Boosting the performance and durability of heterogeneous electrodes for solid oxide electrochemical cells utilizing a data-driven powder-to-power framework

Yang Wang, Chengru Wu, Siyuan Zhao, Zengjia Guo, Minfang Han, Tianshou Zhao, Bingfeng Zu, Qing Du, Meng Ni, Kui Jiao

Research output: Journal article publicationJournal articleAcademic researchpeer-review

Abstract

Solid oxide electrochemical cells (SOCs) hold potential as a critical component in the future landscape of renewable energy storage and conversion systems. However, the commercialization of SOCs still requires further breakthroughs in new material development and engineering designs to achieve high performance and durability. In this study, a data-driven powder-to-power framework has been presented, fully digitizing the morphology evolution of heterogeneous electrodes from fabrication to long-term operation. This framework enables accurate performance prediction over the full life cycle. The intrinsic correlation between microstructural parameters and electrode durability is elucidated through parameter analysis. Rational control of the ion-conducting phase volume fraction can effectively suppress Ni coarsening and mitigate the excessive ohmic loss caused by Ni migration. The initial and degraded electrode performances are attributed to the interplay of multiple parameters. A practical optimization strategy to enhance the initial performance and durability of the electrode is proposed through the construction of the surrogate model and the application of the optimization algorithm. The optimal electrode parameters are determined to accommodate various maximum operation time requirements. By implementing the data-driven powder-to-power framework, it is possible to reduce the degradation rate of Ni-based electrodes from 2.132% to 0.703% kh−1 with a required maximum operation time of over 50,000 h.

Original languageEnglish
Pages (from-to)516-527
Number of pages12
JournalScience Bulletin
Volume68
Issue number5
DOIs
Publication statusPublished - 15 Mar 2023

Keywords

  • Data-driven optimization
  • Electrode performance degradation
  • Long-term operation
  • Powder-to-power framework
  • Solid oxide electrochemical cells

ASJC Scopus subject areas

  • General

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