Electrochemical Gaseous Carbon Monoxide Reduction Using Cu Nanoparticles in Acidic Electrolytes
Authors: Kurihara Ryo , Nagita Kaito , Ohashi Keitaro , Harada Takashi , Nakanishi Shuji , Kamiya Kazuhide 
Published: February 2024

The electrochemical CO2 reduction reaction (CO2RR) into value-added multi-carbon products (C2+), using renewable electricity is an attractive strategy for closing the carbon cycle. Electrolysis of gaseous CO2 using a gas diffusion electrodes (GDEs) enables electrolysis at high current density1, and various studies are being conducted for its practical application2. Multi-carbon compounds (ethylene, ethanol, acetic acid and n-propanol) can be obtained electrochemically from CO2 using only Cu-based electrocatalysts. CO2RR measurements using Cu-based catalysts have generally been performed in neutral-alkaline electrolytes because the competing H2 evolution reaction (HER) can be suppressed. However, CO2 is easily converted to inert (bi)carbonate, which migrates to an anode compartment or is discharged at the outlet of a cathode compartment, and thus, there is a drawback in neutral and alkaline electrolytes from the point of view of substrate utilization efficiency3. Therefore, efficient CO2RR using acidic solutions has been required.

In recent years, although several studies on CO2 reduction under acidic conditions have been reported4, the requirements for C2+ formation in acidic electrolytes are still uncovered. Direct CO electrolysis is more desirable than CO2 electrolysis for studying CO dimerization to C2+ in acidic electrolytes because a constant amount of CO can be supplied to the catalytic surfaces, and local pH variations due to CO2 dissolution can be eliminated. However, compared to CO2RR in acidic solutions, the CO reduction reaction to C2+ in acidic electrolytes has been little studied. In this work, we quantitatively study the CO reduction reaction (CORR) to C2+ products in an acidic solution through experimental gaseous CO electrolysis and multiphysics simulation of the local pH.

We used Cu nanoparticles (CuNPs) as catalysts, which are commonly used in CO2RR. CuNPs were synthesized using a chemical reduction method using NaBH4 as the reductant. The oxidation state of copper nanoparticles is Cu(II), confirmed by XPS and XRD. A catalyst ink was prepared by dispersing 1.7 mg CuNPs in 2.2 μL 5 wt% Nafion solution and 600 μL iso-propanol. 80 μL ink was added dropwise onto the GDE. For CORR measurements, a home-made three-compartment electrochemical cell was employed. A solution of pH 2.0 (0.5 M H3PO4 0.5 M KH2PO4 1.5 M KCl) and pH 1.0 (1.0 M H3PO4 2.0 M KCl) were used for the catholyte. Gas and liquids products were quantified by gas chromatography and 1H-NMR, respectively. A reaction-diffusion model based on Nernst-Planck equation was used to simulate the local pH using COMSOL Multiphysics software. A one-dimensional model was used with a diffusion layer of 100 μm. For simplicity, only proton-consuming reactions were considered. Phosphate equilibrium reactions were introduced.

Electrochemical CO reduction was performed in acidic solutions. Hydrogen evolution was dominant at low current densities (below 50 mA/cm2) in both pH 1.0 and 2.0 solutions. The C2+ production became dominant at 200 mA/cm2, and its faradaic efficiency was almost equivalent to that of neutral and alkaline solutions. We assumed that the suppression of hydrogen evolution was due to the increase in pH at the electrode surface with increasing current density. Therefore, we calculated the local pH by multiphysics simulation. The surface pH suddenly increased to about 13 at 200 mA/cm2 at pH 2.0. Taking into account these results, the selectivity of C2+ increased with increasing pH on the electrode surface. At the conference, we will also present the effect of surface cations on CORR.

References

[1] A. Inoue, T. Harada, S. Nakanishi, K. Kamiya, EES Catal., 2023, 1, 9

[2] K. Kamiya, K. Fujii, M. Sugiyama, S. Nakanishi, Chem Lett., 2021, 50, 166-179

[3] Gu. J., Liu. S., Ni. W., Ren. W., Haussener. S., Hu. X., Nat.Catal.,
2022, 5, 268–276

[4] J. E. Huang, F. Li, A. Ozden, A. S. Rasouli, F. P. G. de Arquer, S. Liu, S. Zhang, M. Luo, X. Wang, Y. Lum, Y. Xu, K. Bertens, R. K. Miao, C. T. Dinh, D. Sinton and E. H. Sargent, Science, 2021, 372, 1074 -1078

Figure 1