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EAGER: Collaborative Research: Consequences of Co-Adsorbed Chlorine on Surface Dynamics and Selectivity in Ethylene Epoxidation on Silver Catalysts

EAGER：合作研究：共吸附氯对银催化剂上乙烯环氧化反应的表面动力学和选择性的影响

基本信息

批准号：
1942072
负责人：
Chris Paolucci
金额：
$ 9.5万
依托单位：
University of Virginia Main Campus
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2019
资助国家：
美国
起止时间：
2019-12-01 至 2021-11-30
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1942072&HistoricalAwards=false
关键词：
EAGER Collaborative Research Consequences Co

项目摘要

Ethylene epoxide (EO) is a major commodity chemical used in the production of materials, industrial solutions, surfactants and consumer goods. EO is manufactured via a catalytic reaction between ethylene and oxygen gas utilizing highly complex catalysts that have evolved over the years primarily through industrial research involving experimental screening of a large array of catalytic, promoter, and stabilizing materials. While those efforts have led to high-performing catalysts containing five or more promoting materials, there remains significant opportunity to improve the catalyst technology. State-of-the art theory, machine learning, spectroscopic and reaction analysis methods will be combined to better understand the role of chlorine, one of the key promoting elements, and identify opportunities for increasing its effectiveness. Higher-performing EO catalysts would improve process energy efficiency, reduce emissions, and promote U.S. competitiveness in a chemical market sector that accounted for $45B in 2016. Among the many different combinations of promoters reported in commercial EO catalysts, chlorine (Cl) is the most ubiquitous promoter, and its addition to an otherwise unmodified silver (Ag) catalyst leads to the greatest increase in selectivity to EO. Reactant and promoter-induced surface dynamics and reconstruction have long been known to play a critical role in many catalytic reactions. The study combines catalyst synthesis, spectroscopic characterization, reactivity testing, and machine-learning enhanced molecular simulations, to explore the dynamic nature of the Cl-promoted Ag surface under reaction conditions. The bottom-up approach to synthesis and characterization yields itself to several opportunities for reconciling conflicting spectroscopic assignments in the literature, mechanistic proposals for this system, and hypotheses for the mode of action of Cl through the combination of cutting-edge computational and experimental methods. Specifically, the study will utilize efficient computational approaches for modeling dynamic evolution of systems with high configurational complexity. Time-averaged simulated Raman spectra derived from molecular dynamics simulations will be used in conjunction with multi-variate curve resolution of experimental Raman spectra to make molecularly precise assignments for different surface oxygen species and the influence of Cl on their structure. The transient behavior of these systems will also be tied to observations at steady-state operation at conditions relevant for industrial systems. The collaborative nature of the project will provide opportunities for cross-exposure of graduate students from the two research groups to theoretical and experimental methods, thereby teaching skills for effective research collaboration. The methodologies developed in the research and their application will be integrated into graduate courses taught by the co-investigators to demonstrate the importance of embracing complexity of catalytic systems, even within fundamental studies.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.

环氧乙烷（EO）是一种主要的日用化学品，用于生产材料、工业溶液、表面活性剂和消费品。环氧乙烷是通过乙烯和氧气之间的催化反应，利用高度复杂的催化剂生产的，这些催化剂主要是通过工业研究发展起来的，涉及大量催化剂、促进剂和稳定材料的实验筛选。虽然这些努力已经导致含有五种或更多种促进材料的高性能催化剂，但仍然存在改进催化剂技术的重大机会。最先进的理论，机器学习，光谱和反应分析方法将结合起来，以更好地了解氯的作用，这是关键的促进因素之一，并确定提高其有效性的机会。更高性能的EO催化剂将提高工艺能效，减少排放，并提高美国在2016年占450亿美元的化学品市场领域的竞争力。在商业EO催化剂中报道的促进剂的许多不同组合中，氯（Cl）是最普遍存在的促进剂，并且将其添加到另外未改性的银（Ag）催化剂中导致EO选择性的最大增加。反应物和促进剂诱导的表面动力学和重构在许多催化反应中起着关键作用。该研究结合了催化剂合成，光谱表征，反应性测试和机器学习增强的分子模拟，以探索Cl促进的Ag表面在反应条件下的动态性质。自下而上的方法来合成和表征产量本身的几个机会，以调和冲突的光谱分配在文献中，该系统的机制建议，并通过尖端的计算和实验方法相结合的Cl的作用模式的假设。具体而言，这项研究将利用高效的计算方法来模拟具有高配置复杂性的系统的动态演化。从分子动力学模拟得到的时间平均模拟拉曼光谱将与实验拉曼光谱的多变量曲线分辨率结合使用，以使分子精确分配不同的表面氧物种和Cl对它们的结构的影响。这些系统的瞬态行为也将与工业系统相关条件下稳态运行时的观察结果联系在一起。该项目的合作性质将为来自两个研究小组的研究生提供交叉接触理论和实验方法的机会，从而教授有效研究合作的技能。在研究中开发的方法及其应用将被整合到由共同研究者教授的研究生课程中，以证明即使在基础研究中也要拥抱催化系统的复杂性的重要性。该奖项反映了NSF的法定使命，并被认为值得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来支持。