CAREER: Multiscale Simulations of Nanofluid Assembly for Smart Materials Design

CAREER: Multiscale Simulations of Nanofluid Assembly for Smart Materials Design

This 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 ABSTRACT

This 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 ABSTRACT

This 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.