A comparative spectroscopic study revealing why the CO2 electroreduction selectivity switches from CO to HCOO- at Cu-Sn and Cu-In based catalysts


  • Gumaa El-Nagar Helmholtz-Zentrum Berlin für Materialien und Energie ,
  • Fan Yang Institut für Chemie und Biochemie, Freie Universität Berlin ,
  • Sasho Stojkovikj Helmholtz-Zentrum Berlin für Materialien und Energie ,
  • Stefan Mebs Freie Universität Berlin ,
  • Siddharth Gupta Helmholtz-Zentrum Berlin für Materialien und Energie ,
  • Ibbi Ahmet Helmholtz-Zentrum Berlin für Materialien und Energie ,
  • Holger Dau Freie Universität Berlin ,
  • Matthew Mayer Helmholtz-Zentrum Berlin für Materialien und Energie


To address the challenge of selectivity towards single product in Cu-catalyzed electrochemical CO2 reduction, one strategy is to incorporate a second metal with the goal of tuning catalytic activity via synergy effects. In particular, catalysts based on Cu modified with post-transition metals (Sn or In) are known to reduce CO2 selectively to either CO or HCOO- depending on their composition. However, it remains unclear exactly which factors induce this switch in reaction pathways, and whether these two related bimetal combinations follow similar general structure-activity trends. To investigate these questions systematically, Cu-In and Cu-Sn bimetallic catalysts were synthesized across a range of composition ratios and studied in detail. Compositional and morphological control was achieved via a simple electrochemical synthesis approach. A combination of operando and quasi in-situ spectroscopic techniques, including X-ray photoelectron, X-ray absorption, and Raman spectroscopy, were used to observe the dynamic behaviors of the catalysts’ surface structure, composition, speciation, and local environment during CO2 electrolysis. The two systems exhibited similar selectivity dependency on their surface composition. Cu-rich catalysts produce mainly CO, while Cu-poor catalysts were found to mainly produce HCOO-. Despite these similarities, the speciation of Sn and In at the surface differed from each other, and were found to be strongly dependent on the applied potential and the catalyst composition. For Cu-rich compositions optimized for CO production (Cu85In15 and Cu85Sn15), indium was present predominantly in reduced metallic form (In0), whereas tin mainly existed as an oxidized species (Sn2/4+). Meanwhile, for the HCOO--selective compositions (Cu25In75 and Cu40Sn60), the indium exclusively exhibited In0 regardless of the applied potential, while the tin resembles was reduced to metallic (Sn0) only at most negative applied potential, which corresponds to the best HCOO- selectivity. Furthermore, while Cu40Sn60 enhances HCOO- selectivity by inhibiting H2 evolution, Cu25In75 improves the HCOO- selectivity at the expense of CO production. Due to these differences, we contend that identical mechanisms cannot be used to explain the behavior of these two bimetallic systems (Cu-In and Cu-Sn). Operando surface-enhanced Raman spectroscopy measurements provide direct evidence of the local alkalization and its impact on the dynamic transformation of oxidized Cu surface species (Cu2O/CuO) into a mixture of Cu(OH)2 and basic Cu carbonates (Cux(OH)y(CO3)y) rather than metallic Cu under CO2 electrolysis. This study provides novel insight into the origin of the switch in selectivity between CO and HCOO- pathways at Cu bimetallic catalysts and the nature of surface-active sites and key intermediates for both pathways.


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Supplementary material

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A comparative spectroscopic study revealing why the CO2 electroreduction selectivity switches from CO to HCOO- at Cu-Sn and Cu-In based catalysts
The detailed information of the utilized materials, chemicals and techniques; synthesis procedures of various Cu-Sn and Cu-In catalysts; additional morphological, structural and compositional characterization figures for the studied catalysts including SEM, XRD, XPS and elemental mapping; details of EXAFS fit models and parameters; additional electrochemical, in-situ Raman and quasi in-situ XAS data.