(520b) Inverse Design of Liquid State Density Fluctuations: Application to Equilibrium Particle Clustering

The inverse statistical mechanical problem of discovering optimal pair potentials that favor targeted (typically ordered), equilibrium structures is becoming commonplace in the bottom-up coarse-grained simulation community. Such tools can also be used to inverse design complex, correlated, fluid states with tailored density fluctuations for a wide range of applications. As an example, this talk will focus on designing a fluid which exhibits monodisperse, spherical, liquid-droplet-like clusters of a controlled size and good center of mass mobility. Our inverse designed potential will be compared to the popular short-range-attractive, long-range-repulsive (SALR) pair interaction, considered the canonical model for equilibrium clustering. Unlike our tailored potential, the SALR potential yields microcrystalline clusters which are not likely representative of systems where crystallization is kinetically or thermodynamically inhibited (i.e. protein suspensions, polydisperse colloids). Adding particle level polydispersity to the SALR system does effectively prevent micro-crystallinity but at the cost of forming very polydisperse, irregular aggregates. The generality of inverse designing density fluctuations and the broader applications will also be discussed.