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Robust and synthesizable photocatalysts for CO2 reduction: a data-driven materials discovery

Author

Listed:
  • Arunima K. Singh

    (Lawrence Berkeley National Laboratory
    Chemical Sciences Division, Lawrence Berkeley National Laboratory)

  • Joseph H. Montoya

    (Environmental Energy Technologies Division, Lawrence Berkeley National Laboratory)

  • John M. Gregoire

    (Joint Center for Artificial Photosynthesis, California Institute of Technology)

  • Kristin A. Persson

    (Environmental Energy Technologies Division, Lawrence Berkeley National Laboratory
    University of California)

Abstract

The photocatalytic conversion of the greenhouse gas CO2 to chemical fuels such as hydrocarbons and alcohols continues to be a promising technology for renewable generation of energy. Major advancements have been made in improving the efficiencies and product selectiveness of currently known CO2 reduction electrocatalysts, nonetheless, materials discovery is needed to enable economically viable, industrial-scale CO2 reduction. We report here the largest CO2 photocathode search to date, starting with 68860 candidate materials, using a rational first-principles computation-based screening strategy to evaluate synthesizability, corrosion resistance, visible-light absorption, and compatibility of the electronic structure with fuel synthesis. The results confirm the observation of the literature that few materials meet the stringent CO2 photocathode requirements, with only 52 materials meeting all requirements. The results are well validated with respect to the literature, with 9 of these materials having been studied for CO2 reduction, and the remaining 43 materials are discoveries from our pipeline that merit further investigation.

Suggested Citation

  • Arunima K. Singh & Joseph H. Montoya & John M. Gregoire & Kristin A. Persson, 2019. "Robust and synthesizable photocatalysts for CO2 reduction: a data-driven materials discovery," Nature Communications, Nature, vol. 10(1), pages 1-9, December.
    • Handle: RePEc:nat:natcom:v:10:y:2019:i:1:d:10.1038_s41467-019-08356-1
    DOI: 10.1038/s41467-019-08356-1
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    Cited by:

    1. Aliaksei Mazheika & Yang-Gang Wang & Rosendo Valero & Francesc Viñes & Francesc Illas & Luca M. Ghiringhelli & Sergey V. Levchenko & Matthias Scheffler, 2022. "Artificial-intelligence-driven discovery of catalyst genes with application to CO2 activation on semiconductor oxides," Nature Communications, Nature, vol. 13(1), pages 1-13, December.
    2. Michael G. Taylor & Daniel J. Burrill & Jan Janssen & Enrique R. Batista & Danny Perez & Ping Yang, 2023. "Architector for high-throughput cross-periodic table 3D complex building," Nature Communications, Nature, vol. 14(1), pages 1-11, December.
    3. Mohammad Qorbani & Amr Sabbah & Ying-Ren Lai & Septia Kholimatussadiah & Shaham Quadir & Chih-Yang Huang & Indrajit Shown & Yi-Fan Huang & Michitoshi Hayashi & Kuei-Hsien Chen & Li-Chyong Chen, 2022. "Atomistic insights into highly active reconstructed edges of monolayer 2H-WSe2 photocatalyst," Nature Communications, Nature, vol. 13(1), pages 1-8, December.
    4. Jihyun Baek & Qiu Jin & Nathan Scott Johnson & Yue Jiang & Rui Ning & Apurva Mehta & Samira Siahrostami & Xiaolin Zheng, 2022. "Discovery of LaAlO3 as an efficient catalyst for two-electron water electrolysis towards hydrogen peroxide," Nature Communications, Nature, vol. 13(1), pages 1-10, December.

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