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Predicting The Nanoparticle Diffusion using Computational Fluid Dynamics (CFD)

Hasan, Nurul (2010) Predicting The Nanoparticle Diffusion using Computational Fluid Dynamics (CFD). In: International Conference on Process Engineering and Advanced Materials (ICPEAM 2010), 15-17 June 2010, Kuala Lumpur Convention Centre.

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Abstract

The modeling of flow through regular sized channels is a relatively easy task. However, when the channel size reduces to the order of micrometers and nanometers, the physics of the particle motion change. Many other factors have to be taken into consideration, such as Brownian Motion and Vander-Waal forces. At such a small scale it is hard to determine the a dominant force, i.e. we do not know whether the drag force is greater than the electrostatic force or the electrostatic force is greater than the Brownian force. The aim of this paper is to solve this problem and try to create a better understanding of the forces in question. The application of such a filter is in capturing nano-sized particles such as viruses. Since these particles are small, it is hard to capture them by physical means. Therefore we have to devise new techniques to capture these particles. We can use simulations to create results instead of carrying out experiments because we are dealing with such a small case. The fabrication of such a filter is an extremely complicated process. In fact even if we have the filter it is hard to mount it in an experimental setup without damaging it. Several parts of these simulations was carried out using a Finite element package called COMSOL Multi- Physics. This package is a great multi-physics tool as it allows seamless integration of various physics, In this case it is mainly Navier-Stokes Equations and Electro-magnetic Equations.

Item Type:Conference or Workshop Item (Paper)
Subjects:T Technology > TJ Mechanical engineering and machinery
Departments / MOR / COE:Departments > Mechanical Engineering
Research Institutes > Institute for Health Analytics
Departments > Chemical Engineering
Research Institutes > Institute for Autonomous Systems
ID Code:5310
Deposited By: Dr. Nurul Hasan
Deposited On:07 Apr 2011 09:09
Last Modified:19 Jan 2017 08:23

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