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CO2-to-methanol electroconversion on a molecular cobalt catalyst facilitated by acidic cations

Nature Catalysis (2024)Cite this article

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Abstract

The crucial role of electrolyte cations in CO2 electroreduction has received intensive attention. One prevailing theory is that through electrostatic interactions or direct coordination, larger cations such as Cs+ can better stabilize the key intermediate species for CO and multicarbon (C2+) product generation, for example, on silver and copper, respectively. Here we show that smaller, more acidic alkali metal cations greatly enhance CO2-to-methanol conversion kinetics (Li+ > Na+ > K+ > Cs+) on an immobilized molecular cobalt catalyst, unlike the trend observed for CO and C2+. Through electrokinetic analyses and kinetic isotope effect studies along with computational investigations, we show that the hydration shell of a cation serves as a proton donor in the rate-determining protonation step of adsorbed CHO where acidic cations promote the proton-coupled electron transfer. This study reveals the promotional effect of cation solvation environment on CO2 electroreduction beyond the widely acknowledged stabilizing effect of cations.

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Fig. 1: Electrocatalytic CO2 conversion by CoPc/CNT and its cation dependence.
Fig. 2: Effect of cation on CO and MeOH production and DFT energy profile.
Fig. 3: KIE on CO and MeOH generation.
Fig. 4: Proposed mechanistic pathways and the role of electrolyte cation.

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The data that support this study are available within the Article and its Supplementary Information, or from the authors upon reasonable request.

References

  1. Huang, B. et al. Cation- and pH-dependent hydrogen evolution and oxidation reaction kinetics. JACS Au 1, 1674–1687 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. Strmcnik, D. et al. The role of non-covalent interactions in electrocatalytic fuel-cell reactions on platinum. Nat. Chem. 1, 466–472 (2009).

    Article  CAS  PubMed  Google Scholar 

  3. Shah, A. H. et al. The role of alkali metal cations and platinum-surface hydroxyl in the alkaline hydrogen evolution reaction. Nat. Catal. 5, 923–933 (2022).

    Article  CAS  Google Scholar 

  4. Monteiro, M. C. O. et al. Absence of CO2 electroreduction on copper, gold and silver electrodes without metal cations in solution. Nat. Catal. 4, 654–662 (2021).

    Article  CAS  Google Scholar 

  5. Shin, S.-J. et al. A unifying mechanism for cation effect modulating C1 and C2 productions from CO2 electroreduction. Nat. Commun. 13, 5482 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Ringe, S. et al. Understanding cation effects in electrochemical CO2 reduction. Energy Environ. Sci. 12, 3001–3014 (2019).

    Article  CAS  Google Scholar 

  7. Monteiro, M. C. O., Dattila, F., López, N. & Koper, M. T. M. The role of cation acidity on the competition between hydrogen evolution and CO2 reduction on gold electrodes. J. Am. Chem. Soc. 144, 1589–1602 (2022).

    Article  CAS  PubMed  Google Scholar 

  8. Murata, A. & Hori, Y. Product selectivity affected by cationic species in electrochemical reduction of CO2 and CO at a Cu electrode. Bull. Chem. Soc. Jpn 64, 123–127 (1991).

    Article  CAS  Google Scholar 

  9. Singh, M. R., Kwon, Y., Lum, Y., Ager, J. W. III & Bell, A. T. Hydrolysis of electrolyte cations enhances the electrochemical reduction of CO2 over Ag and Cu. J. Am. Chem. Soc. 138, 13006–13012 (2016).

    Article  CAS  PubMed  Google Scholar 

  10. Resasco, J. et al. Promoter effects of alkali metal cations on the electrochemical reduction of carbon dioxide. J. Am. Chem. Soc. 139, 11277–11287 (2017).

    Article  CAS  PubMed  Google Scholar 

  11. Dubouis, N. et al. Tuning water reduction through controlled nanoconfinement within an organic liquid matrix. Nat. Catal. 3, 656–663 (2020).

    Article  CAS  Google Scholar 

  12. Nitopi, S. et al. Progress and perspectives of electrochemical CO2 reduction on copper in aqueous electrolyte. Chem. Rev. 119, 7610–7672 (2019).

    Article  CAS  PubMed  Google Scholar 

  13. Birdja, Y. Y. et al. Advances and challenges in understanding the electrocatalytic conversion of carbon dioxide to fuels. Nat. Energy 4, 732–745 (2019).

    Article  CAS  Google Scholar 

  14. Chen, L. D., Urushihara, M., Chan, K. & Nørskov, J. K. Electric field effects in electrochemical CO2 reduction. ACS Catal. 6, 7133–7139 (2016).

    Article  CAS  Google Scholar 

  15. Gu, J. et al. Modulating electric field distribution by alkali cations for CO2 electroreduction in strongly acidic medium. Nat. Catal. 5, 268–276 (2022).

