Zong Jianwei, Wu Wenjie, Mao Lanqun, Yu Ping
Beijing National Laboratory for Molecular Sciences, Key Laboratory of Analytical Chemistry for Living Biosystems, Institute of Chemistry, the Chinese Academy of Sciences (CAS), Beijing 100190, P. R. China.
University of Chinese Academy of Sciences, Beijing 100049, P. R. China.
Chem Commun (Camb). 2023 Nov 2;59(88):13163-13166. doi: 10.1039/d3cc04505f.
Identifying the active sites of electrocatalysts is important for catalyst design. However, determining the specific active sites of catalysts is still a challenge. Herein, we demonstrate that stochastic collision electrochemistry could be used as a simple but efficient method for identifying the active sites of electrocatalysts, which can overcome the problems caused by the considerable difference between the giant geometric area and the limited exposure of active sites when using traditional cyclic voltammetry. To validate the method, the oxygen reduction reaction and ascorbic acid electrooxidation with the as-synthesized nitrogen-doped carbon catalysts were selected as model reactions. The results show that the pyridinic N dominates the reactivity of the oxygen reduction reaction while the CO functional group is the active site for ascorbic acid oxidation, which could not be identified by cyclic voltammetry with the ensemble drop-casting method. This manuscript demonstrates a new method for identifying the active sites of electrocatalysts, essentially enriching the methodology for identifying active sites.
识别电催化剂的活性位点对于催化剂设计至关重要。然而,确定催化剂的具体活性位点仍然是一项挑战。在此,我们证明随机碰撞电化学可作为一种简单而有效的方法来识别电催化剂的活性位点,该方法能够克服使用传统循环伏安法时巨大几何面积与有限活性位点暴露之间存在的显著差异所带来的问题。为验证该方法,选择用合成的氮掺杂碳催化剂进行的氧还原反应和抗坏血酸电氧化作为模型反应。结果表明,吡啶型氮主导氧还原反应的活性,而C=O官能团是抗坏血酸氧化的活性位点,这是采用整体滴铸法的循环伏安法无法识别的。本文展示了一种识别电催化剂活性位点的新方法,从本质上丰富了识别活性位点的方法学。