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Advancing the multiscale understanding on solid oxide electrolysis cells via modelling approaches: a review
journal contribution
posted on 2021-03-01, 15:29 authored by Zheng Li, Hao Zhang, Haoran Xu, Jin XuanSolid 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.
Funding
Newton Advanced Fellowship supported by the Royal Society (grant No. NAF\R1\180146)
Engineering and Physical Sciences Research Council (EPSRC) under grant number EP/V011863/1
History
School
- Aeronautical, Automotive, Chemical and Materials Engineering
Department
- Chemical Engineering
Published in
Renewable and Sustainable Energy ReviewsVolume
141Publisher
Elsevier BVVersion
- AM (Accepted Manuscript)
Rights holder
© ElsevierPublisher statement
This paper was accepted for publication in the journal Renewable and Sustainable Energy Reviews and the definitive published version is available at https://doi.org/10.1016/j.rser.2021.110863.Acceptance date
2021-02-19Publication date
2021-02-24Copyright date
2021ISSN
1364-0321Publisher version
Language
- en
Depositor
Prof Jin Xuan. Deposit date: 28 February 2021Article number
110863Usage metrics
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