Dissipative particle dynamics simulation method

However, the dissipative particle dynamics simulation technique trys to avoid the major drawback of the classical MD method which often provides far more detail of the small-scale fluctuational motion of atoms than is necessary for an understanding of many physical processes of surfactants. With DPD, the mesoscopic length and time regimes in complex fluids are accessible... 

The dissipative particle dynamics (DPD) method is a recent variation of the molecular dynamics technique. Here, in addition to Newtonian forces between hard particles, soft forces between particles are also introduced. These pairwise damping and noise forces model slower molecular motions. The dissipative forces also reduce the drift in kinetic energy that occurs in molecular dynamics simulations. These two reasons mean that DPD can be used to model longer time-scale processes, such as hydrodynamic flows or phase separation processes. 

A fiirther theme is the development of teclmiques to bridge the length and time scales between truly molecular-scale simulations and more coarse-grained descriptions. Typical examples are dissipative particle dynamics [226] and the lattice-Boltzmaim method [227]. Part of the motivation for this is the recognition that... 

During the past few decades, various theoretical models have been developed to explain the physical properties and to find key parameters for the prediction of the system behaviors. Recent technological trends focus toward integration of subsystem models in various scales, which entails examining the nanophysical properties, subsystem size, and scale-specified numerical analysis methods on system level performance. Multi-scale modeling components including quantum mechanical (i.e., density functional theory (DFT) and ab initio simulation), atom-istic/molecular (i.e., Monte Carlo (MC) and molecular dynamics (MD)), mesoscopic (i.e., dissipative particle dynamics (DPD) and lattice Boltzmann method (LBM)), and macroscopic (i.e., LBM, computational... 

Simulation techniques suitable for the description of phenomena at each length-scale are now relatively well established Monte Carlo (MC) and Molecular Dynamics (MD) methods at the molecular length-scale, various mesoscopic simulation methods such as Dissipative Particle Dynamics (Groot and Warren, 1997), Brownian Dynamics, or Lattice Boltzmann in the colloidal domain, Computational Fluid Dynamics at the continuum length-scale, and sequential-modular or equation-based methods at the unit operation/process-systems level. 

Molecular Dynamics simulation is one of many methods to study the macroscopic behavior of systems by following the evolution at the molecular scale. One way of categorizing these methods is by the degree of determinism used in generating molecular positions [134], On the scale from the completely stochastic method of Metropolis Monte Carlo to the pure deterministic method of Molecular Dynamics, we find a multitude and increasingly diverse number of methods to name just a few examples Force-Biased Monte Carlo, Brownian Dynamics, General Langevin Dynamics [135], Dissipative Particle Dynamics [136,137], Colli-sional Dynamics [138] and Reduced Variable Molecular Dynamics [139]. 

Computer simulations in the mesoscopic regime are now possible using methods such as Lattice Bolztmann, Dissipative Particle Dynamics, MesoDyn and Cell Dynamics Simulations. MesoDyn is a commercial package (from... 

Dissipative Particle Dynamics (DPD) is a coarse graining method that groups several atoms into simulation sites whose dynamics is governed by conservative and frictional forces designed to reproduce thermodynamics and hydrodynamics [132,133]. Since the effective interactions are constmcted to reproduce macroscopic properties soft repulsive forces can be used, thereby avoiding the small MD step sizes needed to integrate the system when full interactions are taken into account. In addition, random... 

The molecular dynamics methods that we have discussed in this chapter, and the examples that have been used to illustrate them, fall into the category of atomistic simulations, in that all of the actual atoms (or at least the non-hydrogen atoms) in the core system are represented explicitly. Atomistic simulations can provide very detailed information about the behaviour of the system, but as we have discussed this typically limits a simulation to the nanosecond timescale. Many processes of interest occur over a longer timescale. In the case of processes which occur on a macroscopic timescale (i.e. of the order of seconds) then rather simple models may often be applicable. Between these two extremes are phenomena that occur on an intermediate scale (of the order of microseconds). This is the realm of the mesoscale Dissipative particle dynamics (DPD) is particularly useful in this region, examples include complex fluids such as surfactants and polymer melts. 

ScWijper, A., Hoogetbragge, R, Manke, C. Computer simulation of dilute polymer solutions with the dissipative particle dynamics method. J. Rheol. 39, 567 (1995). doi 10.1122/1. 550713... 

Carmesin, I. and Kremer, K. The bond fluctuation method a new effective algorithm for the dynamics of polymers in all spatial dimensions. Macromolecules, 21,2819-23 (1988). Hoogerbrugge, P. J. and Koelman, J. M. V. A. Simulating microscopic hydrodynamic phenomena with dissipative particle dynamics. Europhys Lett., 19,155-60 (1992). 

Gibson, J. B., Chen, K., and Chynoweth, S. Simulation of particle adsorption onto a polymer-coated surface using the dissipative particle dynamics method. J Colloid Interface 5cz., 206,464-74 (1998). 

The theoretical methods to investigate the evolution kinetics of ordered microdomain structures are those in the atomic-scale including molecular dynamics simulations, Monte Carlo simulations, dynamic SCFT, dynamic density functional theory (DDFT), and those in the meso-scale including dissipative particle dynamics (DPD) simulations, etc. More details of these approaches can be found in the literatures. 

In Equation 7.2, pt +i represents the probability of the system changing from current configuration i to a new configuration i + 1, AE the change in potential energy associated with the attempted move, the Boltzmann constant, and T the temperature of the system. MC simulations are often performed in NVT and pVT ensembles, and widely applied to polymers as well as polymers in contact with filler particles. Brownian dynamics (BD) and dissipative particle dynamics (DPD) are further particle-based coarse-grained simulation methods similar to MD simulation. BD employs a continuum solvent model rather than explicit solvent molecules in MD and the total force is ... 

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