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Surface hydroxide promotes CO2 electrolysis to ethylene in acidic conditions

Author

Listed:
  • Yufei Cao

    (University of Toronto
    Tsinghua University)

  • Zhu Chen

    (University of Toronto)

  • Peihao Li

    (University of Toronto)

  • Adnan Ozden

    (University of Toronto)

  • Pengfei Ou

    (University of Toronto)

  • Weiyan Ni

    (University of Toronto)

  • Jehad Abed

    (University of Toronto)

  • Erfan Shirzadi

    (University of Toronto)

  • Jinqiang Zhang

    (University of Toronto)

  • David Sinton

    (University of Toronto)

  • Jun Ge

    (Tsinghua University
    Shenzhen Bay Laboratory)

  • Edward H. Sargent

    (University of Toronto)

Abstract

Performing CO2 reduction in acidic conditions enables high single-pass CO2 conversion efficiency. However, a faster kinetics of the hydrogen evolution reaction compared to CO2 reduction limits the selectivity toward multicarbon products. Prior studies have shown that adsorbed hydroxide on the Cu surface promotes CO2 reduction in neutral and alkaline conditions. We posited that limited adsorbed hydroxide species in acidic CO2 reduction could contribute to a low selectivity to multicarbon products. Here we report an electrodeposited Cu catalyst that suppresses hydrogen formation and promotes selective CO2 reduction in acidic conditions. Using in situ time-resolved Raman spectroscopy, we show that a high concentration of CO and OH on the catalyst surface promotes C-C coupling, a finding that we correlate with evidence of increased CO residence time. The optimized electrodeposited Cu catalyst achieves a 60% faradaic efficiency for ethylene and 90% for multicarbon products. When deployed in a slim flow cell, the catalyst attains a 20% energy efficiency to ethylene, and 30% to multicarbon products.

Suggested Citation

  • Yufei Cao & Zhu Chen & Peihao Li & Adnan Ozden & Pengfei Ou & Weiyan Ni & Jehad Abed & Erfan Shirzadi & Jinqiang Zhang & David Sinton & Jun Ge & Edward H. Sargent, 2023. "Surface hydroxide promotes CO2 electrolysis to ethylene in acidic conditions," Nature Communications, Nature, vol. 14(1), pages 1-8, December.
  • Handle: RePEc:nat:natcom:v:14:y:2023:i:1:d:10.1038_s41467-023-37898-8
    DOI: 10.1038/s41467-023-37898-8
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    References listed on IDEAS

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    1. Miao Zhong & Kevin Tran & Yimeng Min & Chuanhao Wang & Ziyun Wang & Cao-Thang Dinh & Phil De Luna & Zongqian Yu & Armin Sedighian Rasouli & Peter Brodersen & Song Sun & Oleksandr Voznyy & Chih-Shan Ta, 2020. "Accelerated discovery of CO2 electrocatalysts using active machine learning," Nature, Nature, vol. 581(7807), pages 178-183, May.
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