A Computational Model to Optimize the Electrochemical Reduction of CO2 to Formic Acid Using an Enzymatic Catalyst

Abstract

This work documents the development and subsequent analysis of a transient electrochemical model to predict the electrochemical conversion of CO2 to formic acid (FA) using an enzymatic catalyst. FA has been of recent interest for its applications in hydrogen storage and formic acid-based fuel cells [1]. This process uses an electrochemical charge mediator, commonly methyl viologen (MV) or ethyl viologen (EV) [2], which is initially reduced to a more negative species (i.e. from EV2+ to EV+), then re-oxidized upon reacting with the enzymatic catalyst to produce FA (as HCOO-) from CO2 and protons from the anode.Using an enzymatic catalyst can enable greater selectivity to a particular carbon product compared to traditional metal-based catalysts, which can produce an array of different products [3]. The model was developed in conjunction with experimental investigation to serve as a benchmark for the optimal product conversion of CO2 assuming a stable solution pH and catalyst stability. The model employs transport-based equations for each ionic species of the charge carrier, which will vary based on the initial concentration selected and the applied voltage. Kinetic parameters to determine reaction values are fit to align with existing experimental data.The model uses Butler-Volmer kinetics to estimate the total current in the system as a function of the applied voltage and as a function of estimated experimental parameters. A bulk solution is considered for the electrolytes, but species concentrations are varied across a small diffusion layer (~50 um) between the electrolyte and electrode [4]. For predicting the conversion of CO2 into FA using the enzymatic catalyst and charge carrier species, Michaelis-Menten kinetics are used with appropriate catalyst parameters derived using sampling reactions with a known potassium formate solution and UV-vis spectroscopy.Among the products formed, molecular O2 is factored into the model as it will adversely limit the maximum current in the cell at higher applied voltage, and subsequently will limit the rate of production and efficiency. An O2 scavenger, such as sodium thiosulfate, can limit the contribution of molecular oxygen in the solution, but will not eliminate it. The model assumes that pH remains constant due to the presence of electrolyte buffer in the solution, although the influx of protons will cause a drop in the pH if not immediately converted to FA, and this more acidic solution has been shown to be a significant limitation due to the performance and stability of the catalyst.The results can be analyzed as a function of multiple parameters and operating conditions, although among the most interesting to study are those for the applied voltage and initial charge carrier concentration. There, it can be shown on contour plots that optimal regions for efficiency exist around -0.8 to -1.1 V (vs. Ag/AgCl), and charge carrier concentrations of 0.1 – 10 mM. The trends obtained are in alignment with what has previously been hypothesized [2] but can now also be analyzed in conjunction with other experimental parameters, including the design (sizing) of the electrochemical cell.The primary benefits of the model are in (1) predicting optimal performance when experimental imperfections are removed, (2) rapidly predicting a range of product selectivity and efficiency due to limited resources used to run experiments, primarily for the catalyst, and (3) providing a templating a template with which to iterate upon and consider other value added products, by altering parameters to account for a different catalyst, electrolyte, or charge mediator. The model is presently being developed to include provisions for operating in a flow cell reactor, where considerations to flow rate must be considered and time delay between reduction and production cells. To best match with existing experimental data, additional effects such as pH deterioration and variations in the kinetics with voltage (which can be investigated by cyclic voltammetry experiments) will need to be considered. REFERENCES: Singh AK, Singh S, Kumar A. Hydrogen energy future with formic acid: a renewable chemical hydrogen storage system. Catalysis Science & Technology. 2016;6(1):12-40.Moreno D, Thompson J, Omosebi A, Landon J, Liu K. Electrochemical analysis of charge mediator product composition through transient model and experimental validation. Journal of Applied Electrochemistry. 2022 Nov;52(11):1573-84.Ikeyama S, Amao Y. An Artificial Co‐enzyme Based on the Viologen Skeleton for Highly Efficient CO2 Reduction to Formic Acid with Formate Dehydrogenase. ChemCatChem. 2017 Mar 8;9(5):833-8.Morrison AR, van Beusekom V, Ramdin M, van den Broeke LJ, Vlugt TJ, de Jong W. Modeling the electrochemical conversion of carbon dioxide to formic acid or formate at elevated pressures. Journal of The Electrochemical Society. 2019 Feb 12;166(4):E77. Figure 1