CAREER: Designing Surface Patterns for Adaptive Shape Control of Soft-Matter-Based Nanoparticles

Indiana University, Bloomington IN

Investigators

Abstract

NONTECHNICAL SUMMARY This CAREER award supports an integrated computational and theoretical research, education, and outreach project to develop design patterns for adaptive shape control of nanoparticles made from soft materials. Much of the cream, soap, and gel we use in everyday life, the food we eat, and the biological matter we are made of is classified as soft material. Soft materials include matter such as colloidal dispersions (paints, milk), polymers (plastics, fibers), biological matter (proteins, cells), and liquid crystals (electronic displays). The PI is particularly motivated by biological soft materials that dynamically change their shape in response to chemical and mechanical cues. For example, proteins change conformations in response to changes in ion concentration to enable specific biological processes, and red blood cells deform reversibly to enable their passage through thin capillaries. Researchers have long sought to mimic this intrinsic adaptability of biological materials in the design of synthetic matter. In this project, the PI will develop powerful computational methods to link the inherent attributes of soft-matter-based nanoparticles with their mechanistic behavior, including stable shapes, real-time shape evolution, and self-organization into larger nanostructures. The PI's research team will program the surface charge and elasticity patterns of charged soft-matter-based nanoparticles such as virus-like nanocages and polymeric nanomembranes to enable controlled shape adaptation. Establishing the links between surface pattern and shape will guide the development of deformable nanocontainers into drug-delivery carriers that adapt their shape to evolving physiological conditions and biological barriers. The findings will also elucidate the principles of designing shape-reconfigurable nanoparticles that can act as building blocks of next-generation materials with responsive properties tailored for specific applications, such as shape-shifting microrobots and functional coatings with adaptive optical response. The education and outreach components of this project are directly integrated with its research investigations. The PI will lead a simulation-to-3D-printing workshop for high-school students in Bloomington, Indiana, where they will become familiar with applications of computing tools and fabrication techniques while learning about the design of matter at the nanoscale. The PI's team will design web-based science gateways to bring the computational methods developed in this project to classrooms in and outside of Indiana University, and facilitate the learning of underrepresented students at Minority-Serving Institutions. The PI is in a unique position to play a pivotal role in the design and implementation of a brand-new undergraduate program focused on nanoscale engineering that will significantly impact Indiana University, as it will train a diverse pool of undergraduate students to develop advances in nanotechnology. TECHNICAL SUMMARY This CAREER award supports computational and theoretical research and education to identify the fundamental mechanisms of engineering adaptive shape control in soft-matter-based nanoparticles. Harnessing the adaptability of biological materials in synthetic matter is one of the biggest challenges in materials engineering. The PI is deeply inspired by biology, where viral capsomeres self-assemble into rods and spheres which display shape adaptation, and where proteins selectively bind to viruses that exhibit unique combinations of surface pattern and shape. With such instances in mind, in this project, the PI will connect the surface patterning to mechanistic behavior for nanoparticles made from charged soft materials, such as virus-like nanocontainers, micellar vesicles, and polymeric nanomembranes. The PI's research team will investigate how surface charge and elasticity patterns affect the overall shape of these nanoparticles, and how these patterns control the timescales of shape-switching and aggregation of nanoparticles in physiological conditions. Molecular dynamics simulations will be used to probe surface charge and elasticity patterns that 1) enable nanoparticle shape adaptation, and 2) control real-time shape-switching and assembly of nanoparticles into higher-order nanostructures. The PI will develop molecular dynamics methods that are uniquely capable of connecting the smaller length-scale effects of counterion condensation on nanoparticle surfaces to the larger length-scale aggregation behavior of nanoparticles. Based on this multiscale information, this research will produce maps that link surface patterns to equilibrium and dynamical properties of the shapes of virus-like nanoparticles and polymeric nanomembranes for a wide range of environmental conditions. These maps will help guide the design of deformable nanoparticles that can actively change shape and associated functionalities, advancing the current capabilities for engineering biomimetic nanocontainers for applications in targeted drug-delivery. This research will also expand the synthetic capabilities of designing reconfigurable materials via the self-assembly of deformable nanoscale building blocks. This project will involve graduate students, undergraduate students, and a diverse online community of users in active research via hands-on experiences and research-based courses, workshops, and online computing platforms. The PI will develop a simulation-to-3D-printing workshop and web-based science gateways that will provide a sophisticated, user-friendly environment to engage with the simulations of nanoparticles. These platforms will facilitate access of the educational and research materials to a broad group of students and educators, including those at Minority-Serving Institutions. 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.