Designing Novel Tunable Colloids Via Inverse Statistical Mechanics

Princeton University, Princeton NJ

Investigators

Abstract

The design of many advanced materials relies on the ability to devise building blocks, such as colloids and polymers, that interact with each other in specific ways to self-organize and form materials with novel electronic, mechanical, or optical properties. Scientists and engineers predict this process by specifying an interaction potential between the building blocks and then computing the material structure and its properties that arise from self-organization. This award will support theoretical and computational research to discover new materials using the opposite or ”inverse” approach. In the inverse approach, designers start by specifying the desired material structure and properties and then discover the required interactions between the building blocks that will produce the desired structure. The project will emphasize finding interactions that can be realized experimentally by combining currently available colloidal interactions. Hence, the results should provide guidance to experimentalists to fabricate designer colloids. The inverse approach will provide new ways to control the degree of order/disorder of the material to achieve novel properties, which will accelerate the discovery of materials by design. The project will support training of graduate students and will provide opportunities for undergraduates to participate in research. Algorithms resulting from the research will be made freely available to researchers and will be used to enhance student education. This award supports theoretical and computational research for materials discovery by inverse statistical-mechanical optimization techniques, which allows for a new mode of thinking about the structure and physical properties of condensed phases of matter. A major aim of this project is to further develop and apply inverse statistical mechanics to yield optimized potentials, both isotropic and anisotropic, including those subject to the constraint that they are experimentally realizable in colloidal systems. Such soft matter systems provide a rich testbed to study self-assembly, since both repulsive and attractive interactions can be tuned (e.g., excluded-volume repulsions, depletion interactions, Van der Waals forces, forces induced by functionalizing the particle surface, and electrostatic repulsions) and therefore offer a panoply of possible potentials that far extends the range offered by molecular systems. Potential functions, for both single and multicomponent systems, will be “tailored” to achieve the robust self-assembly of unique targeted crystal, liquid and amorphous states of matter, including exotic disordered hyperuniform systems. Examples of materials that will be designed include novel disordered materials for photonics and structural color, materials with exotic electromagnetic and elastodynamic properties, and materials with optimal transport and mechanical properties. Both equilibrium and nonequilibrium routes will be employed to achieve colloidal and particulate systems with novel physical properties. Finally, the outcomes of this project are expected to have the far-reaching benefit of providing guidance to experimentalists to fabricate designer colloids with optimized interactions and to fabricate optimized disordered hyperuniform materials via 3D printing techniques. 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.