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Numerical Modeling of Polymer Electrolyte Fuel Cell Catalyst Layer with Different Carbon Supports

机译：不同碳载体的聚合物电解质燃料电池催化剂层的数值模拟

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The Monte Carlo simulation method is used to carry out numerical modelling of the polymerelectrolyte membrane fuel cell (PEMFC) catalyst layer with a random catalyst particles distribution ina polymer matrix. The approaches of mass transport and electrochemical kinetics are applied forestimation of potential distribution and current generation in the catalyst layer. It is shown that largeparticles of the catalyst support (agglomerates of nanofibers) provide percolation for electron transportat a lower concentration in comparison with compact catalyst support particles (i.e. Vulcan XC-72R).Mixtures of such supports also have a lower percolation threshold. It gives the possibility to increasepolymer concentration, stabilise water balance and decrease ohmic losses for ion transport in thecatalyst layer. The numerical estimations demonstrate the possibility of precious metal loadingreduction up to 30% and the increase of performance (current density) up to 20% just due to additionof carbon nanofibers in the catalyst layers. In the experimental study we reached an increase ofPEMFC current density for about 10% when we used the Vulcan XC-72R supported Pt catalysttogether with the Pt catalysts on nanofibres.
机译：使用蒙特卡罗模拟方法对聚合物基质中具有随机催化剂颗粒分布的聚合物电解质膜燃料电池（PEMFC）催化剂层进行数值模拟。传质和电化学动力学的方法适用于对催化剂层中的电势分布和电流产生进行演算。结果表明，与致密的催化剂载体颗粒（即Vulcan XC-72R）相比，大颗粒的催化剂载体（纳米纤维的团聚体）以较低的浓度提供了电子传输的渗滤，这种载体的混合物也具有较低的渗滤阈值。它提供了增加聚合物浓度，稳定水平衡并减少用于离子在催化剂层中传输的欧姆损失的可能性。数值估算表明，仅由于在催化剂层中添加了碳纳米纤维，贵金属负载量降低的可能性高达30％，性能（电流密度）的提高高达20％。在实验研究中，当我们在纳米纤维上使用Vulcan XC-72R负载的Pt催化剂和Pt催化剂时，PEMFC电流密度增加了约10％。

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