To date, copper is the only heterogeneous catalyst that has shown a propensity to produce valuable hydrocarbons and alcohols, such as ethylene and ethanol, from electrochemical CO 2 reduction (CO 2 R). There are variety of factors that impact CO 2 R activity and selectivity, including the catalyst surface structure, morphology, composition, the choice of electrolyte ions and pH, and the electrochemical cell design. Many of these factors are often intertwined, which can complicate catalyst discovery and design efforts. Here we take a broad and historical view of these different aspects and their complex interplay in CO 2 R catalysis on Cu, with the purpose of providing new insights, critical evaluations, and guidance to the field with regard to research directions and best practices. First, we describe the various experimental probes and complementary theoretical methods that have been used to discern the mechanisms by which products are formed, and next we present our current understanding of the complex reaction networks for CO 2 R on Cu. We then analyze two key methods that have been used in attempts to alter the activity and selectivity of Cu: nanostructuring and the formation of bimetallic electrodes. Finally, we offer some perspectives on the future outlook for electrochemical CO 2 R.

Electrochemical carbon dioxide reduction to fuels presents one of the great challenges in chemistry. Herein we present an understanding of trends in electrocatalytic activity for carbon dioxide reduction over different metal catalysts that rationalize a number of experimental observations including the selectivity with respect to the competing hydrogen evolution reaction. We also identify two design criteria for more active catalysts. The understanding is based on density functional theory calculations of activation energies for electrochemical carbon monoxide reduction as a basis for an electrochemical kinetic model of the process. We develop scaling relations relating transition state energies to the carbon monoxide adsorption energy and determine the optimal value of this descriptor to be very close to that of copper.

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