当前位置:科学网首页 > 小柯机器人 >详情
环境条件下过渡金属上气态氮氧化物的电化学还原
作者:小柯机器人 发布时间:2022/1/14 14:24:35

美国特拉华大学Feng Jiao团队报道了环境条件下过渡金属上气态氮氧化物的电化学还原。相关研究成果发表在2022年1月11日出版的国际知名学术期刊《美国化学会杂志》。

减少氮氧化物(NOx)排放对于应对全球变暖和改善空气质量至关重要。用于排放控制的传统NOx减排技术在接近环境温度时效率较低。

该文中,研究人员展示了一种在环境条件下以高反应速率(400 mA cm–2)进行的减少气态NOx的电化学途径。对各种过渡金属进行了电化学还原NO和N2O的评估,以揭示电催化剂在决定产物选择性方面的作用。

具体而言,铜对NH3的形成具有高度选择性,在NO电还原中法拉第效率>80%。此外,NO电还原的分压研究表明,高NO覆盖率有利于N–N偶联反应。在酸性电解质中,NH3的生成极为有利,而N2的生成则受到抑制。通过使用流动电化学质谱法进行额外的机理研究,以进一步了解反应途径。

该工作为通过使用可再生电力减少环境条件下的气态NOx排放提供了一条有希望的途径。

附:英文原文

Title: Electrochemical Reduction of Gaseous Nitrogen Oxides on Transition Metals at Ambient Conditions

Author: Byung Hee Ko, Bjorn Hasa, Haeun Shin, Yaran Zhao, Feng Jiao

Issue&Volume: January 11, 2022

Abstract: Mitigating nitrogen oxide (NOx) emissions is critical to tackle global warming and improve air quality. Conventional NOx abatement technologies for emission control suffer from a low efficiency at near ambient temperatures. Herein, we show an electrochemical pathway to reduce gaseous NOx that can be conducted at high reaction rates (400 mA cm–2) under ambient conditions. Various transition metals are evaluated for electrochemical reduction of NO and N2O to reveal the role of electrocatalyst in determining the product selectivity. Specifically, Cu is highly selective toward NH3 formation with >80% Faradaic efficiency in NO electroreduction. Furthermore, the partial pressure study of NO electroreduction revealed that a high NO coverage facilitates the N–N coupling reaction. In acidic electrolytes, the formation of NH3 is greatly favored, whereas the N2 production is suppressed. Additional mechanistic studies were conducted by using flow electrochemical mass spectrometry to gain further insights into reaction pathways. This work provides a promising avenue toward abating gaseous NOx emissions at ambient conditions by using renewable electricity.

DOI: 10.1021/jacs.1c10535

Source: https://pubs.acs.org/doi/10.1021/jacs.1c10535

 

期刊信息

JACS:《美国化学会志》,创刊于1879年。隶属于美国化学会,最新IF:14.612
官方网址:https://pubs.acs.org/journal/jacsat
投稿链接:https://acsparagonplus.acs.org/psweb/loginForm?code=1000