International Collaboration in Chemistry: First Principles Multi-Lattice Kinetic Monte Carlo Simulations of NOx Storage Reduction Catalysts

芝加哥伊利诺伊大学的Randall Meyer教授在化学系化学催化项目和国际科学与工程办公室的支持下，与慕尼黑工业大学的Karsten Reuter教授合作开展研究，开发了一种综合多尺度理论方法，将DFT和多晶格第一性原理动力学蒙特卡罗（kMC）方法结合起来，以获得对表面的基本理解氧化还原循环工况下废气催化剂的反应化学。所研究的具体应用是用于NOx存储还原（NSR）催化剂体系的PdO (101)/Pd（100）表面。将开发特定材料和时间相关的模拟工具，这些工具可以跟踪系统在NSR周期宏观时间尺度上的演化，同时考虑原子尺度上的站点异质性和演化表面的空间分布。路透社教授是由德国资助机构DFG资助的。从基本催化的角度来看，以原子级分辨率和排气系统运行周期的时间尺度跟踪表面形态演变的能力是重要的。所提出的方法也可能影响其他多相催化系统的模拟。它也将有重要的实际应用，如在汽车的燃油经济性。学生将接受计算催化方面的培训，并将通过学生交换计划接触国际研究经验，并有机会与德国的研究人员建立联系。

Professor Randall Meyer of the University of Illinois at Chicago is supported by the Chemical Catalysis Program in the Division of Chemistry and the Office of International Science and Engineering to conduct research in collaboration with Professor Karsten Reuter of the Technical University of Munich to develop an integrated multi-scale theoretical approach combining DFT and a multi-lattice first-principles kinetic Monte Carlo (kMC) approach to gain a fundamental understanding of the surface reaction chemistry of exhaust catalysts operating under cycling conditions between oxidizing and reducing environments. The specific application to be investigated is the PdO (101)/Pd (100) surface for the NOx storage reduction (NSR) catalyst system. Material-specific and time-dependent simulation tools that can follow the evolution of the system over the macroscopic time-scales of NSR cycles, while simultaneously accounting for the atomic-scale site heterogeneity and spatial distributions at the evolving surface, will be developed. Professort Reuter is funded by the German funding agency, the DFG. The ability to follow the evolution of surface morphology with atomic-level resolution and at the timescale of a cycle of the exhaust system operation is important from a fundamental catalysis point of view. The proposed methodology is likely to impact simulations of other heterogeneous catalytic systems as well. It will also have important practical applications, such as in automotive vehicles fuel economy. Students will be trained in computational catalysis and will be exposed to an international research experience with opportunities to network with researchers in Germany through a student exchange plan.