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1 tim 2685 \chapter{\label{chapt:conclusion}CONCLUSION}
2 tim 2880
3     The primary goal of this research has been to develop and apply
4     computational methods to study the structure and dynamics of soft
5 tim 2909 condensed matters. As the underlying physical law behind molecular
6     modeling of soft condensed matter, statistical mechanical principles
7     used in this dissertation are briefly reviewed in
8 tim 2880 Chapt.~\ref{chapt:introduction}. Following that, an introduction to
9     molecular simulation techniques including newtonian dynamics and
10     Langevin dynamics was provided. Even though the motions of soft
11 tim 2909 condensed systems are characterized by different ODEs between
12 tim 2880 Newtonian dynamics and Langevin dynamics, they all preserve some
13 tim 2909 underlying geometric properties. These properties are built into a
14 tim 2880 geometric integration method, which gives the method remarkable
15     performance and stability, especially during long simulations. Thus,
16 tim 2909 the theory of geometric integration and the methods to construct
17 tim 2880 symplectic integrators are also covered in
18     Chapt.~\ref{chapt:introduction}, as well as the mathematics behind
19     the elegant symplectic integration scheme involving rigid body
20     dynamics.
21    
22     In Chapt.~\ref{chapt:methodology}, the basic methods used in this
23     work were discussed. An overview of the DLM method was given showing
24     that DLM distinguished itself by its accuracy and efficiency during
25 tim 2909 long time simulation. Following this, the DLM method was extended to
26 tim 2880 produce canonical ensemble and isobaric-isothermal ensemble, as well
27     as special ensembles like $NPAT$ ensemble and $NP\gamma T$ ensemble
28     to alleviate the anisotropic effect of biological membrane systems.
29     In order to study slow transport in membrane systems, a new method
30     to study diffusion by measuring the constraint force was proposed
31     and verified.
32    
33 tim 2909 Chapt.~\ref{chapt:lipid} provided a general background to transport
34     phenomena in biological membranes. Atomistic simulations were
35     applied to study the headgroup solvation for different
36     phospholipids. A simple but relatively accurate and efficient
37     coarse-grained model was developed to capture essential features of
38     the headgroup-solvent interactions. It was then shown that the
39     structural properties of the simulated membrane bilayers agreed well
40     with experimental data. Further studies combining an external force
41     dragging method and z-constraint method may provide insights into
42     understanding of transport in large scale biological systems.
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44     The current status of experimental and theoretical approaches to
45     study phase transition in banana-shaped liquid crystal system was
46     first reviewed in Chapt.~\ref{chapt:liquidcrystal}. A new rigid body
47     model consisting of three identical Gay-Berne particles was then
48     proposed to represent the banana shaped liquid crystal. Starting
49     from an isotropic configuration, we successfully explored an unique
50     chevron structure. Calculations from various order parameters and
51     correlation functions also confirmed this discovery.
52    
53     Lastly, Chapt.~\ref{chapt:langevin} summarized the applications of
54     Langevin dynamics and the development of Brownian dynamics. By
55     embedding hydrodynamic properties into the sophisticated rigid body
56 tim 2909 dynamics algorithms, we developed a new Langevin dynamics for
57 tim 2880 translation-rotation couplings systems. Molecular simulations with
58     different viscosities demonstrated the temperature control ability
59 tim 2909 of this new algorithm. It was also shown that the dynamics was
60     preserved using this implicit solvent model in studying mixed
61     systems of banana shaped molecules and pentane molecules.
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63     Overall, this work has shown the successful application of
64 tim 2909 statistical mechanics to study structure, dynamics and phase
65     behavior of soft condensed materials. Beginning by developing coarse
66 tim 2880 grained models that could reproduce experimental observations, we
67     have extended molecular simulations to study self-assembly in soft
68     condensed systems. Finally, we have developed a new Langevin
69     dynamics algorithm for arbitrary rigid particles which can be used
70     as an implicit solvent model to explore slow processes in soft
71 tim 2909 condensed systems.