Nanoparticles (NPs) have been widely used in various fields such as drugs & medications, household applications, petroleum engineering, environmental engineering, and so on, which makes understanding their mobility essential. The mobility of NPs in porous media, however, is significantly impacted by their tendency to aggregate since large aggregates may induce some problems such as pore clogging or blocking, thus reducing the mobility of NPs. It is very challenging to perform experiments studying the aggregation of NPs in such complex media; therefore, there are many models built to simulate this process. However, most of them based on aggregation probabilities rather than the physics of particle-particle interactions due to the multiscale nature of this process.
1 The movement of NPs is controlled by diffusion and convection; and simulated at large timesteps (10
-4 or 10
-5s). On the contrary, aggregation is affected by particle-particle interactions, which are applicable when the distance between two particles is as small as a few nanometers; and it is simulated at much smaller timesteps (10
-8 or 10
-9s). Moreover, these stochastic models fail to predict the morphology of aggregates because they are not based on the physics of interactions among particles. Our aim is to build a new Lagrangian particle tracking model based on force balance approach to study the aggregation of NPs and the morphology of aggregates in a porous medium, by taking physicochemical interactions among particles into consideration (to avoid using probabilities). Our model is relied on the Newton second law of motion; and the various forces exerted on a particle include the van der Waals, electrostatic, random, drag, gravity, and buoyancy ones. To overcome the multiscale challenges, dynamic timesteps are used to ensure that both movement and aggregation of particles are accurately simulated. The model has been validated against experimental results of CeO
2 particles suspended in KCl solutions with different concentrations in 100 minutes.
2 To simulate the aggregation of NPs in a porous medium, the lattice Boltzmann method is used to solve the flow field in such medium.
3 Then, our aggregation code is used to investigate the effects of electrolyte concentration, fluid velocity, and particle-size on the aggregation kinetics and morphology of aggregates when NPs move in the random sphere packings. We also intend to investigate the dependence of aggregation kinetics and aggregate morphology on the Peclet number for both diffusion and reaction-limited regimes, which facilitates the quick prediction of aggregation kinetics and morphology of aggregation.
REFENRENCES
(1) Pham, N. H.; Papavassiliou, D. V. Hydrodynamic Effects on the Aggregation of Nanoparticles in Porous Media. Int. J. Heat Mass Transf. 2018, 121, 477–487. https://doi.org/10.1016/j.ijheatmasstransfer.2017.12.150.
(2) Li, K.; Zhang, W.; Huang, Y.; Chen, Y. Aggregation Kinetics of CeO2 Nanoparticles in KCl and CaCl2 Solutions: Measurements and Modeling. J. Nanoparticle Res. 2011, 13 (12), 6483–6491. https://doi.org/10.1007/s11051-011-0548-z.
(3) Papavassiliou, D. V.; Pham, N. H.; Kadri, O. E.; Voronov, R. S. Lattice Boltzmann Methods for Bioengineering Applications. 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.
