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Updated: May 29, 2025

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固体氧化物燃料电池建模的全面审查:从大型系统到精细电极
Zhen Wu1, Pengfei Zhu1, Yakun Huang1
1School of Chemical Engineering and Technology, Xi'an Jiaotong University, Xi'an 710049, China.
Chemical reviews
|February 7, 2025
概括
本综述按规模分类固体氧化物燃料电池 (SOFC) 模拟模型,指导研究人员选择合适的工具. 它强调了新的AI辅助和异质模型,以提高SOFC的性能和耐用性.
科学领域:
- 材料科学与工程 材料科学与工程
- 化学工程是化学工程的重要组成部分.
- 能源系统 能源系统
背景情况:
- 固体氧化物燃料电池 (SOFC) 的商业化取决于提高系统性能和耐用性.
- 通过实验进行优化是昂贵且耗时的,因此数值建模至关重要.
- 现有的审查缺乏对实用,面向问题的模型的分类,并忽略了新兴的人工智能辅助和异质模型.
研究的目的:
- 提供SOFC模拟模型的实用,面向问题的分类.
- 审查和分析SOFC建模的最新进展,包括人工智能辅助和异质方法.
- 引导研究人员选择适合SOFC系统,堆,电池和电极设计的模型.
主要方法:
- 关于SOFC模拟研究的综合文献综述.
- 基于规模的模型分类 (系统,堆,单元,电极).
- 深入分析传统和新兴的建模技术,包括人工智能辅助和异质模型.
主要成果:
- 基于其应用规模的SOFC模型的分类.
- 识别新兴模型 (人工智能辅助,异质) 对于加速复杂的模拟和描述中观行为至关重要.
- 一个对SOFC模拟景观的结构化概述,有助于模型选择.
结论:
- 数字建模对于具有成本效益的SOFC优化至关重要.
- 基于规模的分类和新型模型的纳入对于指导SOFC设计至关重要.
- 这篇评论是研究人员导航SOFC模拟工具的宝贵资源.
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