Simulations system size

This section presents some of the simulation results obtained by simulating systems of sizes 4000, 6912, 10976, 16384 and 32000 atoms on the IBM-SP/2. The simulations were performed on 4, 8 and 16 processors, respectively. Although, the simulated system size and the number of processors can be scaled easily, this section does not show all results. 

Fig. 24a. Phase diagram of the asymmetric polymer mixture (A. = 2.0, NA = NB = N = 32, 4, = 0.5) in the plane of variables reduced temperature and relative concentration 4a/(4a + 4b) of component A. The dashed lines are the histogram extrapolations for three simulated system sizes, the full line denotes the binodal, and the circle denotes the critical point. From Deutsch and Binder [93]. b Phase diagram of asymmetric polymer mixtures for NA = NB = N = 32, 4 = 0.5 in the (T, Ap) plane. Three choices of the asymmetry parameter A are shown as indicated. The first order transitions are shown as a full line, the critical points as circles. Temperature is normalized such that in the Flory-Huggins-approximation the critical temperature would occur for the same abscissa value. From Deutsch [266]...

Gray C G, Sainger Y S, Joslin C G, Cummings P T and Goldman S 1986 Computer simulation of dipolar fluids. Dependence of the dielectric constant on system size a comparative study of Ewald sum and reaction field approaches J. Chem. Phys. 85 1502-4... 

If the simulated system uses periodic boundary conditions, the logical long-range interaction includes a lattice sum over all particles with all their images. Apart from some obvious and resolvable corrections for self-energy and for image interaction between excluded pairs, the question has been raised if one really wishes to enhance the effect of the artificial boundary conditions by including lattice sums. The effect of the periodic conditions should at least be evaluated by simulation with different box sizes or by continuum corrections, if applicable (see below). 

Fig. 3. Average computation time for one step using EGO.VIII on a DEC-Alpha 3300L workstation (175 MHz) for simulation systems of varying size. The insets show some of the protein-water systems used for the benchmark simulations.

II. MOLECULAR DYNAMICS SIMULATIONS OF MEMBRANES A. System Size and Construction... 

Calculation of the energies and forces due to the long-range Coulomb interactions between charged atoms is a major problem in simulations of biological molecules (see Chapter 5). In an isolated system the number of these interactions is proportional to N-, where N is the number of charged atoms, and the evaluation of the electrostatic interactions quickly becomes intractable as the system size is increased. Moreover, when periodic... 

Rousseau, R.W. and Howell, T.R., 1982. Comparison of simulated crystal size distribution control systems based on nuclei density and super-saturation. Industrial and Engineering Chemistry Process Design and Development, 21, 606. 

FIG. 13 Phase diagram of a vector lattice model for a balanced ternary amphiphilic system in the temperature vs surfactant concentration plane. W -I- O denotes a region of coexistence between oil- and water-rich phases, D a disordered phase, Lj an ordered phase which consists of alternating oil, amphiphile, water, and again amphi-phile sheets, and L/r an incommensurate lamellar phase (not present in mean field calculations). The data points are based on simulations at various system sizes on an fee lattice. (From Matsen and Sullivan [182]. Copyright 1994 APS.)... 

The martensite - austenite transition temperatures we find are for all systems in accordance with the previously published ones . Some minor deviations can be attributed to the fact that we are simulating an overheated first order phase transition. Therefore, for our limited system sizes, one cannot expect a definite transition temperature. 

The question arises as to how useful atomistic models may be in predicting the phase behaviour of real liquid crystal molecules. There is some evidence that atomistic models may be quite promising in this respect. For instance, in constant pressure simulations of CCH5 [25, 26] stable nematic and isotropic phases are seen at the right temperatures, even though the simulations of up to 700 ps are too short to observe spontaneous formation of the nematic phase from the isotropic liquid. However, at the present time one must conclude that atomistic models can only be expected to provide qualitative data about individual systems rather than quantitative predictions of phase transition temperatures. Such predictions must await simulations on larger systems, where the system size dependency has been eliminated, and where constant... 

The rapid rise in computer speed over recent years has led to atom-based simulations of liquid crystals becoming an important new area of research. Molecular mechanics and Monte Carlo studies of isolated liquid crystal molecules are now routine. However, care must be taken to model properly the influence of a nematic mean field if information about molecular structure in a mesophase is required. The current state-of-the-art consists of studies of (in the order of) 100 molecules in the bulk, in contact with a surface, or in a bilayer in contact with a solvent. Current simulation times can extend to around 10 ns and are sufficient to observe the growth of mesophases from an isotropic liquid. The results from a number of studies look very promising, and a wealth of structural and dynamic data now exists for bulk phases, monolayers and bilayers. Continued development of force fields for liquid crystals will be particularly important in the next few years, and particular emphasis must be placed on the development of all-atom force fields that are able to reproduce liquid phase densities for small molecules. Without these it will be difficult to obtain accurate phase transition temperatures. It will also be necessary to extend atomistic models to several thousand molecules to remove major system size effects which are present in all current work. This will be greatly facilitated by modern parallel simulation methods that allow molecular dynamics simulations to be carried out in parallel on multi-processor systems [115]. 

---