Decoupling Membrane Electrode Assembly Materials Complexity from Fuel Cell Performance through Image-Based Multiphase and Multiphysics Modelling

IF 26 1区 材料科学 Q1 CHEMISTRY, PHYSICAL Advanced Energy Materials Pub Date : 2025-04-10 DOI:10.1002/aenm.202405179
Jianuo Chen, Wenjia Du, Zunmin Guo, Xuekun Lu, Matthew P. Tudball, Xiaochen Yang, Zeyu Zhou, Shangwei Zhou, Alexander Rack, Bratislav Lukic, Paul R. Shearing, Sarah J. Haigh, Stuart M. Holmes, Thomas S. Miller
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Abstract

Proton exchange membrane fuel cells (PEMFCs) are important clean energy technology, yet the material and structural complexity of their membrane electrode assemblies (MEAs) can hamper the development of next-generation structures, as even a subtle change to one component can have a significant impact on others. Mathematical modelling of PEMFC MEAs proves to be one of the few techniques able to decouple this complexity, but the available models are commonly based on over-simplified structures meaning they are less able to inform material design. In this study, an advanced image-based modelling approach is developed to reveal the interplay of material changes in PEMFC MEAs. Using high-temperature PEMFCs as an example system, advanced structural imaging techniques are used to produce a detailed 3D MEA reconstruction which forms the basis for the multiphase and multi-physics model. This allows both the prediction of cell performance and the decoupling the impact of changes to individual structures or components (such as membrane pores, catalyst cracks, and phase migration), on cell behaviour. These phenomena can then be selectively ‘re-coupled’ to deconvolute the interplay of different materials employed within operational cells. The resulting insights provide a mechanistic understanding of MEA performance, guiding the design and optimisation of future PEMFCs.

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通过基于图像的多相和多物理场建模从燃料电池性能中解耦膜电极组装材料的复杂性
质子交换膜燃料电池(pemfc)是一项重要的清洁能源技术,但其膜电极组件(MEAs)的材料和结构复杂性可能会阻碍下一代结构的发展,因为即使一个组件的细微变化也会对其他组件产生重大影响。PEMFC mea的数学建模被证明是能够解耦这种复杂性的少数技术之一,但可用的模型通常基于过度简化的结构,这意味着它们不太能够为材料设计提供信息。在本研究中,开发了一种先进的基于图像的建模方法来揭示PEMFC mea中材料变化的相互作用。以高温pemfc为例,采用先进的结构成像技术生成详细的三维MEA重建,为多相和多物理场模型奠定了基础。这既可以预测细胞性能,也可以解耦单个结构或组件(如膜孔、催化剂裂缝和相迁移)变化对细胞行为的影响。然后,这些现象可以选择性地“重新耦合”,以消除操作单元内使用的不同材料的相互作用。由此产生的见解提供了对MEA性能的机制理解,指导未来pemfc的设计和优化。
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来源期刊
Advanced Energy Materials
Advanced Energy Materials CHEMISTRY, PHYSICAL-ENERGY & FUELS
CiteScore
41.90
自引率
4.00%
发文量
889
审稿时长
1.4 months
期刊介绍: Established in 2011, Advanced Energy Materials is an international, interdisciplinary, English-language journal that focuses on materials used in energy harvesting, conversion, and storage. It is regarded as a top-quality journal alongside Advanced Materials, Advanced Functional Materials, and Small. With a 2022 Impact Factor of 27.8, Advanced Energy Materials is considered a prime source for the best energy-related research. The journal covers a wide range of topics in energy-related research, including organic and inorganic photovoltaics, batteries and supercapacitors, fuel cells, hydrogen generation and storage, thermoelectrics, water splitting and photocatalysis, solar fuels and thermosolar power, magnetocalorics, and piezoelectronics. The readership of Advanced Energy Materials includes materials scientists, chemists, physicists, and engineers in both academia and industry. The journal is indexed in various databases and collections, such as Advanced Technologies & Aerospace Database, FIZ Karlsruhe, INSPEC (IET), Science Citation Index Expanded, Technology Collection, and Web of Science, among others.
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