CAREER: CYBER-ENABLED MULTISCALE METHODOLOGY FOR HYBRID SOFT MATERIALS-BASED NANOPARTICLE DESIGN

NONTECHNICAL SUMMARYThe Division of Materials Research in the Mathematical and Physical Sciences Directorate and the Office of Advanced Cyberinfrastructure in the Directorate for Computer and Information Science and Engineering contribute funds for this project. This CAREER award supports computational research, cyberinfrastructure development, and education toward the ability to design nanoparticles with desired properties. Nanoparticles are encountered everywhere such as food, drugs, cars and cosmetics. The properties of nanoparticles are determined by the molecules they encompass, and can be precisely adjusted by using different kinds of molecules. Creating nanoparticles with specific properties and molecular constituents requires understanding how the molecules interact with each other and pack together. Given the vast number of molecules available, an efficient method is required to relate the characteristics of a nanoparticle to the properties of its molecular constituents. Of special interest are nanoparticles made of soft materials, such as those in car tires, jello and detergents, which can store various molecules. This CAREER project supports computational research and education on the computational design of mixed soft materials-based nanoparticles with desired characteristics. The PI's approach will use a method that includes essential physics and chemistry at different scales of length and time. The method will be aided by the development and use of advanced cyberinfrastructure. This research will support activities to stimulate the interest of high school students in science, engineering and mathematics. In addition, the research will be used to engage and inform the general public of the role of computation in materials design to society and benefits of University-level education. Finally, the research will enhance and maintain a competitive science and engineering workforce by increasing awareness of advanced computing methods and tools for materials design among undergraduate, graduate students and the scientific community.TECHNICAL SUMMARYThe Division of Materials Research in the Mathematical and Physical Sciences Directorate and the Office of Advanced Cyberinfrastructure in the Directorate for Computer and Information Science and Engineering contribute funds for this project. This CAREER award supports computational research, cyberinfrastructure development, and education toward the ability to design nanoparticles with desired properties. The PI aims to advance the ability to design of hybrid soft materials-based nanoparticles (NPs) with specific structure-property relations aided by the development and use of a cyber-enabled multiscale methodology. The conception of such designs will require a fundamental understanding of the role of molecular conformation, organization and mobility on the collective behavior of the distinct molecular species, and thereby, on material properties. The research lies at the interface of soft materials and advanced computing, and affords an opportunity to increase awareness, interest, recruitment, retention and training of a competitive workforce in science, technology, engineering, and mathematics areas.The PI seeks to design sterically stable hybrid NPs with morphologies optimized to store various molecules. The NP designs will require understanding the links between molecular traits and desired properties of hybrid soft materials. This will be facilitated by the development and use of a multiscale method that can link the compositional details of the NP to its desired attributes by integrating Molecular Dynamics simulations and analysis tools with advanced cyberinfrastructure. This plan will be realized through three objectives: (1) Development of hybrid NP designs; (2) Elucidation of the role of pH on hybrid NP designs, and (3) Prediction and validation of hybrid NP designs encompassing alternate chemical species.The prediction of soft materials-based nanoparticles with desired properties will be significantly accelerated by understanding the relationship between molecular traits and structure-property relations. Both the design rules and the method can be extended to conceive other multicomponent soft material-based systems with targeted structure-property relations. In addition, the use of advanced computing tools in virtual soft materials design can nucleate the adoption of new computational methodologies by the community. This will facilitate the accelerated development of new soft materials-based innovations and technologies.