School of Minerals and Energy Resources Engineering, University of New South Wales, Sydney, NSW, 2052, Australia.
School of Chemistry, University of New South Wales, Sydney, NSW, 2052, Australia.
Nat Commun. 2023 Feb 14;14(1):745. doi: 10.1038/s41467-023-35973-8.
Proton exchange membrane fuel cells, consuming hydrogen and oxygen to generate clean electricity and water, suffer acute liquid water challenges. Accurate liquid water modelling is inherently challenging due to the multi-phase, multi-component, reactive dynamics within multi-scale, multi-layered porous media. In addition, currently inadequate imaging and modelling capabilities are limiting simulations to small areas (<1 mm) or simplified architectures. Herein, an advancement in water modelling is achieved using X-ray micro-computed tomography, deep learned super-resolution, multi-label segmentation, and direct multi-phase simulation. The resulting image is the most resolved domain (16 mm with 700 nm voxel resolution) and the largest direct multi-phase flow simulation of a fuel cell. This generalisable approach unveils multi-scale water clustering and transport mechanisms over large dry and flooded areas in the gas diffusion layer and flow fields, paving the way for next generation proton exchange membrane fuel cells with optimised structures and wettabilities.
质子交换膜燃料电池以氢气和氧气为燃料，生成清洁电能和水，但会面临液态水供应不足的问题。由于多相、多组分和多尺度、多层多孔介质中的反应动力学，准确的液态水建模具有内在的挑战性。此外，目前成像和建模能力不足，限制了模拟在小区域(<1mm)或简化结构中的应用。在此，通过 X 射线微计算机断层扫描、深度学习超分辨率、多标签分割和直接多相模拟，实现了水模型的改进。所得到的图像具有最高的分辨率（16mm，体素分辨率为 700nm），并且是燃料电池中最大的直接多相流模拟。这种通用方法揭示了在气体扩散层和流场的大干燥区和水淹区中的多尺度水簇集和输运机制，为具有优化结构和润湿性的下一代质子交换膜燃料电池铺平了道路。
