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Critical Factors Controlling Gas Separations by Polymeric Membranes

Critical Factors Controlling Gas Separations by Polymeric Membranes
控制聚合物膜气体分离的关键因素
批准号:
1829655
负责人:
Sanat Kumar
金额:
$24.0万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2019
资助国家:
美国
项目状态:
已结题
起止时间:
2019-09-01 至 2021-08-31

项目摘要

项目成果

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中文摘要
翻译
该奖项支持理论、计算和数据密集型研究以及教育,旨在使用计算和数据密集型方法来帮助开发用于分离气体的聚合物膜。PI将开发计算工具,模拟由长链分子组成的聚合物制成的材料。这些工具将与其他理论、数据中心和计算方法结合使用,以推进对聚合物材料的理解,并为当前和新兴技术应用开发聚合物膜的稳健设计方法。这项工作的一个重点是使用聚合物膜来清除气体流中不必要的污染物,例如,在长距离输送压裂气体时,从气体流中去除腐蚀性的硫基化合物,以减轻管道腐蚀。这些研究活动与广泛的教育活动相结合。在最近成功招募高中生和本科生进行暑期研究的推动下,PI将继续努力在本科和研究生阶段招募女性和少数民族学生。重点将是为高中生提供在这个项目中进行暑期研究的机会。受过去成功的鼓舞,这些高中生将被积极鼓励继续接受本科教育,从而可能在STEM领域从事职业。该奖项支持理论、计算和数据密集型研究,以及教育,以促进对聚合物膜的理解。聚合物膜,这是有效的气体分离应用,具有重量轻,易于加工的附加优点。高分子膜材料已经取得了许多进展,但大多数都是经验设计的。为了制定设计策略,需要定量了解控制这些材料的分子运输、溶解度以及渗透性和选择性的微观机制。PI将使用计算机模拟和数据密集型方法来针对本主题中一些最重要的未解决问题。该奖项支持主要使用分子动力学模拟和机器学习方法来解决三个重要问题的研究:(i)数据密集型方法能否应用于设计感兴趣的膜材料?更具体地说,是否可以使用数据挖掘和机器学习来预测渗透率和选择性,从而预测膜气体分离性能的上限相关性?(ii)已经发现,在橡胶聚合物的情况下,溶质尺寸对渗透率的依赖性与在其玻璃类似物中发现的“相反”。这是一个普遍的趋势吗?如果是这样,那么如何从以筛分为主的玻璃状趋势转变为可能由溶解度效应驱动的橡胶状行为呢?(iii)在气体分离的情况下,当纳米粒子与聚合物物理混合时,它们的作用是什么?如果纳米颗粒是选择性的,这种现象会受到什么影响?在这种情况下,纳米粒子在聚合物玻璃老化中的作用是什么?该奖项反映了美国国家科学基金会的法定使命,并通过使用基金会的知识价值和更广泛的影响审查标准进行评估,被认为值得支持。
英文摘要
NONTECHNICAL SUMMARYThis award supports theoretical, computational, and data-intensive research, and education with an aim to use computation and data-intensive approaches to help develop membranes made of polymer to be used to separate gases. The PI will develop computational tools modelling materials made of polymers which are composed of long-chain molecules. These tools will be used in conjunction with other theoretical, data-centric, and computational methods to advance understanding of polymeric materials and to develop robust design methodologies for polymer membranes for current and emerging technological applications. A highlight of the work focuses on using polymer membranes to clean gas streams of unnecessary pollutants, for example removing corrosive sulfur-based compounds from gas streams to mitigate pipeline corrosion when fracked gases are pumped over long distances. These research activities are coupled to extensive educational activities. Driven by the PI's recent success in recruiting high school and undergraduate students for summer research, the PI will continue his efforts to recruit women and minority students at both the undergraduate and graduate levels. A focus will be to provide high school students with opportunities to perform summer research in this project. Encouraged by past successes, these high-school students will be actively encouraged to pursue undergraduate education leading to possible careers in STEM.TECHNICAL SUMMARYThis award supports theoretical, computational, and data-intensive research, and education to advance understanding of polymeric membranes. Polymeric membranes, which are efficient for gas separation applications, have the added advantages of being lightweight and easily processable. There have been many advances in polymer membrane materials, but most of these have been empirically designed. To develop design strategies, there is need for a quantitative understanding of the microscopic mechanisms controlling molecular transport, solubility, and hence permeability and selectivity of these materials. The PI will use computer simulations and data-intensive approaches to target some of the most important unresolved questions in this topic.This award supports research which will primarily use molecular dynamics simulations and machine learning methodologies to address three important questions: (i) Can data-intensive methods be applied to design membrane materials of interest? More specifically, can data mining and machine learning be used to predict permeability and selectivity, and thus the upper bound correlation for membrane gas separation performance? (ii) It has been found that the solute size dependence of permeability in the case of rubbery polymers is "opposite" to that found in their glassy analogs. Is this a general trend, and if so, how does the transition from glassy trends, dominated by sieving, to rubbery behavior, which is probably driven by solubility effects, occur? and (iii) What is the role of nanoparticles when they are physically mixed with polymers in the context of gas separation? How is this phenomenon affected if the nanoparticles are made selective? What is the role of nanoparticles in aging of polymer glasses in this context?This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
期刊论文(2)
专著(0)
科研奖励(0)
会议论文
DOI: 10.1126/sciadv.aaz4301
发表时间: 2020-05-01
期刊: SCIENCE ADVANCES
影响因子: 13.6
作者: [Barnett, J. Wesley, Bilchak, Connor R., Kumar, Sanat K.]
通讯作者: Kumar, Sanat K.
Collaborative Research: Designing Polymer Grafted-Nanoparticle Melts through a Hierarchical Computational Approach
  • 批准号:
    2226898
  • 项目类别:
    Standard Grant
  • 资助金额:
    $27.1万
  • 财政年份:
    2023
  • 负责人:
    Sanat Kumar
  • 依托单位:
CAS-MNP: Origins of Secondary Nanoplastics and Mitigating Their Creation
  • 批准号:
    2301348
  • 项目类别:
    Standard Grant
  • 资助金额:
    $45.9万
  • 财政年份:
    2023
  • 负责人:
    Sanat Kumar
  • 依托单位:
Data-Enabled Theoretical Understanding of the Structure and Properties of Solvent-cast Polymer Nanocomposites
  • 批准号:
    2126660
  • 项目类别:
    Standard Grant
  • 资助金额:
    $39.0万
  • 财政年份:
    2022
  • 负责人:
    Sanat Kumar
  • 依托单位:
2020 Polymer Physics GRC/GRS
  • 批准号:
    2021588
  • 项目类别:
    Standard Grant
  • 资助金额:
    $0.8万
  • 财政年份:
    2020
  • 负责人:
    Sanat Kumar
  • 依托单位:
国内基金
海外基金
生长素响应因子(Auxin Response Factors)在拟南芥雄配子发育中的功能研究
  • 批准号:
    31970520
  • 项目类别:
    面上项目
  • 资助金额:
    58.0万元
  • 批准年份:
    2019
  • 负责人:
    姚小贞
  • 依托单位: