【摘要】 固体氧化物电池将在未来可再生能源储存转换系统中占据重要位置.但SOCs受制于低耐久度的影响,目前仍需在新材料开发和工程设计方面取得进一步的突破以实现商业化.这项研究报道了一个数据驱动的粉体-能量框架（Powder-to-power framework,P2PF）,通过实现从制备到长时运行的异质电极形貌演化数字化,实现了对于整个生命周期的性能预测.首先通过参数分析阐明了微结构参数对于燃料电极长期性能的内在影响机制,发现合理控制离子导电相的体积分数不仅可以有效抑制镍粗化,还是减少镍迁移引起的欧姆损失增加的关键.电极初始性能和性能衰减率是多参数耦合作用的结果.所构建代理模型被应用于多目标遗传算法以提出简单可行的耐久度优化策略.数据驱动的粉体-能量框架确定了满足不同最大运行时长要求的最佳电极制备参数,并将镍基电极的降解率从基本工况下2.132%kh^-1降低到0.703%kh^-1（最大运行时长大于50000 h）.更多还原

【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^-1with a required maximum operation time of over 50,000 h.更多还原