Hierarchical Approach to Model Multilayer Colloidal Deposition in Porous Media

Abstract

Particle deposition is important in many environmental systems such as water and wastewater filtration, air pollution control, subsurface transport, biofilm formation and fouling, and thin film synthesis for use in remediation technologies. While continuum-level models have been developed to predict deposition dynamics in these systems, these models fail to explain transient dynamics of multilayer deposition from a mechanistic viewpoint. In this work, a multiscale approach has been developed to predict multiple layer irreversible colloidal deposition in the presence of interparticle electrostatic and van der Waals interactions in porous media. The approach combines the kinetic information obtained from the mesoscopic stochastic simulations of particle deposition with the macroscopic conservation equation describing colloidal transport. Sequential Brownian dynamics simulations are first performed by accounting for particle-particle (P-P) and particle-surface (P-S) interactions, and multilayered particle deposits are obtained. The available surface function quantifying the deposition kinetics is then obtained from the deposit microstructure. Deposition dynamics are studied at different ionic strengths and particle potentials that control the range and magnitude of interparticle interactions. Simulation results showed that the microstructure of the particle deposits formed under the influence of P-P and P-S electrostatic interactions exhibited significant variations with respect to ionic strength and could be qualitatively explained bythe interplay between the repulsive and attractive P-P and P-S interaction forces. The available surface function also varied significantly as a function of ionic strength. This basic understanding of the deposition dynamics at the mesoscale was then combined with the continuum-level transport equations to predict particle breakthrough curves in porous media. The approach is capable of capturing transient features of deposition dynamics, as demonstrated by the good agreement between the model predictions and the experimental observations.