DMREF: Collaborative Research: An integrated multiscale modeling and experimental approach to design fouling-resistant membranes

DMREF：协作研究：设计防污膜的集成多尺度建模和实验方法

• 批准号: 1742175
• 负责人: Ilenia Battiato
• 金额: $ 21.17万
• 依托单位: Stanford University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-01-01 至 2019-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1742175&HistoricalAwards=false
• 关键词: DMREF; Collaborative; Research; integrated; multiscale

1534304(Sarupria) & 1533874(Battiato)This project addresses a grand challenge facing society today--how to make clean water available to a growing population at low cost. Membranes used in water treatment processes are exposed to feed waters containing organic, inorganic, and biological species, which leads to fouling and loss of membrane productivity over time. Since performance loss due to fouling is one of the largest costs associated with membrane processes in water treatment, discovery of new surface treatments that limit fouling would have significant economic and societal impacts. Fouling propensity of a membrane depends greatly on its surface properties such as chemistry and morphology. The goal of this project is to develop the multiscale mathematical framework to predict fouling behavior on the surfaces of membranes with different geometric patterns and chemical coatings. The ability to predict fouling properties of new membrane surfaces in silico will accelerate the discovery of novel membrane designs and decrease the time from laboratory to market. In this project, comprehensive studies involving iterative feedback between computational modeling and experimental measurements will be performed to test two main hypotheses: (1) targeted combinations of geometric and chemical patterns on a membrane surface will significantly reduce membrane fouling, and (2) experimentally-trained multiscale computational models will accelerate the discovery of novel geometric and chemical surface modifications that significantly reduce membrane fouling. This research will (i) produce a mathematical framework and corresponding models to identify the physical mechanisms and geometric features controlling mass and momentum transfer through and over micro- and nanopatterned membranes, (ii) provide a deep understanding of how foulants and energy fluxes are controlled and regulated by complex topologies, and (iii) elucidate how the macroscopic behavior of filtration flow rates and reactive transport processes are coupled with phenomena at the micro- and nano-scale. This work will be transformational because delivering an experimentally-validated computational framework will enable rapid screening of many membrane surface modifications to short-list the most promising ones for further testing, and it will lead to a leapfrog improvement in membrane filtration technologies. This project will provide a multidisciplinary environment for training graduate and undergraduate researchers. New communication platforms such as Zoom video conferencing will be used to deliver virtual science demonstrations and laboratory tours to elementary school.

1534304(萨鲁普里亚)&1533874(巴蒂亚托)这个项目解决了当今社会面临的一个重大挑战--如何以低成本向不断增长的人口提供清洁水。水处理过程中使用的膜暴露在含有有机、无机和生物物种的给水中，随着时间的推移，这会导致污染和膜生产率的损失。由于膜污染造成的性能损失是水处理中与膜工艺相关的最大成本之一，因此发现限制污染的新的表面处理方法将具有重大的经济和社会影响。膜的污染倾向在很大程度上取决于膜的表面性质，如化学和形态。该项目的目标是开发多尺度数学框架来预测具有不同几何图案和化学涂层的膜表面的污染行为。能够预测硅胶中新膜表面的污染特性将加速发现新的膜设计，并缩短从实验室到市场的时间。在该项目中，将进行计算建模和实验测量之间的迭代反馈的综合研究，以检验两个主要假设：(1)膜表面几何和化学模式的有针对性的组合将显著减少膜污染；(2)经过实验训练的多尺度计算模型将加速发现显著减少膜污染的新的几何和化学表面修饰。这项研究将(I)建立一个数学框架和相应的模型，以确定控制质量和动量传递的物理机制和几何特征，(Ii)深入了解污染物和能量通量是如何被复杂的拓扑结构控制和调节的，(Iii)阐明过滤速度和反应传递过程的宏观行为是如何与微观和纳米尺度的现象相耦合的。这项工作将是变革性的，因为提供一个经过实验验证的计算框架将能够快速筛选许多膜表面修饰，以筛选出最有希望的修饰进行进一步测试，并将导致膜过滤技术的跨越式改进。该项目将为培养研究生和本科生研究人员提供一个多学科的环境。Zoom视频会议等新的交流平台将用于向小学提供虚拟科学演示和实验室参观。

项目成果

Dispersion controlled by permeable surfaces: surface properties and scaling

• DOI: 10.1017/jfm.2016.431
• 发表时间: 2016-08-01
• 期刊: JOURNAL OF FLUID MECHANICS
• 影响因子: 3.7
• 作者: Ling, Bowen;Tartakovsky, Alexandre M.;Battiato, Ilenia
• 通讯作者: Battiato, Ilenia