DMREF: Simulation-Driven Design of Highly Efficient MOF/Nanoparticle Hybrid Catalyst Materials

****技术摘要***本项目旨在利用合成纳米多孔材料的最新进展，通过构建块的方法来构思、合成、表征和测试新的非均相催化剂，这些催化剂在苛刻的化学转化中表现出类似酶的控制。催化活性金属纳米颗粒将被封装在金属有机框架（MOF）晶体中。mof是一种由金属节点和有机连接体以积木方式合成的纳米多孔材料。将金属纳米颗粒包裹在mof中可以防止其团聚，并允许控制反应物进入其表面。分子水平的建模将指导选择和合成适当的金属表面和MOF通道的一类重要的反应。该项目的目标是：1)开发具有从原子水平到颗粒水平的结构控制的合成多相催化剂材料的新方法；2)展示新水平的合成控制与预测性分子水平建模相结合，如何大大缩短新催化材料的开发时间。通过这种模型和实验的结合，该项目旨在对MOF层在定义和调节纳米颗粒的催化行为中所起的作用有一个基本的了解。结果应该是一类既具有高活性又具有选择性的催化剂。该研究将为基于结构的催化剂设计的关键前沿的本科生、研究生和博士后提供一个优秀的培训平台。基于网络的教育和外联活动将覆盖更广泛的受众。****非技术摘要****催化作用是使化学反应更快、更有选择性地向期望产物方向发展的科学和工程。催化是我国制造业基础的一项基础技术，纳米技术、计算能力和我们对催化反应的理论理解的最新进展为改进催化创造了巨大的机会，产生了经济和环境效益。该项目旨在为一类重要的化学反应——选择性氧化——设计新的催化剂。催化活性金属纳米颗粒将被封装在金属有机框架（MOF）晶体中。将金属纳米颗粒包裹在mof中可以防止其团聚，并允许控制反应物进入其表面。然而，有大量的金属纳米颗粒和MOF类型可以选择。因此，分子水平的建模将指导适当的金属表面和MOF通道的选择和合成，从而使所得材料具有所需的性能。该项目的目标是：1)开发具有从原子水平到颗粒水平的结构控制的合成多相催化剂材料的新方法；2)展示新水平的合成控制与预测性分子水平建模相结合，如何大大缩短新催化材料的开发时间。

****Technical Abstract***This project seeks to exploit recent advances in synthesizing nanoporous materials via a building-block approach to conceive, synthesize, characterize, and test new heterogeneous catalysts that exhibit enzyme-like control in demanding chemical transformations. Catalytically active metal nanoparticles will be encapsulated within metal-organic framework (MOF) crystals. MOFs are nanoporous materials synthesized in a building-block approach from metal nodes and organic linkers. Enshrouding metal nanoparticles within MOFs prevents their agglomeration and allows control over reactant access to their surfaces. Molecular-level modeling will guide the selection and synthesis of appropriate metal surfaces and MOF channels for an important class of reactions. The objectives of this project are 1) to develop new ways of synthesizing heterogeneous catalyst materials with structural control ranging from the atomic level to the particle level and 2) to demonstrate how new levels of synthetic control, combined with predictive molecular-level modeling, can drastically decrease the development time of new catalytic materials. Through this combination of modeling and experiment, the project aims to develop a fundamental understanding of the role that the MOF layer plays in defining and modulating the catalytic behavior of nanoparticles. The result should be a class of catalysts that are both highly active and selective. The proposed research will serve as an excellent training platform for undergraduates, graduate students and a postdoctoral fellow in the critical frontier of structure-based catalyst design. Web-based education and outreach activities will reach a wider audience.****Non-Technical Abstract****Catalysis is the science and engineering of making chemical reactions go faster and more selectively toward the desired products. Catalysis is a fundamental technology for our country's manufacturing base, and recent advances in nanotechnology, computational power, and our theoretical understanding of catalytic reactions create tremendous opportunities to improve catalysis, producing both economic and environmental benefits. This project aims to design new catalysts for an important class of chemical reactions known as selective oxidation. Catalytically active metal nanoparticles will be encapsulated within metal-organic framework (MOF) crystals. Enshrouding metal nanoparticles within MOFs prevents their agglomeration and allows control over reactant access to their surfaces. However, there are an enormous number of metal nanoparticle and MOF types that could be chosen. Molecular-level modeling will, therefore, guide the selection and synthesis of appropriate metal surfaces and MOF channels so that the resulting materials have the desired properties. The objectives of this project are 1) to develop new ways of synthesizing heterogeneous catalyst materials with structural control ranging from the atomic level to the particle level and 2) to demonstrate how new levels of synthetic control, combined with predictive molecular-level modeling, can drastically decrease the development time of new catalytic materials.