Simulations of interacting colloids using a Stochastic Kinetic Theory

The behavior of soft matter and polymer systems is driven by a complex interplay between multiple interactions such as electrostatics, excluded volume and hydrodynamic interactions and particle motions arising from thermal fluctuations and diffusion, leading to correlations. These systems exhibit phenomena, such as liquid–liquid phase separation and charge screening. Capturing these phenomena across multiple length and time scales can be challenging, especially for concentrated systems. In this work, we apply a stochastic kinetic theory, also called Stochastic Density Functional Theory (SDFT), to a system of colloids interacting via electrostatic and soft excluded volume interactions. This approach describes the system in terms of stochastic differential equations for the number densities derived from the Langevin equations of individual particles and naturally incorporates fluctuations while relying only on microscopic models of constituent species and interactions. We develop and validate numerical schemes to perform simulations using this approach. We investigate phase separation and the effect of interactions and particle properties on the correlations and dynamics using numerical simulations. We also extend our approach using hybrid quantum–classical algorithms.