EAGER: Towards Multiscale Modeling, Optimization, and Uncertainty in Materials Design for CO2 Capture

EAGER:二氧化碳捕获材料设计中的多尺度建模、优化和不确定性

基本信息

  • 批准号:
    1263165
  • 负责人:
  • 金额:
    $ 10万
  • 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
  • 起止时间:
    2013-04-01 至 2015-03-31
  • 项目状态:
    已结题

项目摘要

Intellectual Merit: The discovery and design of novel materials (e.g., zeolites and metal organic frameworks, MOFs) for high impact energy application domains represents the major scientific challenge for the next decade. The primary objective of the research proposed here is to develop novel theoretical, algorithmic and computational techniques for the discovery and analysis of novel materials for carbon dioxide capture and storage. We propose to investigate: (i) novel optimization framework in simultaneous materials design and process design through modeling at multiple scales; (ii) approaches for the discovery of new materials via multiscale modeling, simulation and optimization; and (iii) optimization approaches for uncertainty characterization and quantification in materials design.We expect that new and transformative theoretical, algorithmic, and computational results, and novel methodologies will be developed and applied to the discovery and design of novel materials (e.g., zeolites, metal organic frameworks) for CO2 capture.Broader Impacts Resulting from the Proposed Activity: The proposed approach has the potential to significantly advance and transform the approaches for discovery of new materials for CO2 capture that will address desired properties and process performance in tandem. The development of novel materials has the potential to contribute significantly to the CO2 capture and sequestration challenge which affects directly the US energy security and economy.Broader Impacts:Integration of Research and Education: The proposed effort will integrate participation of undergraduate and graduate students and will include underrepresented minorities and visiting students. At the undergraduate level, the PI has used and will introduce CO2 capture and sequestration approaches as part of a senior design project, while at the graduate level, the PI intends to incorporate the findings in a graduate course on Optimization in Process Systems Engineering. The students will receive training in process design, simulation, synthesis, optimization, energy, zeolites, metal organic frameworks, life cycle analysis, uncertainty analysis, and scientific computation.Broaden Representation of Underrepresented Groups: The proposed research will broaden the participation of under-represented groups since it will aim at attracting female and minority students at the graduate level and the undergraduate junior independent and senior theses level. The PI has a proven record of promoting diversity in chemical engineering. His trainees have had diverse socioeconomic, racial and ethnical backgrounds, and have included (18) female students and postdoctoral fellows many of whom are now distinguished researchers and Professors in the US or abroad. Currently, the PI supervises 1 Hispanic doctoral student, 2 female doctoral students and 1 female high school student. The PI will continue recruiting efforts of under-represented groups for this project via meeting during his seminar visits and conferences, and attracting juniors and seniors for independent research work.Dissemination: The results of the proposed work will be broadly disseminated to researchers in academia and industry through presentations at domestic and international meetings, scholarly refereed journal publications and through a dedicated web site which will describe the approaches, implementations and results.Impact on Society: The proposed research has potential to accelerate the discovery of transformative new materials for carbon capture which will lead into meeting sustainability targets of the United States.
智力价值:发现和设计用于高影响能源应用领域的新型材料(例如沸石和金属有机骨架,MOF)是下一个十年的重大科学挑战。这里提出的研究的主要目标是开发新的理论、算法和计算技术,以发现和分析二氧化碳捕获和储存的新材料。我们建议研究:(I)通过多尺度建模来同时进行材料设计和工艺设计的新的优化框架;(Ii)通过多尺度建模、模拟和优化来发现新材料的方法;以及(Iii)材料设计中不确定性表征和量化的优化方法。我们希望新的和变革性的理论、算法和计算结果以及新的方法将被开发和应用于发现和设计用于二氧化碳捕获的新材料(例如,沸石、金属有机骨架)。拟议活动产生的广泛影响:建议的方法有可能显著推进和改变发现用于二氧化碳捕获的新材料的方法,这些方法将同时满足所需的性能和工艺性能。新材料的开发有可能对直接影响美国能源安全和经济的二氧化碳捕获和封存挑战做出重大贡献。广泛影响:研究和教育的整合:拟议的努力将整合本科生和研究生的参与,并将包括未被充分代表的少数族裔和来访学生。在本科阶段,PI已经使用并将引入二氧化碳捕获和封存方法,作为高级设计项目的一部分;而在研究生阶段,PI打算将研究结果纳入过程系统工程优化的研究生课程。学生将接受过程设计、模拟、综合、优化、能源、沸石、金属有机框架、生命周期分析、不确定性分析和科学计算方面的培训。代表性不足的群体的代表性:拟议的研究将扩大代表性不足的群体的参与,因为它的目标是吸引研究生水平的女性和少数族裔学生以及本科初级独立论文和高级论文水平的学生。PI在促进化学工程领域的多样性方面有着被证明的记录。他的学员具有不同的社会经济、种族和民族背景,其中包括18名女学生和博士后研究员,其中许多人现在是美国或国外的杰出研究人员和教授。目前,PI指导1名西班牙裔博士生、2名女性博士生和1名女性高中生。PI将继续为该项目招募代表不足的群体的努力,通过在他的研讨会访问和会议期间举行会议,并吸引初级和高级人员进行独立研究工作。授课:拟议工作的结果将通过在国内和国际会议上的演讲、学术评论期刊出版物和将描述方法、实施和结果的专用网站向学术界和工业界的研究人员广泛传播。对社会的影响:拟议的研究有可能加速发现变革性的碳捕获新材料,这将导致实现美国的可持续发展目标。

