Nanoparticle Aggregation in Porous Media with Computations

The aggregation of nanoparticles (NPs) within porous media affects the mobility of NPs. Understanding aggregation remains limited due to the difficulties associated with conducting experiments in complex media. Previous computational models are mainly stochastic because of the difference in scales between diffusion, convection and particle intractions.¹ In this work, a Lagrangian particle tracking model is built that takes the interactions among particles into account. It can compute the aggregation kinetics accurately and it predicts the morphology of aggregates. Six forces including gravity, buoyancy, drag, random, van der Waals, and electrostatic forces are considered. A dynamic timestep is utilized to ensure that particles do not overlap with others or move into the solid matrix of the porous media. The model has been validated against experiments of Cerium oxide (CeO₂) suspended in different potassium chloride (KCl) solutions.² To simulate the aggregation of NPs in porous media, the flow field is solved by applying the Lattice Boltzmann method,³ and the new Lagrangian model is employed to simulate the aggregation of the CeO₂ particles in KCl solutions moving in the pore space between randomly packed spheres to examine the effects of electrolyte concentration, particle size, and pore velocity on the aggregation kinetics, the aggregate fractal dimension, and asphericity.

REFERENCES

(1) Pham, N. H.; Papavassiliou, D. V.. Int. J. Heat Mass Transf. 2018, 121, 477–487. https://doi.org/10.1016/j.ijheatmasstransfer.2017.12.150.

(2) Li, K.; et al. J. Nanoparticle Res. 2011, 13 (12), 6483–6491. https://doi.org/10.1007/s11051-011-0548-z.

(3) Papavassiliou, D. V. et al., in Numerical Methods and Advanced Simulation in Biomechanics and Biological Processes; Elsevier, 2018; pp 415–429. https://doi.org/10.1016/B978-0-12-811718-7.00023-X.