CAREER: Multiscale Simulations of Nanofluid Assembly for Smart Materials Design

职业：智能材料设计的纳米流体组装的多尺度模拟该项目由材料研究部的凝聚态物质和材料理论计划和刺激竞争研究的既定计划（EPSCoR）共同资助。非技术摘要该职业奖支持使用计算机模拟的研究和教育，以帮助理解和操纵流体乳液中稳定结构的形成。食品、化妆品和药品的许多现代配方基于混合两种或更多种流体组分以形成稳定的乳液。典型的流体组分，例如油和水，通常分离成两个单独的相。添加到混合物中的固体颗粒防止分离并导致形成稳定的隔室，从而产生混合物的特殊结构和性质。这些隔室可以封装和运输特定的化学成分，模仿活细胞的功能。这种结构化流体为我们提供了设计可按需控制和操纵的智能软材料的潜力。然而，随着时间的推移，决定界面和液滴在乳液中形成的复杂过程还不完全清楚，因此阻碍了制定控制不断变化的流体结构的协议。本项目旨在使用乳液中的磁性颗粒来操纵界面和液滴在外部磁场中的形成。PI的研究小组寻求探索控制相分离和刺激流体隔室分离和融合的方法。这将通过使用磁相互作用来定向颗粒并操纵流体组分之间的界面来完成。该研究将在克莱姆森大学的棕榈集群上使用大型计算机模拟，这是一个TOP500高性能计算系统。研究生和本科生的培训在这些活动中发挥着重要作用。PI将开发创新的教学材料，支持计算能力和研究计算技能的发展。PI的研究小组还寻求加强推广，并将设计计算机辅助材料设计的展示，以吸引越来越多的多学科领域的计算科学的广大观众。技术摘要该职业奖支持多尺度模拟的计算建模和教育，以理解和控制复杂多相流体中非平衡结构的形成。软界面为主的材料的介观结构和非线性流变学提出了许多挑战的控制机制，使智能流体的设计，自组织和响应外部刺激的发展。胶体颗粒的界面组装可以阻止不混溶流体的相分离，使得它们被捕获在亚稳态，例如，流体-双连续凝胶。这些逮捕相态出现在颗粒多组分混合物由于复杂的相互作用的物理化学相互作用跨越不同的长度和时间尺度。该研究的目的是获得一个基本的理解之间的连接微粒稳定的多相流体中的微尺度自组装和介观相形成，重点是非平衡现象和动力学逮捕相态的出现。该PI旨在采用格子Boltzmann模拟和创新的数据分析来探索定制复杂多相流体的相形态和流变特性的途径。该研究将研究在外部磁场中使用磁性颗粒来控制界面组装并操纵液滴和流体隔室的介观结构。大规模的格子玻尔兹曼模拟将被用来系统地研究的条件和参数下，这种控制是可能的乳液和流体双连续凝胶。PI旨在通过开发一种数据驱动的主动学习方法来推动软材料信息学的新兴领域，该方法用于具有定制结构-性能-处理关系的纳米流体组装。多尺度模拟方法和以数据为中心的方法的整合将促进新的纳米流体材料的发现和设计，并为具有目标功能的合成系统提供新的工程原理。该项目将为研究生和本科生提供发展高级计算能力和研究计算技能的机会。PI将开发课程组件和教材，整合多尺度建模，高性能计算和研究软件工程的各个方面。该项目开发的模拟方法和软件工具将增强基于模拟的科学和工程的更广泛的计算生态系统。PI的研究团队还将设计推广活动，展示使用先进的网络基础设施和虚拟现实/增强现实技术进行材料发现和探索。该奖项反映了NSF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。

CAREER: Multiscale Simulations of Nanofluid Assembly for Smart Materials DesignThis project is jointly funded by the Condensed-Matter-and-Materials-Theory program in the Division of Materials Research and by the Established Program to Stimulate Competitive Research (EPSCoR).NONTECHNICAL ABSTRACTThis CAREER award supports research and education using computer simulations to aid understanding and manipulating the formation of stable structures in fluid emulsions. Many modern formulations of food, cosmetic, and pharmaceutical products are based on mixing two or more fluid components to form a stable emulsion. Typical fluid components, such as oil and water, normally separate into two separate phases. Solid particles added to the mixture prevent the separation and lead to formation of stable compartments that give rise to peculiar structure and properties of the mixture. The compartments can encapsulate and transport specific chemical ingredients, mimicking the function of living cells. Such structured fluids offer us the potential to design smart soft materials that can be controlled and manipulated on demand. However, the complex processes that determine the formation of interfaces and droplets in emulsions over time are incompletely understood, thus hindering the formulation of protocols for control of the evolving fluid structure.This project aims to use magnetic particles in emulsions to manipulate the formation of interfaces and droplets in external magnetic fields. The PI's research group seeks to explore ways to control phase separation and to stimulate separation and fusion of fluid compartments. This will be done by using magnetic interactions to orient the particles and to manipulate the interface between fluid components. The research will employ large computer simulations on Clemson University's Palmetto cluster, a TOP500 high-performance computing system.Training of graduate and undergraduate students plays an important role in these activities. The PI will develop innovative teaching materials that support the development of computational competencies and research computing skills. The PI's research group also seeks to enhance outreach and will design showcases of computer-aided materials design to engage a broad audience in the increasingly multidisciplinary field of computational science.TECHNICAL ABSTRACTThis CAREER award supports computational modeling and education in multiscale simulations to understand and control the formation of non-equilibrium structures in complex multiphase fluids. The mesoscale structure and nonlinear rheology of soft interface-dominated materials raises many challenges for the development of control mechanisms that enable design of smart fluids that self-organize and respond to external stimuli. Interfacial assembly of colloidal particles can arrest the phase separation of immiscible fluids such that they become trapped in metastable states, e.g., fluid-bicontinuous gels. These arrested phase states emerge in particulate multicomponent mixtures due to the intricate interplay of physico-chemical interactions across different length and time-scales. The research aims to gain a fundamental understanding of the connection between microscale self-assembly and mesoscale phase formation in particle-stabilized multiphase fluids, with a focus on non-equilibrium phenomena and the emergence of kinetically arrested phase states. The PI seeks to employ lattice Boltzmann simulations and innovative data analytics to explore avenues for tailoring the phase morphology and rheological properties of complex multiphase fluids.The research will investigate the use of magnetic particles in external magnetic fields to control interfacial assembly and manipulate the mesoscale structure of droplets and fluid compartments. Large-scale lattice Boltzmann simulations will be used to systematically study the conditions and parameters under which such control is possible for emulsions and fluid-bicontinuous gels. The PI seeks to propel the nascent field of soft materials informatics by developing a data-driven active learning approach for nanofluid assembly with tailored structure-property-processing relations. The integration of multiscale simulation methods and data-centric approaches will foster discovery and design of new nanofluid materials with the expectation of new engineering principles for synthetic systems with targeted functionality.The project will provide opportunities for graduate and undergraduate students to develop advanced computational competencies and research computing skills. The PI will develop curriculum components and teaching materials that integrate diverse aspects of multiscale modeling, high-performance computing, and research software engineering. The simulation methods and software tools developed in this project will enhance the broader computing ecosystem for simulation-based science and engineering. The PI's research team will also design outreach activities showcasing the use of advanced cyberinfastructure and virtual-reality/augmented-reality technology for materials discovery and exploration. The activities aim to increase computing literacy and support broader participation in simulation-driven science and engineering.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.