| 项目编号: | 1534260
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| 项目名称: | DMREF: Collaborative Research: Design and Discovery of Multimetallic Heterogeneous Catalysts for a Future Biorefining Industry |
| 作者: | Andreas Heyden
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| 承担单位: | University of South Carolina at Columbia
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| 批准年: | 2014
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| 开始日期: | 2015-09-15
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| 结束日期: | 2019-08-31
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| 资助金额: | USD840000
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| 资助来源: | US-NSF
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| 项目类别: | Standard Grant
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| 国家: | US
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| 语种: | 英语
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| 特色学科分类: | Engineering - Chemical, Bioengineering, Environmental, and Transport Systems
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| 英文关键词: | uncertainty
; statistical analysis
; specific catalyst
; catalyst design
; catalytic material
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| 英文摘要: | #1534260 / #1534269
Heyden, Andreas /
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. |
| 资源类型: | 项目
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| 标识符: | http://119.78.100.158/handle/2HF3EXSE/93205
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| Appears in Collections: | 影响、适应和脆弱性
气候减缓与适应
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| Recommended Citation: | |
Andreas Heyden. DMREF: Collaborative Research: Design and Discovery of Multimetallic Heterogeneous Catalysts for a Future Biorefining Industry. 2014-01-01.
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