Visualization of liquid water in a lung-inspired flow-field based polymer electrolyte membrane fuel cell via neutron radiography

Visualization of liquid water in a lung-inspired flow-field based polymer electrolyte membrane fuel cell via neutron radiography
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DOI:
10.1016/j.energy.2018.12.143
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发表时间:
2019-03-01
期刊:
影响因子:
9
通讯作者:
Coppens, M. -O.
Coppens, M. -O.
中科院分区:
工程技术1区
文献类型:
--
作者:
Cho, J. I. S.;Neville, T. P.;Coppens, M. -O.

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肺部激发的分形流场在提高聚合物电解质膜燃料电池(pemfc)的性能方面具有巨大的潜力,可以提供均匀的气体分布在电极上,并确保整个系统的熵产最小。然而,分形流场对洪水的固有敏感性使其在高湿条件下的应用不充分。深入了解肺激发流场中的水管理对于实施替代出口通道几何形状或工程除水策略以减轻洪水是必不可少的。在这里,液态水的形成和运输通过肺激发和蛇形流场为基础的pemfc评估使用中子射线摄影。结果表明,分形流场N=4代的交错出口通道由于气速慢、通道尺寸窄,易发生水淹,导致性能显著恶化。中子图像还阐明了确保分形流场内部通道结构的重要性,以防止液态水通过芯排回流,以及由狭窄的入口气体通道和疏水气体扩散层引起的毛细压力积聚。(C) 2019作者。Elsevier Ltd.出版。
Lung-inspired, fractal flow-fields hold great potential in improving the performance of polymer electrolyte membrane fuel cells (PEMFCs) by providing uniform gas distribution across the electrodes and ensuring minimum entropy production in the whole system. However, the inherent susceptibility of the fractal flow-fields to flooding renders their use inadequate at high humidity conditions. In-depth understanding of water management in lung-inspired flow-fields is indispensable for the implementation of alternative outlet channel geometries or engineered water removal strategies to alleviate flooding. Here, liquid water formation and transport across the lung-inspired and serpentine flow-field based PEMFCs are evaluated using neutron radiography. The results reveal a propensity to flooding in the interdigitated outlet channels of the fractal flow-field with N=4 generations as a result of slow gas velocity and narrow channel dimensions, which leads to significant performance deterioration. Neutron images also elucidate the importance of ensuring a well-defined internal channel structure of the fractal flow-fields to prevent backflow of liquid water via wicking and capillary pressure build-up arising from the narrow inlet gas channels and hydrophobic gas diffusion layer. (C) 2019 The Authors. Published by Elsevier Ltd.