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\usepackage{listings} |
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\usepackage{cite} |
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%\usepackage from oopseDoc.tex |
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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 phosphlipids 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 |
| 78 |
< |
time scale of the simulation. |
| 49 |
> |
As a rapidly expanding interdisciplinary science bridging physics, |
| 50 |
> |
chemistry and biology, the study of soft condensed matter involves |
| 51 |
> |
the kinetics, dynamics and geometric structures of complex materials |
| 52 |
> |
like membrane, liquid crystal and polymers. These soft condensed |
| 53 |
> |
materials are distinguished by the unique physical properties on the |
| 54 |
> |
mesoscopic scale which can provide useful insights to understand the |
| 55 |
> |
basic physical principles linking the microscopic structure to the |
| 56 |
> |
macroscopic properties. Knowledge of the underlying physics is of |
| 57 |
> |
benefit to a wide range areas, such as the processing of |
| 58 |
> |
biocompatible materials and development of LCD display technologies. |
| 59 |
> |
Although the separation of the length scales allows statistical |
| 60 |
> |
mechanics to be applied, the interesting behavior of these systems |
| 61 |
> |
usually happens on time scale well beyond current computing power. |
| 62 |
> |
In order to simulate large soft condensed systems for long times |
| 63 |
> |
within a reasonable amount of computational time, some new |
| 64 |
> |
coarse-grained models are presented in this dissertation to describe |
| 65 |
> |
phospholipids and liquid crystals. Although these |
| 66 |
> |
models can be described using a small number of physical parameters, |
| 67 |
> |
it is not trivial to introduce rigid constraints between different |
| 68 |
> |
molecular fragments correctly and efficiently. Working with |
| 69 |
> |
colleagues, I developed a new molecular dynamics framework capable |
| 70 |
> |
of performing simulation on systems with orientational degrees of |
| 71 |
> |
freedom in a variety of ensembles. Using this new package, I studied |
| 72 |
> |
the structure, dynamics and transport properties of the biological |
| 73 |
> |
membranes as well as the the phase behavior of liquid |
| 74 |
> |
crystals. A new Langevin dynamics algorithm for arbitrary rigid |
| 75 |
> |
particles is also presented to mimic solvent effects which may |
| 76 |
> |
eventually expand the time scale of the simulation. |
| 77 |
|
|
| 78 |
|
\end{abstract} |
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|
