期刊
NATURE CATALYSIS
卷 5, 期 6, 页码 564-570出版社
NATURE PORTFOLIO
DOI: 10.1038/s41929-022-00788-1
关键词
-
资金
- Research Grants Council of the Hong Kong Special Administrative Region [24304920]
- Natural Sciences and Engineering Research Council of Canada
- Ontario Research Fund - Research Excellence programme
- Marsden Fund Council
- Niagara supercomputer at the SciNet HPC Consortium
- Canada Foundation for Innovation
- Government of Ontario
- Ontario Research Fund - Research Excellence
- University of Toronto
Renewable electricity-powered CO2 reduction to multi-carbon (C2+) products is a promising route for low-carbon-footprint fuels and chemicals. Acidic conditions offer a solution to the consumption of input CO2 by the electrolyte, but also promote the hydrogen evolution reaction. This study presents a design strategy that suppresses the activity of hydrogen evolution reaction by maximizing the co-adsorption of CO and CO2 on Cu-based catalysts.
Renewable electricity-powered CO2 reduction to multi-carbon (C2+) products offers a promising route to realization of low-carbon-footprint fuels and chemicals. However, a major fraction of input CO2 (>85%) is consumed by the electrolyte through reactions with hydroxide to form carbonate/bicarbonate in both alkaline and neutral reactors. Acidic conditions offer a solution to overcoming this limitation, but also promote the hydrogen evolution reaction. Here we report a design strategy that suppresses hydrogen evolution reaction activity by maximizing the co-adsorption of CO and CO2 on Cu-based catalysts to weaken H-star binding. Using density functional theory studies, we found Pd-Cu promising for selective C2+ production over C-1, with the lowest Delta G(OCCOH)star and Delta(GOCCOH)star - Delta(GCHO)star. We synthesized Pd-Cu catalysts and report a crossover-free system (liquid product crossover <0.05%) with a Faradaic efficiency of 89 +/- 4% for CO2 to C2+ at 500 mA cm(-2), simultaneous with single-pass CO2 utilization of 60 +/- 2% to C2+.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据