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Advancing the multiscale understanding on solid oxide electrolysis cells via modelling approaches: A review

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  • Li, Zheng
  • Zhang, Hao
  • Xu, Haoran
  • Xuan, Jin

Abstract

Solid oxide electrolysis cell (SOEC) is a clean and highly efficient technology that converts electrical energy into chemical energy, which is regarded as a promising approach to enable hydrogen production, carbon dioxide utilization and nitrogen reduction, and more. One of the main challenges faced by SOEC is performance descending. Numerical modelling is expected to provide insights on performance evolution and material degradation. Different assumptions and methodologies are applied to model the physicochemical processes in a length scale from molecule scale to system scale. It is rational and can be brought great convenience into modelling to make assumptions and simplifications when focusing on a single length scale, however, valuable details can be missing. Multiscale modelling is expected to maintain more information and generate a systematic understanding of the working mechanism of SOEC. In this paper, the modelling methods at various scale levels are summarized. Then, the recent advances in numerical studying on SOEC are reviewed with a focus on multiscale modelling works bridging two or more contiguous length scales. The challenges and future research directions are proposed to promote the multiscale modelling.

Suggested Citation

  • Li, Zheng & Zhang, Hao & Xu, Haoran & Xuan, Jin, 2021. "Advancing the multiscale understanding on solid oxide electrolysis cells via modelling approaches: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 141(C).
  • Handle: RePEc:eee:rensus:v:141:y:2021:i:c:s136403212100157x
    DOI: 10.1016/j.rser.2021.110863
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    2. Yan Shao & Yongwei Li & Zaiguo Fu & Jingfa Li & Qunzhi Zhu, 2023. "Numerical Investigation on the Performance of IT-SOEC with Double-Layer Composite Electrode," Energies, MDPI, vol. 16(6), pages 1-20, March.
    3. He, Qijiao & Li, Zheng & Zhao, Dongqi & Yu, Jie & Tan, Peng & Guo, Meiting & Liao, Tianjun & Zhao, Tianshou & Ni, Meng, 2023. "A 3D modelling study on all vanadium redox flow battery at various operating temperatures," Energy, Elsevier, vol. 282(C).
    4. Li, Yongwei & Fu, Zaiguo & Li, Jingfa & Shao, Yan & Zhu, Qunzhi & Yuan, Binxia, 2024. "Effects of structural parameters of double-layer electrode on co-electrolysis in a solid oxide electrolysis cell," Energy, Elsevier, vol. 287(C).
    5. Li, Zheng & Yu, Jie & Wang, Chen & Bello, Idris Temitope & Yu, Na & Chen, Xi & Zheng, Keqing & Han, Minfang & Ni, Meng, 2024. "Multi-objective optimization of protonic ceramic electrolysis cells based on a deep neural network surrogate model," Applied Energy, Elsevier, vol. 365(C).
    6. Salomone, Fabio & Marocco, Paolo & Ferrario, Daniele & Lanzini, Andrea & Fino, Debora & Bensaid, Samir & Santarelli, Massimo, 2023. "Process simulation and energy analysis of synthetic natural gas production from water electrolysis and CO2 capture in a waste incinerator," Applied Energy, Elsevier, vol. 343(C).

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