微镜(SECM)在同时筛选形成阵列的不同催化剂方面的应用。我们证明了该方法在电催化评估由三种用于将CO还原为甲酸盐(CO2RF)的Sn/SnO催化剂组成的阵列方面的潜力。使用Pt超微电极尖端对产物(HCOO、CO和H)进行快速扫描(1 V s)循环伏安检测的同时SECM扫描得以实现。我们能够始终如一地区分三种组成和形态不同的Sn/SnO催化剂的电催化活性。将该技术进一步发展用于更大的催化剂阵列和矩阵,并结合基于机器学习的算法,可极大地加速CO电还原催化剂的发现。