CAREER: Multiscale Simulations of Nanofluid Assembly for Smart Materials Design

CARAPE：用于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与材料理论计划和既定的激励竞争研究计划(EPSCoR)共同资助。非技术摘要该CARADE奖支持使用计算机模拟来帮助理解和操纵流体乳状液中稳定结构的形成的研究和教育。食品、化妆品和药品的许多现代配方都是基于混合两种或两种以上的液体成分以形成稳定的乳状液。典型的流体成分，如油和水，通常分成两个独立的相。添加到混合物中的固体颗粒阻止了分离，并导致形成稳定的隔室，从而导致混合物的特殊结构和性质。这些隔间可以包裹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，决定乳状液中界面和液滴随时间形成的复杂过程尚不完全清楚，从而阻碍了控制不断演变的流体结构的协议的制定。本项目旨在利用乳状液中的磁性粒子来操纵外部磁场中界面和液滴的形成。PI的研究小组寻求探索控制相分离和刺激流体隔间的分离和融合的方法。这将通过使用磁相互作用来定向颗粒并操纵流体组件之间的界面来实现。这项研究将在克莱姆森大学的Palmetto集群上进行大型计算机模拟，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扮演着重要的角色。PI将开发创新的教材，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，以在日益多学科的计算科学领域吸引更多的受众。技术摘要该职业奖支持多尺度模拟的计算建模和教育，以了解和控制复杂多相流体中非平衡结构的形成。以软界面为主的材料的介观结构和非线性流变学为控制机制的开发提出了许多挑战，使智能流体能够自组织并对外部刺激做出响应。胶体粒子的界面组装可以阻止不相容流体的相分离，从而使它们被困在亚稳态，例如流体-双连续凝胶。这些滞留的相态出现在颗粒多组分混合物中，是由于不同长度和时间尺度上的物理化学相互作用的错综复杂的相互作用。这项研究旨在从根本上理解颗粒稳定多相流体中微尺度自组装和介观相形成之间的联系，重点是非平衡现象和动力学停滞相态的出现。PI试图使用格子Boltzmann模拟和创新的数据分析来探索调整复杂多相流体的相形态和流变性的途径。这项研究将调查使用外部磁场中的磁性粒子来控制界面组装和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乳状液和流体双连续凝胶进行这种控制的条件和参数。PI寻求通过开发一种具有量身定制的结构-性质-加工关系的纳米流体组装的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。多尺度模拟方法和以数据为中心的方法的集成将促进新纳米流体材料的发现和设计，并期待具有目标功能的合成系统的新工程原理。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，将多尺度建模、高性能计算和研究软件工程的不同方面整合在一起。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。国际和平研究所的研究小组还将设计外联活动，展示使用先进的网络基础设施和虚拟现实/增强现实技术来发现和探索材料。这些活动旨在提高计算能力，并支持更广泛地参与模拟驱动的科学和工程。这一奖项反映了NSF的法定使命，并通过使用基金会的智力优势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.