Multiphysics Modeling and Performance Optimization of CO2/H2O Co-Electrolysis in Solid Oxide Electrolysis Cells: Temperature, Voltage, and Flow Configuration Effects

This study developed a two-dimensional multiphysics-coupled model for co-electrolysis of CO2 and H2O in solid oxide electrolysis cells (SOECs) using COMSOL Multiphysics, systematically investigating the influence mechanisms of key operating parameters including temperature, voltage, feed ratio, and flow configuration on co-electrolysis performance. The results demonstrate that increasing temperature significantly enhances CO2 electrolysis, with the current density increasing over 12-fold when temperature rises from 923 K to 1423 K. However, the H2O electrolysis reaction slows beyond 1173 K due to kinetic limitations, leading to reduced H2 selectivity. Higher voltages simultaneously accelerate all electrochemical reactions, with CO and H2 production at 1.5 V increasing by 15-fold and 13-fold, respectively, compared to 0.8 V, while the water–gas shift reaction rate rises to 6.59 mol/m3·s. Feed ratio experiments show that increasing CO2 concentration boosts CO yield by 5.7 times but suppresses H2 generation. Notably, counter-current operation optimizes reactant concentration distribution, increasing H2 and CO production by 2.49% and 2.3%, respectively, compared to co-current mode, providing critical guidance for reactor design. This multiscale simulation reveals the complex coupling mechanisms in SOEC co-electrolysis, offering theoretical foundations for developing efficient carbon-neutral technologies.

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Publication Details

Journal
Energies
Published
2025-07-24
DOI
https://doi.org/10.3390/en18153941
Citations
2
Primary Topic
Advancements in Solid Oxide Fuel Cells
Type
article
Field-Weighted Citation Impact
1.04

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article

Multiphysics Modeling and Performance Optimization of CO2/H2O Co-Electrolysis in Solid Oxide Electrolysis Cells: Temperature, Voltage, and Flow Configuration Effects

Shunai Che, Rui Xue, Jiale Chen, Jinping Wang
2 citations
Energies
Advancements in Solid Oxide Fuel Cells
1.04
article

Multiphysics Modeling and Performance Optimization of CO2/H2O Co-Electrolysis in Solid Oxide Electrolysis Cells: Temperature, Voltage, and Flow Configuration Effects

Shunai Che, Rui Xue, Jiale Chen, Jinping Wang
article en
2 citations

Abstract

This study developed a two-dimensional multiphysics-coupled model for co-electrolysis of CO2 and H2O in solid oxide electrolysis cells (SOECs) using COMSOL Multiphysics, systematically investigating the influence mechanisms of key operating parameters including temperature, voltage, feed ratio, and flow configuration on co-electrolysis performance. The results demonstrate that increasing temperature significantly enhances CO2 electrolysis, with the current density increasing over 12-fold when temperature rises from 923 K to 1423 K. However, the H2O electrolysis reaction slows beyond 1173 K due to kinetic limitations, leading to reduced H2 selectivity. Higher voltages simultaneously accelerate all electrochemical reactions, with CO and H2 production at 1.5 V increasing by 15-fold and 13-fold, respectively, compared to 0.8 V, while the water–gas shift reaction rate rises to 6.59 mol/m3·s. Feed ratio experiments show that increasing CO2 concentration boosts CO yield by 5.7 times but suppresses H2 generation. Notably, counter-current operation optimizes reactant concentration distribution, increasing H2 and CO production by 2.49% and 2.3%, respectively, compared to co-current mode, providing critical guidance for reactor design. This multiscale simulation reveals the complex coupling mechanisms in SOEC co-electrolysis, offering theoretical foundations for developing efficient carbon-neutral technologies.

EnergiesVol. 18(15)
Nanjing Institute of Technology (CN)
Government of Jiangsu Province
Openalex Percentile: Top 23%
Advancements in Solid Oxide Fuel Cells
1.04
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Multiphysics Modeling and Performance Optimization of CO2/H2O Co-Electrolysis in Solid Oxide Electrolysis Cells: Temperature, Voltage, and Flow Configuration Effects — Shunai Che, Rui Xue, et al. · Energies (2025) | TGRS Research Map | TGRS