Cationic-group-functionalized electrocatalysts enable stable acidic CO2 electrolysis

Mengyang Fan, Jianan Erick Huang, Rui Kai Miao, Yu Mao, Pengfei Ou, Feng Li, Xiao Yan Li, Yufei Cao, Zishuai Zhang, Jinqiang Zhang, Yu Yan, Adnan Ozden, Weiyan Ni, Ying Wang, Yong Zhao, Zhu Chen, Behrooz Khatir, Colin P. O’Brien, Yi Xu, Yurou Celine XiaoGeoffrey I.N. Waterhouse, Kevin Golovin, Ziyun Wang*, Edward H. Sargent*, David Sinton*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

135 Scopus citations

Abstract

Acidic electrochemical CO2 reduction (CO2R) addresses CO2 loss and thus mitigates the energy penalties associated with CO2 recovery; however, acidic CO2R suffers low selectivity. One promising remedy—using a high concentration of alkali cations—steers CO2R towards multi-carbon (C2+) products, but these same alkali cations result in salt formation, limiting operating stability to <15 h. Here we present a copper catalyst functionalized with cationic groups (CG) that enables efficient CO2 activation in a stable manner. By replacing alkali cations with immobilized benzimidazolium CG within ionomer coatings, we achieve over 150 h of stable CO2R in acid. We find the water-management property of CG minimizes proton migration that enables operation at a modest voltage of 3.3 V with mildly alkaline local pH, leading to more energy-efficient CO2R with a C2+ Faradaic efficiency of 80 ± 3%. As a result, we report an energy efficiency of 28% for acidic CO2R towards C2+ products and a single-pass CO2 conversion efficiency exceeding 70%. [Figure not available: see fulltext.]

Original languageEnglish (US)
Pages (from-to)763-772
Number of pages10
JournalNature Catalysis
Volume6
Issue number9
DOIs
StatePublished - Sep 2023

Funding

We acknowledge support from the Natural Sciences and Engineering Research Council (NSERC) of Canada and TotalEnergies SE. Support from Canada Research Chairs Program is also gratefully acknowledged. Infrastructure provided through the Canada Foundation for Innovation and the Ontario Research Fund supported the work. R.K.M. thanks NSERC, Hatch and the Government of Ontario for their support through graduate scholarships. P.O. thanks the Climate Positive Energy for its support through Rising Stars in Clean Energy Postdoctoral Fellowship. Density functional theory calculations were performed on the Niagara supercomputer at the SciNet HPC Consortium. SciNet is funded by: the Canada Foundation for Innovation; the Government of Ontario; Ontario Research Fund - Research Excellence; and the University of Toronto. The computational study is supported by the Marsden Fund Council from Government funding (21-UOA-237) and Catalyst: Seeding General Grant (22-UOA-031-CGS), managed by Royal Society Te Apārangi. Z.W. and Y.M. acknowledge the use of New Zealand eScience Infrastructure (NeSI) high-performance computing facilities, consulting support and/or training services as part of this research. G.I.N.W. and Y.M. acknowledge funding support from the MacDiarmid Institute for Advanced Materials and Nanotechnology, the Energy Education Trust of New Zealand and the Royal Society Te Apārangi. Z.W. and Y.M. graciously acknowledge D. J. Searles (University of Queensland) and J. Cheng (Xiamen University) for their support and scientific discussions on the computational work. We acknowledge support from the Natural Sciences and Engineering Research Council (NSERC) of Canada and TotalEnergies SE. Support from Canada Research Chairs Program is also gratefully acknowledged. Infrastructure provided through the Canada Foundation for Innovation and the Ontario Research Fund supported the work. R.K.M. thanks NSERC, Hatch and the Government of Ontario for their support through graduate scholarships. P.O. thanks the Climate Positive Energy for its support through Rising Stars in Clean Energy Postdoctoral Fellowship. Density functional theory calculations were performed on the Niagara supercomputer at the SciNet HPC Consortium. SciNet is funded by: the Canada Foundation for Innovation; the Government of Ontario; Ontario Research Fund - Research Excellence; and the University of Toronto. The computational study is supported by the Marsden Fund Council from Government funding (21-UOA-237) and Catalyst: Seeding General Grant (22-UOA-031-CGS), managed by Royal Society Te Apārangi. Z.W. and Y.M. acknowledge the use of New Zealand eScience Infrastructure (NeSI) high-performance computing facilities, consulting support and/or training services as part of this research. G.I.N.W. and Y.M. acknowledge funding support from the MacDiarmid Institute for Advanced Materials and Nanotechnology, the Energy Education Trust of New Zealand and the Royal Society Te Apārangi. Z.W. and Y.M. graciously acknowledge D. J. Searles (University of Queensland) and J. Cheng (Xiamen University) for their support and scientific discussions on the computational work.

ASJC Scopus subject areas

  • Catalysis
  • Bioengineering
  • Biochemistry
  • Process Chemistry and Technology

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