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
Depositing User: Dr. Nurul Hasan
Date Deposited: 07 Apr 2011 09:09
Last Modified: 19 Jan 2017 08:23
URI: http://scholars.utp.edu.my/id/eprint/5310

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