Non-Mean Field Treatments of Surface Chemistry: Incorporating Adsorbate-Adsorbate Interactions into Deterministic Kinetic Theories

普渡大学的Jeffrey格里利获得了化学系化学催化项目的奖项，以新的理论方法研究非均相催化剂。 多相催化剂加速了化学物质向有价值产品的转化，它们支撑了许多具有重要技术意义的化学过程，从塑料生产到燃料电池发电。 这些催化剂通常由金属纳米颗粒组成，其表面断裂并在分子中形成化学键以产生有价值的产品。 这些分子转变如何发生的基本模型已经为许多化学反应开发出来，并且极大地增强了对这些转变的理解和新催化材料的设计。 然而，这些模型在描述相关的分子过程时往往会做出显著的近似，包括假设反应分子和产物随机分布在催化剂表面，并且彼此不相互作用。 改进的理论描述的发展，纠正这些近似值，并明确描述当分子彼此强烈相互作用时反应如何变化，这反过来又是该项目的中心焦点。 改进的模型将导致更准确的描述多相催化过程，并最终可能促进改进的催化剂的设计。为了更广泛的影响，新的能力和软件将提供给催化社区。外联和教育工作将集中在高中学生在他们的学术道路的早期阶段，以鼓励追求STEM研究。PI将集中精力吸引来自不同和代表性不足的群体的学生。这项活动将是PI成功努力的延续，学生将与PI和研究生配对，进行量身定制的研究项目。表面动力学的平均场理论允许关于非均相催化过程的关键信息，包括整体反应速率，有效活化势垒和反应级数，根据催化剂表面上发生的基元反应步骤和这些基元步骤的速率常数的组合知识来预测。尽管这些理论的力量，但是，平均场近似开始打破表面吸附物之间的强相互作用的条件下，有必要开发表面动力学建模技术，直接将非平均场效应，而在同一时间，保持强大的物理和机械的见解，自然出现从确定性平均场的描述。 在这项工作中，分析或半分析校正平均场表达式的平衡常数和速率常数的基元反应将开发正方形平面和六边形催化剂表面。 这些表达式，这将是基于Bethe-Peierls近似簇变分法，将被用来确定数学和概念的原则，描述当非平均场效应将显着影响表面催化。 由此产生的形式主义，这将确定性地处理非平均场效应，同时保留强大的机械见解，可以从平均场微观动力学分析，将基准上的两个经典的表面反应化学，直接和H2-协助分解NO和从N2和H2合成或分解氨。该奖项反映了NSF的法定使命，并被认为值得支持通过使用基金会的知识价值和更广泛的影响审查标准进行评估。

Jeffrey Greeley of Purdue University is supported by an award from the Chemical Catalysis program in the Division of Chemistry to study heterogeneous catalysts with new theoretical methods. Heterogeneous catalysts accelerate the conversion of chemical species to valuable products, and they underpin a host of technologically important chemical processes, ranging from production of plastics to generation of electricity in fuel cells. These catalysts are often composed of metal nanoparticles, the surfaces of which break and form chemical bonds in molecules to produce valuable products. Fundamental models of how these molecular transformations occur have been developed for many chemical reactions and have greatly enhanced both the understanding of these transformations and the design of new catalytic materials. However, these models often make significant approximations in their descriptions of the relevant molecular processes, including the assumption that reacting molecules and products are randomly distributed across the catalyst surfaces and do not interact with one another. The development of improved theoretical descriptions that correct these approximations and explicitly describe how the reactions change when molecules interact strongly with one another, is, in turn, the central focus of this project. The improved models will lead to more accurate descriptions of heterogeneous catalytic processes and may ultimately facilitate the design of improved catalysts. For broader impacts, the new capability and software will be made available to the catalysis community. Outreach and education efforts will focus on high school students at a very early stage in their academic path, to encourage the pursuit of STEM studies. PI will make a focused effort to engage students from diverse and under-represented groups. This activity will be a continuation of a successful effort by the PI, whereby the students are paired with the PI and graduate students to pursue tailored research projects.Mean field theories of surface kinetics permit crucial information about heterogeneous catalytic processes, including the overall reaction rates, effective activation barriers, and reaction orders, to be predicted from a combined knowledge of the elementary reaction steps occurring on a catalyst surface and the rate constants of these elementary steps. In spite of the power of these theories, however, the mean field approximation begins to break down under conditions of strong interactions between surface adsorbates, and there is a need to develop surface kinetic modeling techniques that directly incorporate non-mean field effects while, at the same time, preserving the powerful physical and mechanistic insights that emerge naturally from deterministic mean field descriptions. In this work, analytical or semi-analytical corrections to mean field expressions for equilibrium constants and rate constants of elementary reactions will be developed on square planar and hexagonal catalyst surfaces. These expressions, which will be based on the Bethe-Peierls approximation to the Cluster Variation Method, will be used to identify mathematical and conceptual principles that describe when non-mean field effects will significantly impact surface catalysis. The resulting formalisms, which will deterministically treat non-mean field effects while preserving the powerful mechanistic insights that can be obtained from mean field microkinetic analyses, will be benchmarked on two classic surface reaction chemistries, the direct and H2-assisted decomposition of NO and the synthesis or decomposition of ammonia from N2 and H2.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.