A Two-Level, Discrete Particle Approach For Large-Scale Simulation Of Colloidal Aggregates

Most numerical techniques employed for aggregation simulation are based on equilibrium growth assumption and Smoluchowski theory. We present a new two-level discrete particle model, which can be employed in simulating large colloidal clusters in highly nonequilibrium physical conditions. We consider the system of colloidal particles (CP) interacting via conservative CP–CP repulsive-attractive two-body forces, which is initially mixed in a dissipative solvent. In order to obtain a high-resolution picture of colloidal dynamics, we employ around 20 million particles consisting of two kinds of particles. For bridging the spatio-temporal scales between nanoscale colloidal and the solvent particles (SP), the solvent is modeled by dissipative particle dynamics (DPD) fluid. We focus on the systems size for which the CP–SP interactions can also be described by the DPD forces. Unlike previous numerical techniques, the two-level particle model can display much more realistic physics, thus allowing for the simulation of aggregation for various types of colloids and solvent liquids in a broad range of conditions. We show that not only large and static clusters but also the initial stages of aggregation evolution can be better scrutinized. The large-scale simulation results obtained in two-dimensions show that the mean cluster size grows with timetaccording to the power lawtκ. Because of the time-dependence of growth mechanism, the value of κ necessarily must change. We have firstκ = 1with a value of 1 achieved asymptotically with time. We can also discern intermediate-scale structures. We emphasize that the method developed here can be easily extended to algorithms dealing with multi-level hierarchy and multiphase fluid dynamics.