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\begin{document} |
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\renewcommand{\lstlistingname}{Scheme} |
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\frontmatter |
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\work{Dissertation} % Change to ``Thesis'' for Master's thesis |
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\title{MOLECULAR DYNAMICS SIMULATIONS OF PHOSPHOLIPID BILAYERS AND LIQUID CRYSTALS} |
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\title{MOLECULAR DYNAMICS METHODOLOGY AND SIMULATIONS OF PHOSPHOLIPID BILAYERS AND LIQUID CRYSTALS} |
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\author{Teng Lin} |
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\degprior{B.S., B.E.} % All previously earned degrees |
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\degaward{Doctor of Philosophy} % What this paper is for |
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%% \copypage % Uncomment if you want a copyright page |
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\begin{abstract} |
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|
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As an rapidly expanding interdisciplinary of physics, chemistry and |
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biology \emph{etc}, soft condensed matter science studies the |
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kinetics, dynamics and geometric structures of complex materials |
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like membrane, liquid crystal and polymers \emph{etc}. These soft |
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condensed matters are distinguished by the unique physical |
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properties on the mesoscopic scale which can provide useful insights |
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to understand the basic physical principles linking the microscopic |
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structure to the macroscopic properties. Knowledge of the underlying |
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physics is of benefit to a wide range of applications areas, such as |
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the processing of biocompatible materials and development of LCD |
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display technologies. Although the separation of the length scale |
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allows statistical mechanics to be applied, the interesting behavior |
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of these systems usually happens on the time scale well beyond the |
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current computing power. In order to simulate large soft condensed |
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systems for long times within a reasonable amount of computational |
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time, some new coarse-grained models were proposed in this |
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dissertation to describe phospholipids and banana-shaped liquid |
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crystals. Although these models can be described using a small |
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number of physical parameter, it is not trivial to maintain the |
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introducing rigid constraints between different molecular fragments |
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correctly and efficiently. Working with colleagues, I developed a |
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new molecular dynamics framework capable of performing simulation on |
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systems with orientational degrees of freedom in a variety of |
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< |
ensembles. Using this new package, I study the structure, the |
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dynamics and transport properties of the biological membranes as |
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well as the the phase behavior of banana shaped liquid crystal. A |
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new Langevin dynamics algorithm for arbitrary rigid particles is |
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proposed to mimic solvent effect which may eventually expand the |
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< |
time scale of the simulation. |
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> |
As a rapidly expanding interdisciplinary science bridging physics, |
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> |
chemistry and biology, the study of soft condensed matter involves |
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> |
the kinetics, dynamics and geometric structures of complex materials |
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> |
like membrane, liquid crystal and polymers. These soft condensed |
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> |
materials are distinguished by the unique physical properties on the |
53 |
> |
mesoscopic scale which can provide useful insights to understand the |
54 |
> |
basic physical principles linking the microscopic structure to the |
55 |
> |
macroscopic properties. Knowledge of the underlying physics is of |
56 |
> |
benefit to a wide range areas, such as the processing of |
57 |
> |
biocompatible materials and development of LCD display technologies. |
58 |
> |
Although the separation of the length scales allows statistical |
59 |
> |
mechanics to be applied, the interesting behavior of these systems |
60 |
> |
usually happens on time scale well beyond current computing power. |
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> |
In order to simulate large soft condensed systems for long times |
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> |
within a reasonable amount of computational time, some new |
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> |
coarse-grained models are presented in this dissertation to describe |
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> |
phospholipids and liquid crystals. Although these |
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> |
models can be described using a small number of physical parameters, |
66 |
> |
it is not trivial to introduce rigid constraints between different |
67 |
> |
molecular fragments correctly and efficiently. Working with |
68 |
> |
colleagues, I developed a new molecular dynamics framework capable |
69 |
> |
of performing simulation on systems with orientational degrees of |
70 |
> |
freedom in a variety of ensembles. Using this new package, I studied |
71 |
> |
the structure, dynamics and transport properties of the biological |
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> |
membranes as well as the the phase behavior of liquid |
73 |
> |
crystals. A new Langevin dynamics algorithm for arbitrary rigid |
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> |
particles is also presented to mimic solvent effects which may |
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> |
eventually expand the time scale of the simulation. |
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|
|
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\end{abstract} |
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