Synthesis and Monte Carlo Modeling of Selective CO oxidation Catalysts for Fuel Cells (TSE99-A)

摘要提案题目：燃料电池选择性CO氧化催化剂的合成与蒙特卡罗建模提案号：cts -9985449首席研究员：Erdogan gulari单位：密歇根大学该项目研究燃料电池电极CO中毒问题。为了使燃料电池在汽车应用中成功使用，燃料气体CO含量必须降低到10ppm以下。新型氧化铝负载铂催化剂将用于选择性氧化CO与氧。目标是在大量氢气存在的情况下，使用1%的氧气，将二氧化碳浓度降低到2 ppm。催化剂将通过溶胶-凝胶方法制备，其中胶体铂纳米晶体在凝胶形成时被纳入氧化铝凝胶中。此外，由于第二种合成方法将允许将预先合成的胶体铂晶体并入氧化铝凝胶中。为了了解晶体尺寸、金属载荷和燃料气体组分之间的相互作用，将开发一个蒙特卡罗模型。通过根据表面科学结果分配粘附系数和反应速率，pi将开发一个模型来预测实验观察到的现象。该模型还将用于指导催化剂的设计。这项工作可能会导致燃料电池的改进，以减少车辆的排放。

AbstractProposal Title: Synthesis and Monte Carlo Modeling of Selective CO Oxidation Catalysts for Fuel CellsProposal Number: CTS-9985449Principal Investigator: Erdogan GulariInstitution: University of MichiganThis project addresses the problem of CO poisoning of fuel-cell electrodes. To enable successful use of fuel cells in vehicular applications, the fuel gas CO content must be reduced below 10 ppm. Novel alumina supported platinum catalysts will be used to selectively oxidize CO with oxygen. The goal is to reduce the level of CO to 2 ppm using 1% oxygen in the presence of large amounts of hydrogen. Catalysts will be prepared by the sol-gel method in which colloidal platinum nanocrystallites are incorporated into an alumina gel as the gel is forming. In addition, as second method of synthesis will permit pre-synthesized colloidal platinum crystallites to be incorporated into the alumina gel. To understand the interaction between crystallite size, metal loading, and the components of the fuel gas, a Monte Carlo model will be developed. By assigning sticking coefficients and reaction rates based on surface science results, the PIs will develop a model that predicts the experimentally observed phenomena. The model will also be used to guide catalyst design. This work could lead to improvements in fuel cells for reducing emissions in vehicles.