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Revision 2906 by tim, Wed Jun 28 17:36:32 2006 UTC vs.
Revision 2907 by tim, Thu Jun 29 16:57:37 2006 UTC

# Line 36 | Line 36
36   \renewcommand{\lstlistingname}{Scheme}
37   \frontmatter
38   \work{Dissertation}  % Change to ``Thesis'' for Master's thesis
39 < \title{MOLECULAR DYNAMICS SIMULATIONS OF PHOSPHOLIPID BILAYERS AND LIQUID CRYSTALS}
39 > \title{MOLECULAR DYNAMICS METHODOLOGY AND SIMULATIONS OF PHOSPHOLIPID BILAYERS AND LIQUID CRYSTALS}
40   \author{Teng Lin}
41   \degprior{B.S., B.E.}                 % All previously earned degrees
42   \degaward{Doctor of Philosophy}  % What this paper is for
# Line 47 | Line 47 | As an rapidly expanding interdisciplinary of physics,
47   %% \copypage              % Uncomment if you want a copyright page
48   \begin{abstract}
49  
50 < As an rapidly expanding interdisciplinary of physics, chemistry and
51 < biology \emph{etc}, soft condensed matter science studies the
52 < kinetics, dynamics and geometric structures of complex materials
53 < like membrane, liquid crystal and polymers \emph{etc}. These soft
54 < condensed matters are distinguished by the unique physical
55 < properties on the mesoscopic scale which can provide useful insights
56 < to understand the basic physical principles linking the microscopic
57 < structure to the macroscopic properties. Knowledge of the underlying
58 < physics is of benefit to a wide range of applications areas, such as
59 < the processing of biocompatible materials and development of LCD
60 < display technologies. Although the separation of the length scale
61 < allows statistical mechanics to be applied, the interesting behavior
62 < of these systems usually happens on the time scale well beyond the
63 < current computing power. In order to simulate large soft condensed
64 < systems for long times within a reasonable amount of computational
65 < time, some new coarse-grained models were proposed in this
66 < dissertation to describe phospholipids and banana-shaped liquid
67 < crystals. Although these models can be described using a small
68 < number of physical parameter, it is not trivial to maintain the
69 < introducing rigid constraints between different molecular fragments
70 < correctly and efficiently. Working with colleagues, I developed a
71 < new molecular dynamics framework capable of performing simulation on
72 < systems with orientational degrees of freedom in a variety of
73 < ensembles. Using this new package, I study the structure, the
74 < dynamics and transport properties of the biological membranes as
75 < well as the the phase behavior of banana shaped liquid crystal. A
76 < new Langevin dynamics algorithm for arbitrary rigid particles is
77 < proposed to mimic solvent effect which may eventually expand the
78 < time scale of the simulation.
50 > As a rapidly expanding interdisciplinary science bridging physics,
51 > chemistry and biology, the study of soft condensed matter involves
52 > the kinetics, dynamics and geometric structures of complex materials
53 > like membrane, liquid crystal and polymers. These soft condensed
54 > materials are distinguished by the unique physical properties on the
55 > mesoscopic scale which can provide useful insights to understand the
56 > basic physical principles linking the microscopic structure to the
57 > macroscopic properties. Knowledge of the underlying physics is of
58 > benefit to a wide range areas, such as the processing of
59 > biocompatible materials and development of LCD display technologies.
60 > Although the separation of the length scales allows statistical
61 > mechanics to be applied, the interesting behavior of these systems
62 > usually happens on time scale well beyond current computing power.
63 > In order to simulate large soft condensed systems for long times
64 > within a reasonable amount of computational time, some new
65 > coarse-grained models are presented in this dissertation to describe
66 > phospholipids and banana-shaped liquid crystals. Although these
67 > models can be described using a small number of physical parameters,
68 > it is not trivial to introduce rigid constraints between different
69 > molecular fragments correctly and efficiently. Working with
70 > colleagues, I developed a new molecular dynamics framework capable
71 > of performing simulation on systems with orientational degrees of
72 > freedom in a variety of ensembles. Using this new package, I studied
73 > the structure, the dynamics and transport properties of the
74 > biological membranes as well as the the phase behavior of banana
75 > shaped liquid crystals. A new Langevin dynamics algorithm for
76 > arbitrary rigid particles is proposed to mimic solvent effects which
77 > may eventually expand the time scale of the simulation.
78  
79   \end{abstract}
80  

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