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

DMREF: Simulation-Driven Design of Highly Efficient MOF/Nanoparticle Hybrid Catalyst Materials
DMREF:高效 MOF/纳米颗粒杂化催化剂材料的仿真驱动设计
批准号:
1334928
负责人:
Randall Snurr
金额:
$120.0万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2013
资助国家:
美国
项目状态:
已结题
起止时间:
2013-09-01 至 2017-08-31

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中文摘要
翻译
*技术摘要*本项目旨在利用构建块方法合成纳米多孔材料的最新进展,以构思、合成、表征和测试新的多相催化剂,这些催化剂在要求苛刻的化学转化中表现出类似酶的控制。具有催化活性的金属纳米颗粒将被包裹在金属有机骨架(MOF)晶体中。MOF是一种以金属节点和有机连接物为原料,采用积木方法合成的纳米多孔材料。包裹在MOF中的金属纳米颗粒防止了它们的团聚,并允许控制反应物进入其表面。分子水平的模拟将指导为一类重要的反应选择和合成合适的金属表面和MOF通道。该项目的目标是1)开发合成具有从原子水平到颗粒水平的结构控制的多相催化剂材料的新方法,以及2)展示新的合成控制水平如何与预测的分子水平建模相结合,可以显著缩短新催化材料的开发时间。通过模拟和实验的结合,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。其结果应该是一类既具有高活性又具有选择性的催化剂。拟议的研究将为本科生、研究生和博士后在基于结构的催化剂设计的关键前沿领域提供一个极好的培训平台。基于网络的教育和推广活动将接触到更广泛的受众。*非技术摘要*催化是使化学反应更快、更有选择性地朝着所需产品进行的科学和工程学。催化是我国制造业基础的基础技术,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提高催化性能创造了巨大的机会,产生了经济效益和环境效益。该项目旨在为一类重要的化学反应设计新的催化剂,这种化学反应被称为选择性氧化。具有催化活性的金属纳米颗粒将被包裹在金属有机骨架(MOF)晶体中。包裹在MOF中的金属纳米颗粒防止了它们的团聚,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类型可供选择。因此,分子水平的模拟将指导选择和合成合适的金属表面和MOF通道,从而使得到的材料具有所需的性能。该项目的目标是1)开发合成具有从原子水平到颗粒水平的结构控制的多相催化剂材料的新方法,以及2)展示新的合成控制水平如何与预测的分子水平建模相结合,可以显著缩短新催化材料的开发时间。
英文摘要
****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.
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Collaborative Research: DMREF: GOALI: Discovering Materials for CO2 Capture in the Presence of Water via Integrated Experiment, Modeling, and Theory
  • 批准号:
    2119433
  • 项目类别:
    Standard Grant
  • 资助金额:
    $138.23万
  • 财政年份:
    2021
  • 负责人:
    Randall Snurr
  • 依托单位:
Participant Support for Foundations of Molecular Modeling and Simulation: Molecular Modeling and the Materials Genome (FOMMS 2015); Welches, Oregon, on July 12-15, 2015
  • 批准号:
    1513429
  • 项目类别:
    Standard Grant
  • 资助金额:
    $2.2万
  • 财政年份:
    2015
  • 负责人:
    Randall Snurr
  • 依托单位:
SusChem: High-throughput Computational Discovery of New Nanoporous Materials for Energy Storage
  • 批准号:
    1308799
  • 项目类别:
    Standard Grant
  • 资助金额:
    $27.29万
  • 财政年份:
    2013
  • 负责人:
    Randall Snurr
  • 依托单位:
NIRT: Design of Nanoporous Materials for Enantioselective Single-Site Catalysis and Separations
  • 批准号:
    0507013
  • 项目类别:
    Standard Grant
  • 资助金额:
    $100.0万
  • 财政年份:
    2005
  • 负责人:
    Randall Snurr
  • 依托单位:
国内基金
海外基金
Simulation and certification of the ground state of many-body systems on quantum simulators
  • 批准号:
    --
  • 项目类别:
    --
  • 资助金额:
    40万元
  • 批准年份:
    2020
  • 负责人:
    Abolfazl Bayat
  • 依托单位: