A high throughput optical method for studying compositional effects in electrocatalysts for CO2 reduction
In the problem of electrochemical CO 2 reduction, the discovery of earth-abundant, efficient, and selective catalysts is essential to enabling technology that can contribute to a carbon-neutral energy cycle. In this study, we adapt an optical high throughput screening method to study multi-metallic...
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Veröffentlicht in: | Nature communications 2021-02, Vol.12 (1), p.1114-1114, Article 1114 |
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Sprache: | eng |
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Zusammenfassung: | In the problem of electrochemical CO
2
reduction, the discovery of earth-abundant, efficient, and selective catalysts is essential to enabling technology that can contribute to a carbon-neutral energy cycle. In this study, we adapt an optical high throughput screening method to study multi-metallic catalysts for CO
2
electroreduction. We demonstrate the utility of the method by constructing catalytic activity maps of different alloyed elements and use X-ray scattering analysis by the atomic pair distribution function (PDF) method to gain insight into the structures of the most active compositions. Among combinations of four elements (Au, Ag, Cu, Zn), Au
6
Ag
2
Cu
2
and Au
4
Zn
3
Cu
3
were identified as the most active compositions in their respective ternaries. These ternary electrocatalysts were more active than any binary combination, and a ca. 5-fold increase in current density at potentials of −0.4 to −0.8 V vs. RHE was obtained for the best ternary catalysts relative to Au prepared by the same method. Tafel plots of electrochemical data for CO
2
reduction and hydrogen evolution indicate that the ternary catalysts, despite their higher surface area, are poorer catalysts for the hydrogen evolution reaction than pure Au. This results in high Faradaic efficiency for CO
2
reduction to CO.
A high-throughput method is presented for the synthesis and testing of alloy electrocatalysts for gas phase CO
2
electrolysis. Active ternary alloy catalysts were discovered and their structures characterized by X-ray pair distribution functional analysis. |
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ISSN: | 2041-1723 2041-1723 |
DOI: | 10.1038/s41467-021-21342-w |