    Article  CAS  Google Scholar 

  16. Wu, Y., Jiang, Z., Lu, X., Liang, Y. & Wang, H. Domino electroreduction of CO2 to methanol on a molecular catalyst. Nature 575, 639–642 (2019).

    Article  CAS  PubMed  Google Scholar 

  17. Boutin, E. et al. Aqueous electrochemical reduction of carbon dioxide and carbon monoxide into methanol with cobalt phthalocyanine. Angew. Chem. Int. Ed. 58, 16172–16176 (2019).

    Article  CAS  Google Scholar 

  18. Kapusta, S. & Hackerman, N. Carbon dioxide reduction at a metal phthalocyanine catalyzed carbon electrode. J. Electrochem. Soc. 131, 1511 (1984).

    Article  CAS  Google Scholar 

  19. Shi, L.-L., Li, M., You, B. & Liao, R.-Z. Theoretical study on the electro-reduction of carbon dioxide to methanol catalyzed by cobalt phthalocyanine. Inorg. Chem. 61, 16549–16564 (2022).

    Article  CAS  PubMed  Google Scholar 

  20. Hossain, M. N. et al. Temperature dependent product distribution of electrochemical CO2 reduction on CoTPP/MWCNT composite. Appl. Catal. B 304, 120863 (2022).

    Article  CAS  Google Scholar 

  21. Su, J. et al. Strain enhances the activity of molecular electrocatalysts via carbon nanotube supports. Nat. Catal. 6, 818–828 (2023).

    Article  CAS  Google Scholar 

  22. Chang, Q. et al. Metal-coordinated phthalocyanines as platform molecules for understanding isolated metal sites in the electrochemical reduction of CO2. J. Am. Chem. Soc. 144, 16131–16138 (2022).

    Article  CAS  PubMed  Google Scholar 

  23. Zhang, X. et al. Highly selective and active CO2 reduction electrocatalysts based on cobalt phthalocyanine/carbon nanotube hybrid structures. Nat. Commun. 8, 14675 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  24. Han, N. et al. Supported cobalt polyphthalocyanine for high-performance electrocatalytic CO2 reduction. Chem 3, 652–664 (2017).

    Article  CAS  Google Scholar 

  25. Zhu, M., Ye, R., Jin, K., Lazouski, N. & Manthiram, K. Elucidating the reactivity and mechanism of CO2 electroreduction at highly dispersed cobalt phthalocyanine. ACS Energy Lett. 3, 1381–1386 (2018).

    Article  CAS  Google Scholar 

  26. Wang, L. et al. Electrochemical carbon monoxide reduction on polycrystalline copper: effects of potential, pressure, and pH on selectivity toward multicarbon and oxygenated products. ACS Catal. 8, 7445–7454 (2018).

    Article  CAS  Google Scholar 

  27. Koper, M. T. M. Theory of multiple proton–electron transfer reactions and its implications for electrocatalysis. Chem. Sci. 4, 2710–2723 (2013).

    Article  CAS  Google Scholar 

  28. Ledezma-Yanez, I. et al. Interfacial water reorganization as a pH-dependent descriptor of the hydrogen evolution rate on platinum electrodes. Nat. Energy 2, 17031 (2017).

    Article  CAS  Google Scholar 

  29. Ringe, S. Cation effects on electrocatalytic reduction processes at the example of the hydrogen evolution reaction. Curr. Opin. Electrochem. 39, 101268 (2023).

    Article  CAS  Google Scholar 

  30. Marcandalli, G., Goyal, A. & Koper, M. T. M. Electrolyte effects on the Faradaic efficiency of CO2 reduction to CO on a gold electrode. ACS Catal. 11, 4936–4945 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Corbin, N., Zeng, J., Williams, K. & Manthiram, K. Heterogeneous molecular catalysts for electrocatalytic CO2 reduction. Nano Res. 12, 2093–2125 (2019).

    Article  CAS  Google Scholar 

  32. Goyal, A. & Koper, M. T. M. The interrelated effect of cations and electrolyte pH on the hydrogen evolution reaction on gold electrodes in alkaline media. Angew. Chem. Int. Ed. 60, 13452–13462 (2021).

    Article  CAS  Google Scholar 

  33. Deringer, V. L., Tchougréeff, A. L. & Dronskowski, R. Crystal orbital hamilton population (COHP) analysis as projected from plane-wave basis sets. J. Phys. Chem. A 115, 5461–5466 (2011).

    Article  CAS  PubMed  Google Scholar 

  34. Cao, P. et al. Metal single-site catalyst design for electrocatalytic production of hydrogen peroxide at industrial-relevant currents. Nat. Commun. 14, 172 (2023).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Li, J. et al. Mechanism-guided realization of selective carbon monoxide electroreduction to methanol. Nat. Synth. 2, 1194–1201 (2023).

