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

表面化学的非平均场处理：将吸附质-吸附质相互作用纳入确定性动力学理论

• 批准号: 2102614
• 负责人: Jeffrey Greeley
• 金额: $ 29.98万
• 依托单位: Purdue University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-01-01 至 2024-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2102614&HistoricalAwards=false
• 关键词: Non; Mean; Field; Treatments; Surface

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.

普渡大学的杰弗里·格里利获得了化学系化学催化项目的支持，用新的理论方法研究多相催化剂。多相催化剂加速了化学物种向有价值的产品的转化，它们支撑着一系列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，纳米金属颗粒的表面断裂并在分子中形成化学键，从而产生有价值的产品。这些分子转化如何发生的基本模型已经为许多化学反应而发展，并极大地提高了对这些转化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有很大的近似性，包括假设反应分子和产物随机分布在催化剂表面，彼此不相互作用。改进的理论描述的发展，修正了这些近似，并明确描述了当分子相互作用强烈时反应如何变化，这反过来又是这个项目的中心焦点。改进后的模型将更准确地描述多相催化过程，并最终可能有助于改进催化剂的设计。对于更广泛的影响，新的能力和软件将提供给催化社区。外展和教育工作将侧重于高中生在学业道路上的早期阶段，以鼓励他们追求STEM学习。PI将集中努力吸引来自不同和代表性不足群体的学生。这项活动将是PI成功努力的延续，即学生与PI和研究生配对进行量身定制的研究项目。表面动力学的场理论允许根据催化剂表面发生的基本反应步骤和这些基本步骤的速度常数的组合知识来预测关于多相催化过程的关键信息，包括总反应速率、有效活化势垒和反应级数。然而，尽管这些理论的力量很大，平均场近似在表面吸附之间强相互作用的条件下开始崩溃，因此需要开发表面动力学建模技术，直接结合非平均场效应，同时保留从确定性平均场描述中自然产生的强大的物理和力学见解。在这项工作中，将在正方形、平面型和六边形催化剂表面上对基元反应的平衡常数和速率常数的平均场表达式进行解析或半解析修正。这些表达式将基于Bethe-Peierls近似的团簇变分方法，将用于确定描述非平均场效应何时将显著影响表面催化的数学和概念原理。由此产生的形式主义将决定性地处理非平均场效应，同时保留可以从平均场微观动力学分析中获得的强大的机制洞察力，将以两个经典的表面反应化学反应为基准，即直接和氢气辅助分解NO，以及从氮气和氢气合成或分解氨。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。