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质子交换膜燃料电池催化剂层中离聚物的结构与导电性:基于模型的分析

Structure and conductivity of ionomer in PEM fuel cell catalyst layers: a model-based analysis.

作者信息

Olbrich W, Kadyk T, Sauter U, Eikerling M, Gostick J

机构信息

Theory and Computation of Energy Materials (IEK-13), Institute of Energy and Climate Research, Forschungszentrum Jülich GmbH, 52425, Jülich, Germany.

Robert Bosch GmbH, Corporate Research, 71272, Renningen, Germany.

出版信息

Sci Rep. 2023 Aug 29;13(1):14127. doi: 10.1038/s41598-023-40637-0.

Abstract

Efforts in design and optimization of catalyst layers for polymer electrolyte fuel cells hinge on mathematical models that link electrode composition and microstructure with effective physico-chemical properties. A pivotal property of these layers and the focus of this work is the proton conductivity, which is largely determined by the morphology of the ionomer. However, available relations between catalyst layer composition and proton conductivity are often adopted from general theories for random heterogeneous media and ignore specific features of the microstructure, e.g., agglomerates, film-like structures, or the hierarchical porous network. To establish a comprehensive understanding of the peculiar structure-property relations, we generated synthetic volumetric images of the catalyst layer microstructure. In a mesoscopic volume element, we modeled the electrolyte phase and calculated the proton conductivity using numerical tools. Varying the ionomer morphology in terms of ionomer film coverage and thickness revealed two limiting cases: the ionomer can either form a thin film with high coverage on the catalyst agglomerates; or the ionomer exists as voluminous chunks that connect across the inter-agglomerate space. Both cases were modeled analytically, adapting relations from percolation theory. Based on the simulated data, a novel relation is proposed, which links the catalyst layer microstructure to the proton conductivity over a wide range of morphologies. The presented analytical approach is a versatile tool for the interpretation of experimental trends and it provides valuable guidance for catalyst layer design. The proposed model was used to analyze the formation of the catalyst layer microstructure during the ink stage. A parameter study of the initial ionomer film thickness and the ionomer dispersion parameter revealed that the ionomer morphology should be tweaked towards well-defined films with high coverage of catalyst agglomerates. These implications match current efforts in the experimental literature and they may thus provide direction in electrode materials research for polymer electrolyte fuel cells.

摘要

聚合物电解质燃料电池催化剂层的设计和优化工作依赖于数学模型,这些模型将电极组成和微观结构与有效的物理化学性质联系起来。这些层的一个关键性质以及本工作的重点是质子传导率,它在很大程度上由离聚物的形态决定。然而,催化剂层组成与质子传导率之间的现有关系通常是从随机非均匀介质的一般理论中采用的,并且忽略了微观结构的特定特征,例如团聚体、膜状结构或分级多孔网络。为了全面理解独特的结构 - 性质关系,我们生成了催化剂层微观结构的合成体积图像。在一个介观体积元中,我们对电解质相进行建模,并使用数值工具计算质子传导率。通过改变离聚物膜覆盖率和厚度方面的离聚物形态,揭示了两种极限情况:离聚物可以在催化剂团聚体上形成具有高覆盖率的薄膜;或者离聚物以大量块体的形式存在,这些块体跨越团聚体间空间相连。这两种情况都采用渗流理论的关系进行了分析建模。基于模拟数据,提出了一种新的关系,该关系在广泛的形态范围内将催化剂层微观结构与质子传导率联系起来。所提出的分析方法是解释实验趋势的通用工具,并且为催化剂层设计提供了有价值的指导。所提出的模型用于分析墨水阶段催化剂层微观结构的形成。对初始离聚物膜厚度和离聚物分散参数的参数研究表明,离聚物形态应调整为具有高催化剂团聚体覆盖率的明确薄膜。这些结论与实验文献中的当前研究工作相匹配,因此它们可能为聚合物电解质燃料电池的电极材料研究提供方向。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2909/10465542/3821c8662620/41598_2023_40637_Fig1_HTML.jpg

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