Collaborative Research: Integrated Measurement and Predictive Modeling of Adsorbate Coverage and Compositional Effects on Catalytic Activity

合作研究：吸附物覆盖率和催化活性的成分影响的综合测量和预测模型

• 批准号: 1264798
• 负责人: William Schneider
• 金额: $ 33.32万
• 依托单位: University of Notre Dame
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-08-15 至 2018-01-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1264798&HistoricalAwards=false
• 关键词: Collaborative; Research; Integrated; Measurement; Predictive

ABSTRACTHeterogeneous, solid catalysts are widely used to promote desirable chemical reactions. One very common example is the automotive catalytic converter, which catalyzes the chemical conversion of the environmentally hazardous components of engine exhaust into benign products. The ?active? catalysts in the catalytic converter contain expensive precious metals, like platinum, palladium, and rhodium as the active metal sites. Other processes critical to society, like the production of ammonia for fertilizer or of gasoline for fuel, all depend on catalysts to promote the key chemical reactions. In many of these cases the available catalysts are expensive, perform less than perfectly, or seriously degrade in performance over time. Further, there are many reactions for which good catalysts are simply unknown. In most cases, heterogeneous catalytic reactions happen at the surface of the catalyst. This interface has traditionally been studied under ultra-high vacuum, where it is relatively easy to tease out the various chemical events. Quantum mechanical, density functional theory (DFT), molecular models are well suited to studying these interfaces and processes in the high vacuum limit. There remains however a gap between these traditional approaches and the real conditions of catalytic interest. It is now well understood that at operating conditions, a catalyst surface is often crowded with lots of molecules and that these molecules can even cause the catalyst surface to change shape or chemical form. To understand and improve heterogeneous catalysts, one must study and model them at these more realistic conditions. The National Science Foundation Catalysis & Biocatalysis Program is awarding three researchers, Professors William Schneider and Franklin Tao of Notre Dame University and Christopher Wolverton of Northwestern University to collaboratively tackle the high-pressure challenge through a combination of advanced computer models and ambient pressure experiments. By combining the expertise of Schneider at Notre Dame in molecular-level modeling of catalytic reactions with the expertise of Wolverton at Northwestern in multi-scale cluster expansion models, tools will be developed to predict the behavior of a metal surface under reaction conditions. The tools will be developed and validated initially against the ambient pressure experiments of Tao at Notre Dame. The workers will study in particular the reactions of CO and NO at platinum and rhodium surfaces, reactions relevant to environmental protection. The students will be exposed to an interdisciplinary, multi-institutional collaborative research program which will lead to cross-fertilization of ideas. Three graduate students advised by the principle investigators will work together on the theory and experiments. The models will be disseminated to the catalyst community, and have the potential to advance both the application of existing catalysts and discovery of design principles for new ones.

突变的固体催化剂被广泛用于促进理想的化学反应。 一个非常普遍的例子是汽车催化转化器，它催化了发动机排气的环境危险组件的化学转化为良性产品。 活跃？催化转化器中的催化剂含有昂贵的贵金属，例如铂，钯和若i位作为活性金属位置。 其他对社会至关重要的过程，例如肥料或汽油燃料的产生，都依赖催化剂来促进关键的化学反应。 在许多情况下，可用的催化剂昂贵，表现不佳或随着时间的推移严重降级。 此外，有许多反应是，好催化剂是完全未知的。在大多数情况下，异质性催化反应发生在催化剂的表面。传统上，该界面是在超高真空下研究的，在该真空吸尘器下，取消各种化学事件相对容易。 量子机械，密度功能理论（DFT），分子模型非常适合于在高真空极限中研究这些界面和过程。 但是，这些传统方法与催化兴趣的实际条件之间仍然存在差距。 现在众所周知，在工作条件下，催化剂表面通常挤满了很多分子，并且这些分子甚至会导致催化剂表面改变形状或化学形式。 要了解和改善异质催化剂，必须在这些更现实的条件下研究和建模它们。 国家科学基金会催化与生物催化计划正在授予三名研究人员，教授威廉·施耐德（William Schneider）和巴黎圣母院（Notre Dame University）的富兰克林·陶（Franklin Tao）和西北大学的克里斯托弗·沃尔弗顿（Christopher Wolverton），通过高级计算机模型和环境压力实验的结合来协作解决高压挑战。 通过将施耐德在巴黎圣母院的专业知识结合在催化反应的分子级建模中，以及在多尺度群集扩展模型中西北部的沃尔弗顿的专业知识中，将开发工具来预测在反应条件下金属表面的行为。 这些工具最初将针对巴黎圣母院的Tao的环境压力实验开发和验证。 工人将特别研究CO和NO在铂和铑表面的反应，与环境保护有关。 学生将接触一项跨学科的多机构合作研究计划，这将导致思想的交叉侵入。主要研究人员建议的三名研究生将在理论和实验上共同努力。 这些模型将被传播到催化剂社区，并有可能促进现有催化剂的应用以及发现新的催化剂。