项目成果

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Christodoulos Floudas其他文献

Christodoulos Floudas的其他文献

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{{ truncateString('Christodoulos Floudas', 18)}}的其他基金

Novel Optimization Methods for Design, Synthesis, Supply Chain, and Uncertainty of Hybrid Biomass, Coal, and Natural Gas to Liquids, CBGTL, Processes
用于混合生物质、煤炭和天然气液化、CBGTL、工艺的设计、合成、供应链和不确定性的新颖优化方法
  • 批准号:
    1158849
  • 财政年份:
    2012
  • 资助金额:
    $ 10万
  • 项目类别:
    Standard Grant
Integrated Framework for Operational Planning and Scheduling Under Uncertainty
不确定性下的运营规划和调度综合框架
  • 批准号:
    0856021
  • 财政年份:
    2009
  • 资助金额:
    $ 10万
  • 项目类别:
    Standard Grant
CDI-Type II: MS-Omics Hub for Cyber-enabled Acceleration of Mass Spectrometry-based Metabolomics and Proteomics
CDI-Type II:MS-Omics 中心,用于网络加速基于质谱的代谢组学和蛋白质组学
  • 批准号:
    0941143
  • 财政年份:
    2009
  • 资助金额:
    $ 10万
  • 项目类别:
    Standard Grant
Novel Methods and Computational Studies for Global Optimization
全局优化的新方法和计算研究
  • 批准号:
    0827907
  • 财政年份:
    2008
  • 资助金额:
    $ 10万
  • 项目类别:
    Standard Grant
GOALI: Short-term Scheduling Under Uncertainty: A Robust Optimization Framework
GOALI:不确定性下的短期调度:鲁棒优化框架
  • 批准号:
    0355336
  • 财政年份:
    2004
  • 资助金额:
    $ 10万
  • 项目类别:
    Standard Grant
SGER:Performance Analysis of the BlueGene Class of Machines via the ASTRO-FOLD Protein Structure Prediction Framework
SGER:通过 ASTRO-FOLD 蛋白质结构预测框架对 BlueGene 类机器进行性能分析
  • 批准号:
    0401635
  • 财政年份:
    2004
  • 资助金额:
    $ 10万
  • 项目类别:
    Standard Grant
FOCAPD 2004 Conference: Discovery through Product and Process Design
FOCAPD 2004 会议:通过产品和工艺设计进行发现
  • 批准号:
    0355399
  • 财政年份:
    2004
  • 资助金额:
    $ 10万
  • 项目类别:
    Standard Grant
ITR: Collaborative Research: (ASE+NHS+EVS)-(sim+dmc+int): In Silico De Novo Protein Design: A Dynamically Data Driven, (DDDAS), Computational and Experimental Framework
ITR:协作研究:(ASE NHS EVS)-(sim dmc int):计算机从头蛋白质设计:动态数据驱动、(DDDAS)、计算和实验框架
  • 批准号:
    0426691
  • 财政年份:
    2004
  • 资助金额:
    $ 10万
  • 项目类别:
    Continuing Grant
Improved Convex Underestimators and Hybrid Methods for Deterministic Global Optimization
用于确定性全局优化的改进凸低估器和混合方法
  • 批准号:
    0330541
  • 财政年份:
    2003
  • 资助金额:
    $ 10万
  • 项目类别:
    Standard Grant
QSB: Computational and Experimental Studies of Pathways in Yeast
QSB:酵母途径的计算和实验研究
  • 批准号:
    0222471
  • 财政年份:
    2002
  • 资助金额:
    $ 10万
  • 项目类别:
    Continuing Grant

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