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Artificial spherical chromatophore nanomicelles for selective CO2 reduction in water

Nature Catalysis volume 6, pages 464–475 (2023)Cite this article

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Abstract

In nature, photosynthetic organelles harness solar radiation to produce energy-rich compounds from water and atmospheric CO2 via exquisite supramolecular assemblies. Although artificial photocatalytic cycles have been shown to occur at higher intrinsic efficiencies, the low selectivity and stability in water for multi-electron CO2 reduction hamper their practical applications. The creation of water-compatible artificial photocatalytic systems mimicking the natural photosynthetic apparatus for selective and efficient solar fuel production represents a major challenge. Here we show a highly stable and efficient artificial spherical chromatophore nanomicelle system self-assembled from Zn porphyrin amphiphiles with a Co catalyst in water for CO2-to-methane conversion with a turnover number >6,600 and 89% selectivity over 30 days. The hierarchical self-assembly induced a spherical antenna effect that could facilitate the photocatalytic process with an initial 15% solar-to-fuel efficiency. Furthermore, it has a capability to efficiently reduce atmospheric CO2 into methane with high selectivity in water.

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Fig. 1: Preparation and structures of the artificial spherical chromatophore nanomicelle system.
Fig. 2: Characterization of artificial spherical chromatophore nanomicelles.
Fig. 3: Photocatalytic performance of Nalg-1–4.
Fig. 4: fs-TA dynamics of the nanomicelle system.

Data availability

The data that support the findings of this study are available from the corresponding authors upon reasonable request.

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Acknowledgements

J.T. acknowledges the funding support from National Key Research and Development Program of China (2022YFA1206200); Shanghai Institute of Organic Chemistry and Shanghai Branch, CAS; Shanghai Rising-Star Program (22QA1411200); and the National Natural Science Foundation of China (no. 22271306). J.T. acknowledges the Marie-Curie Fellowship. I.M. acknowledges the Canada 150 Research Chair and NSERC Discovery Grant. R.Y. acknowledges the funding support from Young Scientists Fund of the National Natural Science Foundation of China (grant no. 21905240); the Shenzhen Research Institute, City University of Hong Kong; the State Key Laboratory of Marine Pollution (SKLMP) Seed Collaborative Research Fund; the Guangdong Basic and Applied Basic Research Fund (2022A1515011333); the Shenzhen Science and Technology Program (JCYJ20220818101204009); Hong Kong Research Grant Council (21300620) and the State Key Laboratory of Marine Pollution Internal Research Fund (SKLMP/IRF/0029). D.L.P. and L.D. thank the University of Hong Kong Development Fund 2013-2014 project ‘New Ultrafast Spectroscopy Experiments for Shared Facilities’. We thank the Shanghai Synchrotron Radiation Facility for providing the BL16B1 and BL10U1 beamline for collecting the synchrotron X-ray scattering data. We acknowledge access and support of the GW4 Facility for High-Resolution Electron Cryo-Microscopy, funded by the Wellcome Trust (202904/Z/16/Z and 206181/Z/17/Z) and BBSRC (BB/R000484/1). We thank Y. Zhang and X. Jin for the useful discussions. We thank M. Sener and D. H. Fackler for permission to use the visual molecular dynamics model in Fig. 1c.

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Author notes

  1. These authors contributed equally: Junlai Yu, Libei Huang.

Authors and Affiliations

  1. Key Laboratory of Synthetic and Self-Assembly Chemistry for Organic Functional Molecules, Center for Excellence in Molecular Synthesis, Shanghai Institute of Organic Chemistry, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China

    Junlai Yu, Qingxuan Tang, Shang-Bo Yu, Qiao-Yan Qi & Jia Tian

  2. Department of Chemistry, Shanghai Key Laboratory of Molecular Catalysis and Innovative Materials, Fudan University, Shanghai, China

    Junlai Yu, Jiangshan Zhang, Danying Ma & Yifei Lei

  3. Department of Chemistry, State Key Laboratory of Marine Pollution, City University of Hong Kong, Hong Kong, China

    Libei Huang, Jianjun Su, Yun Song & Ruquan Ye

  4. School of Chemistry, University of Bristol, Bristol, UK

    Jean-Charles Eloi & Robert L. Harniman

  5. GW4 Facility for High-Resolution Electron Cryo-Microscopy, University of Bristol, Bristol, UK

    Ufuk Borucu

  6. Department of Chemistry, Northwestern University, Evanston, IL, USA

    Long Zhang

  7. State Key Laboratory of Chemical Engineering, East China University of Science and Technology, Shanghai, China

    Minghui Zhu

  8. Shanghai Advanced Research Institute, Chinese Academy of Sciences, Shanghai, China

    Feng Tian

  9. Department of Chemistry, The University of Hong Kong, Hong Kong, China

    Lili Du & David Lee Phillips

  10. School of Life Sciences, Jiangsu University, Zhenjiang, China

    Lili Du

  11. Department of Chemistry, University of Victoria, Victoria, British Columbia, Canada

    Ian Manners

  12. City University of Hong Kong Shenzhen Research Institute, Shenzhen, China

    Ruquan Ye

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  1. Junlai Yu
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Contributions

J.T. conceived, designed and supervised the research. J.T., J.Y., Q.T., S.-B.Y. and R.Y. carried out most of the experiments. M.Z., L.H., J.S., Y.S., J.Z., D.M., Y.L., Q.-Y.Q., F.T. and L.Z. conducted part of the experiments. J.-C.E. performed the TEM, STEM and EDX imaging. R.L.H performed the AFM analysis. U.B. performed the cryo-TEM imaging. L.D. and D.L.P. performed the fs-TA studies. J.T., L.D., D.L.P. and R.Y. analysed the data and wrote the manuscript with input from the other authors. I.M. provided useful inputs and comments on the manuscript.

Corresponding authors

Correspondence to Lili Du, David Lee Phillips, Ruquan Ye or Jia Tian.

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Supplementary information

Supplementary Information

Supplementary Methods, Figs. 1–83, Tables 1–8 and References.

Supplementary Data 1

Atomic coordinates of optimized computational model of CO-CoN4.

Supplementary Data 2

Atomic coordinates of optimized computational model of ZnN4.

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Yu, J., Huang, L., Tang, Q. et al. Artificial spherical chromatophore nanomicelles for selective CO2 reduction in water. Nat Catal 6, 464–475 (2023). https://doi.org/10.1038/s41929-023-00962-z

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