Mesoscale/mesoscopic methods

Mesoscopic methods include several field-based approaches such as cell dynamical systems (CDS), mesoscale density functional theory (DFT), and self-consistent field (SCF)" theory. Most of these methods are related to the time-dependent Ginzburg-Landau equation (TDGL) ... 

A problem area that is not so amenable to mesoscale methods is polymer crystallization. This has proven to be one of the most difficult computational challenges in all of polymer science because the pertinent phenomena operate simultaneously over a wide range of length scales. The pol5uner crystallizes into a particular space group because of atomic detail, and the mechanical properties of the crystallites are determined by, and can only be calculated reliably with, atomic force fields with all atoms represented (126,127). Yet the size of the crystallites or spherulites is so large as to require mesoscopic methods for comprehension. But a crystalline polymer is almost never 100% crystalline. The interphases between crystalline and amorphous domains, with the possibilities for adjacent or nonadjacent reentry and tie-chain distributions, are critical to the properties of semicrystalline polymers. Only recently have models been developed (203) to rigorously address this problem area. 

A comparison of mesoscopic simulation methods with MD simulations has been performed by Denniston and Robbins.423 They study a binary mixture of simple Lennard-Jones fluids and map out the required parameters of the mesoscopic model from their MD simulation data. Their mapping scheme is more complete than those of previous workers because in addition to accounting for the interfacial order parameter and density profiles, they also consider the stress. Their mapping consists of using MD simulations to parameterise the popular mesoscale Lattice Boltzmann simulation technique and find that a... 

The off-grid particle methods, such as DPD and FPM, can capture easily mesoscopic scales of hundreds of micrometers employing up to 10 fluid particles currently, i.e., the scales in which temperature fluctuations and depletion forces interact with mesoscopic flows. Therefore, gridless particle methods can mimic the complex dynamics of fluid particles in the mesoscale more realistically than LEG. The FPMs also save computational time taken by molecular dynamics for calculating thermal noise. Instead, in DPD and FPM, we introduce the random Brownian force. 

This chapter is organized as follows. In section 1.1, we introduce our notation and present the details of the molecular and mesoscale simulations the expanded ensemble-density of states Monte Carlo method,and the evolution equation for the tensor order parameter [5]. The results of both approaches are presented and compared in section 1.2 for the cases of one or two nanoscopic colloids immersed in a confined liquid crystal. Here the emphasis is on the calculation of the effective interaction (i.e. potential of mean force) for the nanoparticles, and also in assessing the agreement between the defect structures found by the two approaches. In section 1.3 we apply the mesoscopic theory to a model LC-based sensor and analyze the domain coarsening process by monitoring the equal-time correlation function for the tensor order parameter, as a function of the concentration of adsorbed nanocolloids. We present our conclusions in Section 1.4. 

Molecular simulation techniques can obtain the microscopic information that cannot be detected by current experimental conditions, but the conventional simulation methods stiU have inherent limitations with special mesoscopic scales of various complex forces and complex structure. It is necessary to establish a new mesoscale method that considers the chemical reaction and transport to the larger system at the same time. The roughness and chemical properties of catalyst supporting interface have great influence on chemical and physical adsorption stability of clusters. The problem is that the system is too large for traditional simulation in nano-/micro-/mesoscale. We need a new mesoscale method to study the effect of interface roughness on physical/chemistry phenomena. 

By molecular modeling technique, we can obtain the microscopic information that could not be detected by current experimental methods. But conventional molecular simulation method still has inherent limitations for various complex forces and complex mesoscopic structures under special mesoscale. For example, quantum chemistry cannot calculate the systems containing a large number of atoms. We have to ignore the role of chemical... 

We are developing a general purpose method for mesoscale soft-condensed matter computer simulations, based on a functional Langevin approach for mesoscopic phase separation dynamics of complex polymer liquids. This project aims to consider topics of utmost importance in chemical engineering, such as chemical reactions, convection and flow effects, surfaces and boundaries, etc. 

At the mesoscopic scale, interactions between molecular components control the self-organization phenomena between molecular components that lead to random phase-segregation during fabrication of CLs [7]. Mesoscale simulations can describe the morphology of heterogeneous materials and rationalize their effective properties beyond length- and time-scale limitations of atomistic simulations. A recently introduced computational method allows evaluation of the key faetors during fabrication of CLs. These simulations rationalize structural... 

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