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.
智力优势:发现和设计新材料(例如,沸石和金属有机框架,MOFs)的高冲击能量应用领域代表了未来十年的主要科学挑战。本文提出的研究的主要目标是开发新的理论,算法和计算技术,用于发现和分析用于二氧化碳捕获和储存的新材料。我们建议调查:(i)通过多尺度建模实现材料设计和工艺设计同步的新型优化框架;(ii)通过多尺度建模、模拟和优化发现新材料的方法;以及(iii)材料设计中不确定性表征和量化的优化方法。我们期望新的和变革性的理论,算法和计算结果,并且新的方法学将被开发并应用于新材料的发现和设计(例如,所提议的活动产生的更广泛的影响:所提议的方法具有显著推进和转变用于发现用于CO2捕获的新材料的方法的潜力,所述新材料将同时解决所需的性质和工艺性能。新型材料的发展有可能大大有助于CO2捕获和封存的挑战,直接影响到美国的能源安全和economy.Broader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,并将包括代表性不足的少数民族和访问学生。在本科阶段,PI已经使用并将引入CO2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、合成、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等方面的培训。拟议的研究将扩大参与的不足-该方案的目的是吸引研究生一级的女生和少数民族学生以及本科三年级、独立和四年级的学生,水平。PI在促进化学工程多样性方面有着良好的记录。他的学员有不同的社会经济,种族和民族背景,并包括(18)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监督1名西班牙裔博士生,2名女博士生和1名女高中生。PI将继续通过在研讨会访问和会议期间的会面为该项目招募代表性不足的群体,并吸引大三学生和大四学生进行独立研究工作。拟议工作的结果将通过在国内和国际会议上的介绍向学术界和工业界的研究人员广泛传播,学术期刊出版物,并通过一个专门的网站,其中将描述的方法,实施和结果。这项拟议的研究有可能加速发现用于碳捕获的变革性新材料,从而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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