    Article  Google Scholar 

  36. Ren, X. et al. In-situ spectroscopic probe of the intrinsic structure feature of single-atom center in electrochemical CO/CO2 reduction to methanol. Nat. Commun. 14, 3401 (2023).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Ding, J. et al. Atomic high-spin cobalt(II) center for highly selective electrochemical CO reduction to CH3OH. Nat. Commun. 14, 6550 (2023).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Kastlunger, G. et al. Using pH dependence to understand mechanisms in electrochemical CO reduction. ACS Catal. 12, 4344–4357 (2022).

    Article  CAS  Google Scholar 

  39. Liu, X. et al. pH effects on the electrochemical reduction of CO(2) towards C2 products on stepped copper. Nat. Commun. 10, 32 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. Hori, Y., Takahashi, R., Yoshinami, Y. & Murata, A. Electrochemical reduction of CO at a copper. Electrode. J. Phys. Chem. B 101, 7075–7081 (1997).

    Article  CAS  Google Scholar 

  41. Warburton, R. E., Soudackov, A. V. & Hammes-Schiffer, S. Theoretical modeling of electrochemical proton-coupled electron transfer. Chem. Rev. 122, 10599–10650 (2022).

    Article  CAS  PubMed  Google Scholar 

  42. Huang, B. et al. Cation-dependent interfacial structures and kinetics for outer-sphere electron-transfer reactions. J. Phys. Chem. C 125, 4397–4411 (2021).

    Article  CAS  Google Scholar 

  43. Krȩżel, A. & Bal, W. A formula for correlating pKa values determined in D2O and H2O. J. Inorg. Biochem. 98, 161–166 (2004).

    Article  PubMed  Google Scholar 

  44. Choi, C. et al. Efficient electrocatalytic valorization of chlorinated organic water pollutant to ethylene. Nat. Nanotechnol. 18, 160–167 (2023).

    Article  CAS  PubMed  Google Scholar 

  45. Kresse, G. & Hafner, J. Ab initio molecular dynamics for liquid metals. Phys. Rev. B 47, 558–561 (1993).

    Article  CAS  Google Scholar 

  46. Kresse, G. & Furthmüller, J. Efficient iterative schemes for ab initio total-energy calculations using a plane-wave basis set. Phys. Rev. B 54, 11169–11186 (1996).

    Article  CAS  Google Scholar 

  47. Blöchl, P. E. Projector augmented-wave method. Phys. Rev. B 50, 17953–17979 (1994).

    Article  Google Scholar 

  48. Johnson, E. R. & Becke, A. D. A post-Hartree–Fock model of intermolecular interactions: inclusion of higher-order corrections. J. Chem. Phys. 124, 174104 (2006).

    Article  PubMed  Google Scholar 

  49. Maintz, S., Deringer, V. L., Tchougréeff, A. L. & Dronskowski, R. LOBSTER: a tool to extract chemical bonding from plane-wave based DFT. J. Comput. Chem. 37, 1030–1035 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Mathew, K., Sundararaman, R., Letchworth-Weaver, K., Arias, T. A. & Hennig, R. G. Implicit solvation model for density-functional study of nanocrystal surfaces and reaction pathways. J. Chem. Phys. 140, 084106 (2014).

    Article  PubMed  Google Scholar 

  51. Christensen, R., Hansen, H. A. & Vegge, T. Identifying systematic DFT errors in catalytic reactions. Catal. Sci. Technol. 5, 4946–4949 (2015).

    Article  CAS  Google Scholar 

  52. Hammer, B., Hansen, L. B. & Nørskov, J. K. Improved adsorption energetics within density-functional theory using revised Perdew–Burke–Ernzerhof functionals. Phys. Rev. B 59, 7413–7421 (1999).

    Article  Google Scholar 

  53. Wellendorff, J. et al. Density functionals for surface science: exchange-correlation model development with Bayesian error estimation. Phys. Rev. B 85, 235149 (2012).

    Article  Google Scholar 

  54. Nørskov, J. K. et al. Origin of the overpotential for oxygen reduction at a fuel-cell cathode. J. Phys. Chem. B 108, 17886–17892 (2004).

    Article  Google Scholar 

  55. Peterson, A. A., Abild-Pedersen, F., Studt, F., Rossmeisl, J. & Nørskov, J. K. How copper catalyzes the electroreduction of carbon dioxide into hydrocarbon fuels. Energy Environ. Sci. 3, 1311–1315 (2010).

