[CCoE Notice] PhD Defense Deepak Mangal of Chemical Engineering

[UH Cullen College of Engineering]

PhD Dissertation Defense of Deepak Mangal

DATE:  December 1, 2021

TIME: 3-5pm

COMMITTEE CHAIRs: Prof. Jeremy Palmer and Prof. Jacinta Conrad

LOCATION:  Zoom link: https://urldefense.com/v3/__https://uh-edu-cougarnet.zoom.us/j/99765234812__;!!LkSTlj0I!Fsc1lRiy2d0kHYnBB7IisBTUOoPBdoHTgOOEY-KK3HIWB5xdgUvzlERbHsRinVNzdJkUqCdpN7IvjJItugLAfCqSm8E$ 



TITLE:   Simulation of finite-sized nanoparticle transport through porous media



Understanding the transport of finite-sized particles comparable to pore or throat diameter through a porous medium is important in many industrial and natural processes, including oil recovery, drug delivery, the dispersion of nutrients, minerals, and contaminants through soils, and separations techniques such as gel electrophoresis and chromatography. One key aspect influencing nanoparticle transport is the nature of their interactions with the surrounding medium, which include steric repulsions, van der Waals and depletion-induced attractions, and hydrodynamic and electrostatic forces. However, the influence of these interactions remains incompletely understood, particularly their effects on how particles disperse through porous media under non-equilibrium flow conditions. We investigate the effects of these interactions and other factors on particle dispersion in ordered arrays using Stokesian dynamics simulation. We find that steric and hydrodynamic interactions hinder particle diffusivity under quiescent conditions and enhance longitudinal dispersion under flow. Next, we examine the effect of array structure and flow orientations on particle transport in similar model systems. We find that quiescent diffusion is independent of array geometry. Longitudinal dispersion under flow depends on the direction of incident flow relative to the array lattice vectors. Lastly, we examine the effects of physicochemical attractions between particle and ordered arrays. We find that weak attractions negligibly affect particle transport due to dominant Brownian fluctuations. Strong attractions, however, significantly hinder particle diffusion due to the localization of particles near the nanoposts. Conversely, under flow conditions, strong attractions significantly enhance longitudinal dispersion at low to moderate Péclet number (Pe). At high Pe, however, advection becomes dominant and attractions weakly enhance the dispersion. The insights from our research work will help to improve the design of nanoparticles for transport through porous media and the design of periodic microstructures for separations of nanomaterials
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