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DMREF: Collaborative Research: Design and Discovery of Multimetallic Hetergeneous Catalysts for a Future Biorefining Industry

DMREF: Collaborative Research: Design and Discovery of Multimetallic Hetergeneous Catalysts for a Future Biorefining Industry
DMREF:合作研究:未来生物精炼行业多金属多相催化剂的设计和发现
批准号:
1534269
负责人:
Jesse Bond
金额:
$40.0万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2015
资助国家:
美国
项目状态:
已结题
起止时间:
2015-09-15 至 2020-08-31

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中文摘要
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英文摘要
#1534260 / #1534269Heyden, Andreas / Bond, Jesse Q.The proposal utilizes statistical analysis to estimate uncertainties in both experimental data and theoretical calculations relating to catalytic hydrodeoxygenation of succinic acid (SUCC HDO) - an important reaction in the refining of biomass-derived chemicals to commercially valuable products. The experimental and computational methods employed - combined with statistical error analysis - provide a more accurate and powerful approach for identifying improved catalytic materials than possible by either experiments or theory alone. The approach is applicable to a broad range of catalytic applications, and could provide a blueprint for a new approach to the discovery and design of catalytic materials. The results of the study will be made available to the catalysis community via a website and software tool.Specifically, the project involves preparation of well-defined and well-dispersed bimetallic clusters of tin (Sn) adsorbed on ruthenium (Ru), platinum (Pt) or rhodium (Rh) deposited on amorphous silica or carbon supports. The catalysts will be characterized in detail with respect to structure, composition, and surface acidity, and then evaluated in the SUCC HDO reaction. A multiscale strategy will be used for the computations based on DFT methods and techniques developed in the investigators' laboratory aimed at reducing uncertainties in the estimation of free energies. Uncertainties in both the experimental and computational analyses will be subjected to Bayesian statistical analysis. Refinements to both the experimental and computational methods will be made to minimize the uncertainties and obtain meaningful comparisons between theory and experiment. The methodology employed in the study can potentially guide materials selection and catalyst design for many applications beyond the specific catalysts and reaction demonstrated here. Rigorous standards are set for both the experimental and computational work, that when combined with statistical analysis, provide confidence heretofore lacking in the certainty with which new catalytic materials can be predicted. The selected reaction is in biomass processing and not only demonstrates application of the methods to complicated systems, but suggests potential use of the methods in both aqueous and gas-phase reactions important to renewable resources and energy sustainability.
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Collaborative Research: Understanding and manipulating the solvent microenvironment for selective, catalytic amination of renewable oxygenates
  • 批准号:
    1804843
  • 项目类别:
    Continuing Grant
  • 资助金额:
    $22.5万
  • 财政年份:
    2018
  • 负责人:
    Jesse Bond
  • 依托单位:
Collaborative Research: SusChEM: Phase-specific catalysis combined with reactive distillation for the selective production of butadiene from y-valerolactone
  • 批准号:
    1605114
  • 项目类别:
    Standard Grant
  • 资助金额:
    $17.5万
  • 财政年份:
    2016
  • 负责人:
    Jesse Bond
  • 依托单位:
CAREER: SusChEM: Development of Governing Mechanistic and Kinetic Models for the Selective Oxidative Cleavage of Levulinic Acid Over Supported Vanadium Oxides
  • 批准号:
    1454346
  • 项目类别:
    Standard Grant
  • 资助金额:
    $50.0万
  • 财政年份:
    2015
  • 负责人:
    Jesse Bond
  • 依托单位:
Collaborative Research: Rational design of bifunctional catalysts for the conversion of Ievulinic acid to gamma-valerolactone
  • 批准号:
    1159739
  • 项目类别:
    Continuing Grant
  • 资助金额:
    $25.0万
  • 财政年份:
    2012
  • 负责人:
    Jesse Bond
  • 依托单位:
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