CAS: Developing Methods for Reaction Modeling to Tune Catalysts for Substrate Variability

有了这个奖项，NSF化学部的化学催化计划正在支持密歇根州立大学化学系的Aaron Odom教授的研究，以开发一个预测催化剂效率的模型。奥多姆教授和他的研究小组正在研究的催化剂是钛和钒的络合物，这是地球上丰富的早期过渡金属，提供独特的化学产品。这种更具可持续性的反应模型将最大限度地减少工业中常用的催化系统优化所需的时间和精力。虽然已经对用于不同类型应用的后过渡金属催化剂进行了类似的研究，但该模型是针对前过渡金属催化剂设计的。这些研究正在推进Odom教授先前开发的初始模型，该模型能够与大量反应变量和不同类型的催化剂-底物相互作用一起发挥作用。该计划还发现了新的方法，使模型适用于附着在固体载体上的催化剂。通过参加这些活动，一批不同的研究生和本科生正在接受培训，一个化学演示小组正在组织起来，让当地K-12学生参与STEM学科。配体参数化方法最近已被确立为后过渡金属体系催化剂优化的宝贵工具。虽然早期过渡金属催化剂用于将石化产品转化为增值商品的各种工业过程中，但催化性能预测方法在该领域的发展较慢。Odom实验室开发了第一个模型，将控制用于加氢胺化的钛催化剂反应性的因素系统化。这些研究人员现在正在推进他们的工作模型，以便能够应对新的挑战，例如非对称配体系统和多组分反应。 此外，该方法被设计为适应二氧化硅负载的钛催化剂和钒烯烃异构化催化剂，需要考虑新型的催化剂-基质相互作用。这些研究为无机/有机金属化学和化学实验领域的研究生和本科生提供培训，以及机器学习在分子设计中的人工智能应用。该奖项反映了NSF的法定使命，并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，被认为值得支持。

With this award, the Chemical Catalysis Program of the NSF Division of Chemistry is supporting the research of Professor Aaron Odom of the Department of Chemistry at Michigan State University to develop a model to predict catalyst efficiency. The catalysts that Professor Odom and his research group are studying are complexes of titanium and vanadium, which are early transition metals that are earth abundant and offer unique chemical products. This more sustainable reactivity model will minimize the time and effort required for the optimization of catalytic systems that are commonly used in industry. While similar studies have been performed for late transition metal catalysts that are used for different types of applications, this model has been designed for early transition metal catalysts. These studies are advancing an initial model previously developed by Professor Odom to be able to function with a larger number of reaction variables and different types of catalyst-substrate interactions. The program is also discovering new ways to adapt the model to catalysts that are attached to solid supports. A diverse group of graduate and undergraduate students are being trained through their participation in these activities and a chemical demonstration team is being organized to engage local K-12 students in STEM disciplines.Ligand parametrization methods have recently been established as valuable tools for catalyst optimization with late transition metal systems. Although early transition metal catalysts are used in a variety of industrial processes for the conversion of petrochemical products to value-added commodities, catalytic performance predictive methods have been slower to evolve in this area. The Odom laboratory has developed the first model to systematize the factors that control the reactivity of titanium-catalysts used for hydroamination. These researchers are now advancing their working model to be able to handle new challenges such as non-symmetrical ligand systems and multicomponent reactions. In addition, the method is being designed to accommodate silica-supported titanium catalysts and vanadium olefin isomerization catalysts that require consideration of new types of catalyst-substrate interactions. These studies are providing training for graduate and undergraduate students in the field of inorganic/organometallic chemistry and chemical experimentation as well as in machine learning with applications to artificial intelligence in molecular design.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.