Cooperative CO2-to-ethanol conversion via enriched intermediates at molecule–metal catalyst interfaces

Fengwang Li, Yuguang C. Li, Ziyun Wang, Jun Li, Dae-Hyun Nam, Yanwei Lum, Mingchuan Luo, Xue Wang, Adnan Ozden, Sung-Fu Hung, Bin Chen, Yuhang Wang, Joshua Wicks, Yi Xu, Yilin Li, Christine M. Gabardo, Cao-Thang Dinh, Ying Wang, Tao-Tao Zhuang, David SintonEdward H. Sargent*

*Corresponding author for this work

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

Abstract

Electrochemical conversion of CO2 into liquid fuels, powered by renewable electricity, offers one means to address the need for the storage of intermittent renewable energy. Here we present a cooperative catalyst design of molecule–metal catalyst interfaces with the goal of producing a reaction-intermediate-rich local environment, which improves the electrosynthesis of ethanol from CO2 and H2O. We implement the strategy by functionalizing the copper surface with a family of porphyrin-based metallic complexes that catalyse CO2 to CO. Using density functional theory calculations, and in situ Raman and operando X-ray absorption spectroscopies, we find that the high concentration of local CO facilitates carbon–carbon coupling and steers the reaction pathway towards ethanol. We report a CO2-to-ethanol Faradaic efficiency of 41% and a partial current density of 124 mA cm−2 at −0.82 V versus the reversible hydrogen electrode. We integrate the catalyst into a membrane electrode assembly-based system and achieve an overall energy efficiency of 13%.
Original languageEnglish
Pages (from-to)75-82
JournalNature Catalysis
Volume3
Issue number1
Online published16 Dec 2019
DOIs
Publication statusPublished - Jan 2020
Externally publishedYes

Funding

The authors acknowledge funding support from Suncor Energy, the Ontario Research fund and the Natural Sciences and Engineering Research Council (NSERC). DFT computations were performed on the IBM BlueGene/Q supercomputer with support from the Niagara supercomputer at the SciNet HPC Consortium and the Southern Ontario Smart Computing Innovation Platform (SOSCIP). SciNet is funded by the Canada Foundation for Innovation, the Government of Ontario’s Ontario Research Fund – Research Excellence, and the University of Toronto. SOSCIP is funded by the Federal Economic Development Agency of Southern Ontario, the Province of Ontario, IBM Canada, Ontario Centres of Excellence, Mitacs and 15 Ontario academic member institutions. This research used synchrotron resources of the Advanced Photon Source, an Office of Science User Facility operated for the US Department of Energy Office of Science by Argonne National Laboratory and was supported by the US Department of Energy under contract no. DE-AC02-06CH11357 and the Canadian Light Source and its funding partners. F.L. thanks H.T.L. for ICP–MS measurement. J.L. acknowledges the Banting Postdoctoral Fellowships programme. C.G. acknowledges the NSERC Postdoctoral Fellowships programme. D.S. acknowledges the NSERC E.W.R. Steacie Memorial Fellowship.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 7 - Affordable and Clean Energy
    SDG 7 Affordable and Clean Energy
  2. SDG 13 - Climate Action
    SDG 13 Climate Action

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