Study of particle dynamics in dusty plasma system using stochastic models / Chew Wei Xiang
Dusty plasma typically consists of electrons and ions with micron-size charged dust particles. Due to complex inter-species interactions, the system accommodates rich phenomena such as formation of strongly-coupled states, structural phase transition, formation of linear and non-linear waves, and a...
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my.um.stud.41812014-10-01T02:42:02Z Study of particle dynamics in dusty plasma system using stochastic models / Chew Wei Xiang Chew, Wei Xiang Q Science (General) QC Physics Dusty plasma typically consists of electrons and ions with micron-size charged dust particles. Due to complex inter-species interactions, the system accommodates rich phenomena such as formation of strongly-coupled states, structural phase transition, formation of linear and non-linear waves, and anomalous diffusion behavior that violates the Fick’s law. Particles motion in dusty plasma can be modeled using Brownian motion, but this model is inadequate to fully capture the detailed dynamics. In this study, charged dust particle dynamics is investigated using stochastic process with fractal characteristics based on the fractional calculus. Dusty plasma is generated using a capacitively coupled 13.56 MHz radio frequency (rf) gas discharge system and different particle states are observed by varying the neutral gas pressure. Particle motion are probed by monitoring the intensity fluctuation of scattered light in dynamic light scattering (DLS) experiment and particle trajectories obtained from particle tracking using digital video camera. In DLS experiment, particle transport mechanisms are deduced by fitting empirical intensity correlation functions using different transport models, which include purely ballistic, purely diffusive, and hybrid ballistic-diffusive transport model with the assumption of monodisperse particles. The hybrid model is found to be most accurate in describing the particle transport. A new correlation model based on a non-standard fractional Langevin equation is introduced to model polydisperse dust particles dynamics. In particle tracking experiment, time-dependent scaling behavior in particles’ mean-square-displacement (MSD) is observed. This is consistent with the results from DLS experiment that shows dust particles undergo fast ballistic transport at short time scale and slow dynamic at longer time duration. Transient anomalous diffusion is described using a simple generalization of Riemann-Liouville fractional Brownian motion. The study is concluded with a brief discussion on how the DLS and MSD approaches can be corroborated to give useful insights into complex particle transport in dusty plasmas. 2013 Thesis NonPeerReviewed application/pdf http://studentsrepo.um.edu.my/4181/1/chew_wei_xiang_thesis.pdf Chew, Wei Xiang (2013) Study of particle dynamics in dusty plasma system using stochastic models / Chew Wei Xiang. Masters thesis, University of Malaya. http://studentsrepo.um.edu.my/4181/ |
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Q Science (General) QC Physics Chew, Wei Xiang Study of particle dynamics in dusty plasma system using stochastic models / Chew Wei Xiang |
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Dusty plasma typically consists of electrons and ions with micron-size charged dust particles. Due to complex inter-species interactions, the system accommodates rich
phenomena such as formation of strongly-coupled states, structural phase transition, formation of linear and non-linear waves, and anomalous diffusion behavior that
violates the Fick’s law. Particles motion in dusty plasma can be modeled using Brownian motion, but this model is inadequate to fully capture the detailed dynamics. In
this study, charged dust particle dynamics is investigated using stochastic process with fractal characteristics based on the fractional calculus. Dusty plasma is generated using
a capacitively coupled 13.56 MHz radio frequency (rf) gas discharge system and different particle states are observed by varying the neutral gas pressure. Particle motion
are probed by monitoring the intensity fluctuation of scattered light in dynamic light scattering (DLS) experiment and particle trajectories obtained from particle tracking using digital video camera. In DLS experiment, particle transport mechanisms are deduced by fitting empirical intensity correlation functions using different transport models, which include purely ballistic, purely diffusive, and hybrid ballistic-diffusive transport model with the assumption of monodisperse particles. The hybrid model is found to be most accurate in describing the particle transport. A new correlation model based on a non-standard fractional Langevin equation is introduced to model polydisperse dust particles dynamics. In particle tracking experiment, time-dependent scaling behavior in particles’ mean-square-displacement (MSD) is observed. This is consistent with the results from DLS experiment that shows dust particles undergo fast ballistic transport at short time scale and slow dynamic at longer time duration.
Transient anomalous diffusion is described using a simple generalization of Riemann-Liouville fractional Brownian motion. The study is concluded with a brief discussion on
how the DLS and MSD approaches can be corroborated to give useful insights into complex particle transport in dusty plasmas. |
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Thesis |
author |
Chew, Wei Xiang |
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Chew, Wei Xiang |
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Chew, Wei Xiang |
title |
Study of particle dynamics in dusty plasma system using stochastic models / Chew Wei Xiang |
title_short |
Study of particle dynamics in dusty plasma system using stochastic models / Chew Wei Xiang |
title_full |
Study of particle dynamics in dusty plasma system using stochastic models / Chew Wei Xiang |
title_fullStr |
Study of particle dynamics in dusty plasma system using stochastic models / Chew Wei Xiang |
title_full_unstemmed |
Study of particle dynamics in dusty plasma system using stochastic models / Chew Wei Xiang |
title_sort |
study of particle dynamics in dusty plasma system using stochastic models / chew wei xiang |
publishDate |
2013 |
url |
http://studentsrepo.um.edu.my/4181/1/chew_wei_xiang_thesis.pdf http://studentsrepo.um.edu.my/4181/ |
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