(100a) Morphological Control of Structures Self-Assembled from Strongly Interacting Nanoparticles and Colloids

Identifying particles that will self-assemble into a desired structure is a difficult task due to the enormous parameter space that includes inter-particle interactions, particle shape, and thermodynamic parameters such as density and temperature. Computer simulation plays a valuable role in exploring this design space, but the increasing complexity of available building blocks can render traditional simulation methods useless. In this work, we demonstrate the use of a new computational tool we have developed to study the assembly possibilities of a family of similar strongly interacting particles. By efficiently generating energy-minimizing configurations of these particles, we identify those that have the potential to assemble into interesting and desirable structures. Some of these structures include patterns with multiple levels of periodicity, discrete and continuous domains, and open structures with uniform pore sizes. In addition to identifying energy-minimizing structures for a family of particles, our algorithm suggests possible assembly strategies for generating these configurations.