Descriptors for Electrochemical CO2 Reduction in Imidazolium-Based Electrolytes

Abstract

Electrochemical CO2 reduction (CO2R) allows us to close the carbon cycle and store intermittent renewable energy into chemical products. Among these, syngas, a mixture of hydrogen and carbon monoxide, is particularly valuable due to its high market share and the low energy required for its electrocatalytic production. In addition to catalyst optimization, lately, electrolyte modifications to achieve a suitable CO/H2 ratio have also been considered. Ionic liquid (IL)-based electrolytes have enabled high faradaic efficiency toward CO, depending on the chemical properties of the IL. In this work, we rationalized through density functional theory (DFT) descriptors the competition between hydrogen evolution (HER) and CO2R on silver in imidazolium-based electrolytes, developing a DFT-based analytical model. The electrolyte anion regulates the concentration ratio between cationic and carbene species of ILs cation, respectively, between the 1-ethyl-3-methylimidazolium cation (EMIM+) and carbene (EMIM:) species and between the 1-butyl-3-methylimidazolium cation (BMIM+) and carbene (BMIM:). The latter species, if formed, hinders the CO2R by blocking the active sites or trapping CO2 in solution. In the case of weak Lewis base anions as fluorinated ones, EMIM+ (BMIM+) cations, which serve as cocatalysts in CO2R, are more abundant, allowing high CO partial current densities and high electrochemically active surface area. Applying the here-defined descriptors to ILs not yet tested makes it possible to predict the HER and CO2R selectivity on silver, thus enabling guidelines for designing better ILs for CO2R.

Document Type

Article


Published version

Language

English

CDU Subject

Subject

Química

Pages

9 p.

Publisher

ACS Publications

Grant Agreement Number

European Commission through the European Union’s Horizon 2020 Research and Innovation Action program under the SunCoChem project (Grant Agreement No. 862192)

Spanish Ministry of Science and Innovation (PID2021-122516OI00, Severo Ochoa Grant MCIN/AEI/10.13039/501100011033CEX2019-000925-S)

F.D. and S.H. acknowledge the CINECA award under the ISCRA initiative for the availability of high-performance computing resources and support within the ILCO2SYN project.

F.Z. thanks Fondazione CRT

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