(487b) Agglomeration of Nanoparticles Evaluated Via a Constant Number Monte Carlo Simulation

Nanoparticles (NPs) tend to agglomerate in aqueous media which then affects their fate and transport in the environment and behavior in biological systems. Given the rapid growth of the nanotechnology industry, experimental mapping of the agglomeration behavior of the rapidly rising large number of NPs, over the range of NPs properties and water chemistry that may be of interest is a daunting task. In order to provide a platform for assessing the agglomeration behavior of NPs, a computational model was developed based on a constant-number dynamic simulation Monte Carlo (DSMC) simulation of particles in a box to essentially solve the Smoluchowski equation of particle agglomeration. In this modeling approach, NPs which are in Brownian motion collide and the attachment efficiency of colliding particles is dictated by the interaction energy between particles. In the present work, the total particle-particle interaction energy was quantified by an extended-DLVO theory that accounts for electrostatic and hydration repulsions and van der Waals attraction. Model predictions were assessed relative to experimental dynamic light scattering (DLS) size measurements for TiO₂, CeO₂, SiO₂, and a-Fe₂O₃ (hematite) demonstrated that the hydration repulsion energy can be significantly greater than the electrostatic repulsion energy at high ionic strength (IS) and low absolute zeta potential. Under such conditions the hydration repulsion increases the repulsion energy thus leading to lowering of the resulting agglomerate diameter. The present analysis suggests that quantification of the hydration repulsion over a broad range of suspension and NPs would be beneficial to improving predictions of the agglomeration of NPs in aqueous suspensions.