Correlative X-ray Tomographic Imaging of Catalyst Layer Degradation in Fuel Cells

被引:24
|
作者
White, Robin T. [1 ]
Ramani, Dilip [1 ]
Eberhardt, Sebastian [1 ]
Najm, Marina [1 ]
Orfino, Francesco P. [1 ]
Dutta, Monica [2 ]
Kjeang, Erik [1 ]
机构
[1] Simon Fraser Univ, Sch Mechatron Syst Engn, Fuel Cell Res Lab FCReL, Surrey, BC V3T 0A3, Canada
[2] Ballard Power Syst, Burnaby, BC V5J 5J8, Canada
基金
加拿大自然科学与工程研究理事会; 加拿大创新基金会;
关键词
GAS-DIFFUSION LAYERS; CARBON CORROSION; ACCELERATED DEGRADATION; MEMBRANE DEGRADATION; FAILURE ANALYSIS; LIQUID WATER; 3D ANALYSIS; PORE; ELECTRODES; POROSITY;
D O I
10.1149/2.0121913jes
中图分类号
O646 [电化学、电解、磁化学];
学科分类号
081704 ;
摘要
Effective catalyst layer design is vital for high-performing polymer electrolyte fuel cells. However, the desired catalyst layer structure may be compromised by operational degradation, causing performance decay. The present work investigates the multi-scale catalyst layer structure and properties across different stages of degradation, including liquid water distribution in an operating fuel cell. A correlative, multi-scale imaging workflow with a combined analysis by operando lab-based micro-X-ray computed tomography (XCT) and nano-XCT is developed for this purpose. From operando XCT results, the catalyst layer solid area fraction was found to gradually decrease by 25% with crack formation and severe localized corrosion accompanied by up to 50% thinning and significantly altered liquid water distribution. Localized degradation features such as nano-scale cracks and internal pore-size distribution changes were resolved using nano-XCT and tracked by 3+1D imaging at different stages of degradation. Porosity changes quantified by nano-XCT on the order of 40% from beginning-of-life to end-of-life with reduction in connected pore fraction were observed as well as increase in average pore size by 50%. The effect of changes at the nano-scale on diffusion properties were calculated and an empirical model is proposed for degraded catalyst layer structures where Knudsen effects are dominant. (C) The Author(s) 2019. Published by ECS.
引用
收藏
页码:F914 / F925
页数:12
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