Enhancement of Catalytic Activity and Selectivity for the Gaseous Electroreduction of CO2 to CO: Guidelines for the Selection of Carbon Supports
- Authors
- Lim, Chulwan; Lee, Woong Hee; Won, Jong Ho; Ko, Young-Jin; Kim, Sangkuk; Min, Byoung Koun; Lee, Kwan-Young; Jung, Won Suk; Oh, Hyung-Suk
- Issue Date
- 2021-12
- Publisher
- WILEY-V C H VERLAG GMBH
- Citation
- Advanced Sustainable Systems, v.5, no.12
- Abstract
- To secure the economic feasibility of electrochemical carbon dioxide reduction reaction (CO2RR), a method of using support materials to reduce the amount of catalyst loading and increase catalytic activity for CO2RR can be a solution. Herein, guidelines for selecting carbon support materials suitable for CO2RR are reported. In a gaseous CO2-fed CO2RR electrolyzer, an Ag nanoparticle-composited carbon nanocage (denoted as Ag/CNC) electrode exhibits an optimal performance for CO2RR with a partial current density of approximate to 400 mA cm(-2). Ag/CNC showcases a uniformly dispersed morphology with Ag nanoparticles and sufficient hydrophobicity after the reaction to prevent flooding, which is known to inhibit the mass transfer of CO2. Furthermore, the CNCs possess small amounts of carbon defects; this suppresses the catalytic activity for the hydrogen evolution reaction (HER), which is a side reaction of CO2RR. Results of a three-stack cell experiment with the Ag/CNC electrode reveal the possibility of a support-based strategy for achieving an industrial-level scaling of CO2RR. This study suggests that the support material for CO2RR should be considered not only on the basis of the morphology of carbon, uniform dispersion of Ag nanoparticles, and hydrophobicity of the electrode but also factors influencing the HER, such as carbon defects.
- Keywords
- GENERAL TECHNOECONOMIC ANALYSIS; OXYGEN REDUCTION; ELECTROCHEMICAL REDUCTION; ACTIVATED CARBON; SINGLE ATOMS; DIOXIDE; ELECTROLYSIS; EFFICIENT; NANOPARTICLES; CONVERSION; carbon dioxide reduction reaction; carbon support; carbon monoxide; hydrophobicity; micro computed tomography
- ISSN
- 2366-7486
- URI
- https://pubs.kist.re.kr/handle/201004/116102
- DOI
- 10.1002/adsu.202100216
- Appears in Collections:
- KIST Article > 2021
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