Technical Papers
Feb 4, 2022

Electrochemical Modeling and Simulation of CO2 Reduction in Solid Oxide Electrolysis Cells

Publication: Journal of Hazardous, Toxic, and Radioactive Waste
Volume 26, Issue 2

Abstract

Mathematical models for electrochemical conversion of CO2 to CO in a solid oxide electrolysis cell (SOEC) are formulated. Model simulation has been carried out on a button cell having Ni-yttria stabilized zirconia (YSZ) composite as cathode, YSZ as electrolyte, and lanthanum strontium manganite (LSM) as anode material. The simulation results were used to estimate the overpotentials associated with the electrochemical reduction reactions of CO2 to CO and hence predict the overall performance of a SOEC under varying operating conditions. Overpotential includes the contribution from activation, concentration, and ohmic losses corresponding to cathode, anode, and electrolyte components of the SOEC. Fick’s model, the Butler–Volmer equation, and Ohm’s law are used to estimate the values of concentration, activation, and ohmic overpotential losses, respectively. Of the three, ohmic overpotential dominates over other losses throughout the operating voltages. The calculated value of ohmic overpotential loss is 0.19 V at an operating voltage of 1.2 V and current density of 0.8 A/cm2. The model is simulated for varying fuel gas compositions (CO2/CO = 99/01, 70/30, 50/50, and 30/70) at a temperature of 1,073 K, and corresponding current–voltage characteristics of the SOEC are predicted. As the CO2 content in fuel gas increases from 30% to 99%, the estimated current density is raised from −0.28 to −0.76 A/cm2 at an applied potential of 1.1 V, indicating the presence of CO2 in fuel and leading to improved performance of the SOEC. Similarly, at higher temperatures, part of the thermal energy contributes to activation of CO2 molecules; hence, the calculated current density at a particular applied voltage (1 V) is enhanced from −0.2 to −0.6 A/cm2 with a rise in temperature from 1,073 to 1,123 K of the SOEC system.

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Notation

The following symbols are used in this paper:
a
anode;
Bg
permeability (cm2);
c
cathode;
DCO2eff
effective diffusion coefficient of CO2 (meter square per second);
DCO2,k
Knudsen diffusion coefficient of CO2;
DCO2–CO
molecular diffusion coefficient for CO2–CO binary system;
da
anode thickness (µm);
dc
cathode thickness (µm);
E
Nernst potential (V);
E0
equilibrium potential at standard pressure (V);
F
Faraday constant (C · mol−1);
J
current density (A · cm−2);
J0
exchange current density (A · cm−2);
L
electrolyte thickness (µm);
M
molecular weight;
MCO
molecular weight of CO;
MCO2
molecular weight of CO2;
n
number of electrons produced per reaction;
p
partial pressure (bar);
p0
partial pressure (bar);
R
universal gas constant (J · mol−1 · K−1);
r
mean pore radius (µm);
T
operating temperature (K);
β
charge transfer coefficient;
ηact
activation overpotential (V);
ηconc
concentration overpotential (V);
ηohmic
ohmic overpotential (V);
µ
dynamic viscosity (kg · cm−1 · s−1);
σCO2–CO
characteristic length of species; and
D
diffusion collision integral.

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Go to Journal of Hazardous, Toxic, and Radioactive Waste
Journal of Hazardous, Toxic, and Radioactive Waste
Volume 26Issue 2April 2022

History

Received: Aug 18, 2021
Accepted: Oct 23, 2021
Published online: Feb 4, 2022
Published in print: Apr 1, 2022
Discussion open until: Jul 4, 2022

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Shivika Sharma [email protected]
Research Scholar, Dept. of Chemical Engineering, Malaviya National Institute of Technology Jaipur, Jaipur 302017, India. Email: [email protected]
Junior Research Fellow, Dept. of Chemical Engineering, Malaviya National Institute of Technology Jaipur, Jaipur 302017, India. Email: [email protected]
Assistant Professor, Dept. of Chemical Engineering, Malaviya National Institute of Technology Jaipur, Jaipur 302017, India (corresponding author). ORCID: https://orcid.org/0000-0002-7729-2924. Email: [email protected]

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  • Challenges and opportunities of process intensification for the conversion of waste CO to liquid fuels , Chemical Engineering and Processing - Process Intensification, 10.1016/j.cep.2023.109329, 186, (109329), (2023).

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