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High carbon utilization in CO2 reduction to multi-carbon products in acidic media

Nature Catalysis volume 5, pages 564–570 (2022)Cite this article

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Abstract

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* binding. Using density functional theory studies, we found Pd–Cu promising for selective C2+ production over C1, with the lowest ∆GOCCOH* and ∆GOCCOH* - ∆GCHO*. 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+.

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Fig. 1: Profile of local species (CO2 and H+).
Fig. 2: DFT calculation of CO2RR on bimetallic X–Cu(111).
Fig. 3: Structural and compositional characterization of Pd–Cu catalysts on PTFE.
Fig. 4: CO2RR performance of Pd–Cu catalysts.

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All data are available from the authors upon reasonable request.

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Acknowledgements

Ying Wang, Y.X. and Z.X. acknowledge the support of the Research Grants Council of the Hong Kong Special Administrative Region (project no. 24304920). E.H.S., P.O., X.W., J.E.H., J.W., N.W. and Yuhang Wang acknowledge the support of the Natural Sciences and Engineering Research Council of Canada and the Ontario Research Fund – Research Excellence programme. Z.W. wishes to acknowledge the Marsden Fund Council from Government funding, managed by Royal Society Te Apārangi and the eScience Infrastructure (NeSI) high performance computing facilities. All DFT calculations were performed with support from 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.

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Author notes

  1. These authors contributed equally: Yi Xie, Pengfei Ou, Xue Wang.

Authors and Affiliations

  1. Department of Chemistry, The Chinese University of Hong Kong, Hong Kong, China

    Yi Xie, Zhanyou Xu, Jimmy C. Yu & Ying Wang

  2. Department of Electrical and Computer Engineering, University of Toronto, Toronto, Ontario, Canada

    Pengfei Ou, Xue Wang, Jianan Erick Huang, Joshua Wicks, Ning Wang, Yuhang Wang & Edward H. Sargent

  3. Department of Chemistry, University at Buffalo, State University of New York, Buffalo, New York, USA

    Yuguang C. Li

  4. School of Chemical Sciences, The University of Auckland, Auckland, New Zealand

    Ziyun Wang

  5. Department of Mechanical and Industrial Engineering, University of Toronto, Toronto, Ontario, Canada

    Christopher McCallum & David Sinton

  6. Department of Applied Biology and Chemical Technology, The Hong Kong Polytechnic University, Hong Kong, China

    Tianxiang Chen & Benedict T. W. Lo

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  1. Yi Xie
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Contributions

Ying Wang and E.H.S. designed and supervised the project. Y.X. carried out electrochemical measurements, part of the COMSOL simulations and analysed data. P.O. carried out DFT calculations and analysed data. X.W. performed in situ Raman analysis. C.M. contributed part of the COMSOL modelling. T.C. and T.B.L. performed XPS measurements. Ying Wang, P.O., X.W., Y.X., Z.X., J.E.H., Y.C.L., J.W. and Z.W. co-wrote the paper. All authors discussed the results and contributed to the preparation of the manuscript.

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Correspondence to Ying Wang or Edward H. Sargent.

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Nature Catalysis thanks Yuanyue Liu, Edmund Dickinson and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Supplementary Information

Supplementary Figs. 1–21, Note 1 and Tables 1–12.

Supplementary Data

Atomic coordinates of optimized computational models.

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Xie, Y., Ou, P., Wang, X. et al. High carbon utilization in CO2 reduction to multi-carbon products in acidic media. Nat Catal 5, 564–570 (2022). https://doi.org/10.1038/s41929-022-00788-1

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