    Article  CAS  Google Scholar 

  56. Poon, J., Batchelor-McAuley, C., Tschulik, K. & Compton, R. G. Single graphene nanoplatelets: capacitance, potential of zero charge and diffusion coefficient. Chem. Sci. 6, 2869–2876 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  57. Thompson, A. P. et al. LAMMPS—a flexible simulation tool for particle-based materials modeling at the atomic, meso, and continuum scales. Comput. Phys. Commun. 271, 108171 (2022).

    Article  CAS  Google Scholar 

  58. Rappe, A. K., Casewit, C. J., Colwell, K. S., Goddard, W. A. III & Skiff, W. M. UFF, a full periodic table force field for molecular mechanics and molecular dynamics simulations. J. Am. Chem. Soc. 114, 10024–10035 (1992).

    Article  CAS  Google Scholar 

  59. Boyd, P. G., Moosavi, S. M., Witman, M. & Smit, B. Force-field prediction of materials properties in metal–organic frameworks. J. Phys. Chem. Lett. 8, 357–363 (2017).

    Article  CAS  PubMed  Google Scholar 

  60. Frisch, M. J. et al. Gaussian 16 Rev. C.01 (Gaussian, 2016).

  61. Martínez, L., Andrade, R., Birgin, E. G. & Martínez, J. M. PACKMOL: a package for building initial configurations for molecular dynamics simulations. J. Comput. Chem. 30, 2157–2164 (2009).

    Article  PubMed  Google Scholar 

  62. Berendsen, H. J. C., Grigera, J. R. & Straatsma, T. P. The missing term in effective pair potentials. J. Phys. Chem. 91, 6269–6271 (1987).

    Article  CAS  Google Scholar 

  63. Wang, Z., Yang, Y., Olmsted, D. L., Asta, M. & Laird, B. B. Evaluation of the constant potential method in simulating electric double-layer capacitors. J. Chem. Phys. 141, 184102 (2014).

    Article  PubMed  Google Scholar 

  64. Humphrey, W., Dalke, A. & Schulten, K. VMD: visual molecular dynamics. J. Mol. Graph. 14, 33–38 (1996).

    Article  CAS  PubMed  Google Scholar 

  65. Liu, J., He, X., Zhang, J. Z. H. & Qi, L.-W. Hydrogen-bond structure dynamics in bulk water: insights from ab initio simulations with coupled cluster theory. Chem. Sci. 9, 2065–2073 (2018).

    Article  CAS  PubMed  Google Scholar 

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Acknowledgements

This work was supported by Niterra Co., Ltd. The authors are grateful to W. Massefski, J. Grimes and B. Adams for their assistance with NMR pulse sequence optimization and data analysis. We thank J. Johnson, A. Wang and B. Liu for access to their freeze dryer. We also thank J. Peng and J. Lunger for discussions on our computational approaches. This work used the Extreme Science and Engineering Discovery Environment, which is supported by National Science Foundation grant number DMR-160163. The authors also acknowledge the MIT SuperCloud and Lincoln Laboratory Supercomputing Center for providing high-performance computing resources.

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Authors and Affiliations

  1. Research Laboratory of Electronics, Massachusetts Institute of Technology, Cambridge, MA, USA

    Sunmoon Yu, Shuo Wang, Abhishek Aggarwal, Junghwa Kim, Botao Huang, Hongbin Xu, Daniel J. Zheng, Xiao Wang, Haldrian Iriawan, Davide Menga & Yang Shao-Horn

  2. Scientific Research Laboratory, Niterra Co. Ltd., Iwasaki, Komaki, Japan

    Hiroki Yamauchi

  3. Department of Materials Science and Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA

    Shuo Wang, Abhishek Aggarwal, Junghwa Kim, Hongbin Xu, Daniel J. Zheng, Haldrian Iriawan & Yang Shao-Horn

  4. Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA

    Kiarash Gordiz & Yang Shao-Horn

  5. Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA

    Xiao Wang

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Contributions

S.Y. and Y.S.-H. conceived the research idea. S.Y. and H.Y. performed experiments with assistance from H.X. and D.J.Z. S.W. and A.A. carried out DFT calculations and MD simulations with assistance from K.G., respectively. J.K. conducted electron microscopy characterization. B.H., H.X., D.J.Z., X.W., H.I. and D.M. contributed to discussions. S.Y. and Y.S.-H. wrote the manuscript with feedback from all authors.

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Correspondence to Sunmoon Yu or Yang Shao-Horn.

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Supplementary Information

Supplementary Figs. 1–34, Tables 1–6 and Notes 1 and 2.

Supplementary Data 1

Atomic coordinates of optimized structures.

Supplementary Data 2

Initial and final configurations for MD simulations.

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Yu, S., Yamauchi, H., Wang, S. et al. CO2-to-methanol electroconversion on a molecular cobalt catalyst facilitated by acidic cations. Nat Catal (2024). https://doi.org/10.1038/s41929-024-01197-2

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