Catalyst electro-redeposition controls morphology and oxidation state for selective carbon dioxide reduction View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2018-02

AUTHORS

Phil De Luna, Rafael Quintero-Bermudez, Cao-Thang Dinh, Michael B. Ross, Oleksandr S. Bushuyev, Petar Todorović, Tom Regier, Shana O. Kelley, Peidong Yang, Edward H. Sargent

ABSTRACT

The reduction of carbon dioxide to renewable fuels and feedstocks offers opportunities for large-scale, long-term energy storage. The synthesis of efficient CO2 reduction electrocatalysts with high C2:C1 selectivity remains a field of intense interest. Here we present electro-redeposition, the dissolution and redeposition of copper from a sol–gel, to enhance copper catalysts in terms of their morphology, oxidation state and consequent performance. We utilized in situ soft X-ray absorption spectroscopy to track the oxidation state of copper under CO2 reduction conditions with time resolution. The sol–gel material slows the electrochemical reduction of copper, enabling control over nanoscale morphology and the stabilization of Cu+ at negative potentials. CO2 reduction experiments, in situ X-ray spectroscopy and density functional theory simulations revealed the beneficial interplay between sharp morphologies and Cu+ oxidation state. The catalyst exhibits a partial ethylene current density of 160 mA cm–2 (−1.0 V versus reversible hydrogen electrode) and an ethylene/methane ratio of 200. Catalysts that can selectively reduce carbon dioxide to C2+ products are attractive for the generation of more complex and useful chemicals. Here, an electro-redeposited copper catalyst is shown to provide excellent selectivity and high current density for ethylene formation. Detailed characterization and theory link the performance to the catalyst morphology. More... »

PAGES

103-110

Identifiers

URI

http://scigraph.springernature.com/pub.10.1038/s41929-017-0018-9

DOI

http://dx.doi.org/10.1038/s41929-017-0018-9

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1100320666


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