Mesoscale dynamics

The conceptual forerunner to mesoscale dynamics is Brownian dynamics. Brownian simulations used equations of motion modified by a random force... 

The meso- and micro-scale synoptic systems which form rainstorm occur and develop along the large-scale circumfluence. The post studies were mainly describing the large-scale and meso-scale systems (Tao et al., 1998). Therefore, it is still difficult to explain the heavy rain event with meso-P scale weather systems with the existing mesoscale dynamical theories. 

Mesoscale simulations model a material as a collection of units, called beads. Each bead might represent a substructure, molecule, monomer, micelle, micro-crystalline domain, solid particle, or an arbitrary region of a fluid. Multiple beads might be connected, typically by a harmonic potential, in order to model a polymer. A simulation is then conducted in which there is an interaction potential between beads and sometimes dynamical equations of motion. This is very hard to do with extremely large molecular dynamics calculations because they would have to be very accurate to correctly reflect the small free energy differences between microstates. There are algorithms for determining an appropriate bead size from molecular dynamics and Monte Carlo simulations. 

Many of the mesoscale techniques have grown out of the polymer SCF mean field computation of microphase diagrams. Mesoscale calculations are able to predict microscopic features such as the formation of capsules, rods, droplets, mazes, cells, coils, shells, rod clusters, and droplet clusters. With enough work, an entire phase diagram can be mapped out. In order to predict these features, the simulation must incorporate shape, dynamics, shear, and interactions between beads. 

Dissipative particle dynamics (DPD) is a technique for simulating the motion of mesoscale beads. The technique is superficially similar to a Brownian dynamics simulation in that it incorporates equations of motion, a dissipative (random) force, and a viscous drag between moving beads. However, the simulation uses a modified velocity Verlet algorithm to ensure that total momentum and force symmetries are conserved. This results in a simulation that obeys the Navier-Stokes equations and can thus predict flow. In order to set up these equations, there must be parameters to describe the interaction between beads, dissipative force, and drag. 

DPD (dissipative particle dynamics) a mesoscale algorithm DREIDING a molecular mechanics force field... 

Underlying all continuum and mesoscale descriptions of shock-wave compression of solids is the microscale. Physical processes on the microscale control observed dynamic material behavior in subtle ways sometimes in ways that do not fit nicely with simple preconceived macroscale ideas. The repeated cycle of experiment and theory slowly reveals the micromechanical nature of the shock-compression process. 

Chemical engineers of the future will be integrating a wider range of scales than at r other branch of engineering. For example, some may work to relate the macroscale of the environment to the mesoscale of combustion systems and the microscale of molecular reactions and transport (see Chapter 7). Others may work to relate the macroscale performance of a composite aircraft to the mesoscale chemical reactor in which the wing was formed, the design of the reactor perhaps having been influenced by studies of the microscale dynamics of complex liquids (see Chapter 5). 

The linkage of microscopic and macroscopic properties is not without challenges, both theoretical and experimental. Statistical mechanics and thermodynamics provide the connection between molecular properties and the behavior of macroscopic matter. Coupled with statistical mechanics, computer simulation of the structure, properties, and dynamics of mesoscale models is now feasible and can handle the increase in length and time scales. 

MULTIPARTICLE COLLISION DYNAMICS SIMULATION OF COMPLEX SYSTEMS ON MESOSCALES... 

In studies of reactions in nanomaterials, biochemical reactions within the cell, and other systems with small length scales, it is necessary to deal with reactive dynamics on a mesoscale level that incorporates the effects of molecular fluctuations. In such systems mean field kinetic approaches may lose their validity. In this section we show how hybrid MPC-MD schemes can be generalized to treat chemical reactions. 

A. Malevanets and R. Kapral, Solute dynamics in a mesoscale solvent, J. Chem. Phys. 112,... 

An alternative mesoscale approach for high-level molecular modeling of hydrated ionomer membranes is coarse-grained molecular dynamics (CGMD) simulations. One should notice an important difference between CGMD and DPD techniques. CGMD is essentially a multiscale technique (parameters are directly extracted from classical atomistic MD) and it... 

MesoScale Discovery (MSD) succeeded in introducing product with a similar technology approach based upon ruthenium redox-mediated electrochemical detection (Figure 2.14). MSD is a joint venture of its parent company, MesoScale, and IGEN, a company that pioneered much of fhe work on electrochemical detechon based on the ruthenium redox system. MSD s Multi-Spot plates contain antibodies immobilized on multiple working electrode pads within each well, allowing each spot within the well to serve as an individual assay. Multiplexed cytokine immxmoassays can be performed in 96-well (4,7, or 10 spots per well) patterns with detection limits of 1 to 10 pg/mL and a linear dynamic range up to 3,000 pg/mL. Both 24-and 384-well electrode systems are available. 

Finally, it should be mentioned that a combination of COSMO-RS with tools such as MESODYN [127] or DPD [128] (dissipative particle dynamics) may lead to further progress in the area of the mesoscale modeling of inhomogeneous systems. Such tools are used in academia and industry in order to explore the complexity of the phase behavior of surfactant systems and amphiphilic block-co-polymers. In their coarse-grained 3D description of the long-chain molecules the tools require a thermodynamic kernel... 

Sewell and co workers [145-148] have performed molecular dynamics simulations using the HMX model developed by Smith and Bharadwaj [142] to predict thermophysical and mechanical properties of HMX for use in mesoscale simulations of HMX-containing plastic-bonded explosives. Since much of the information needed for the mesoscale models cannot readily be obtained through experimental measurement, Menikoff and Sewell [145] demonstrate how information on HMX generated through molecular dynamics simulation supplement the available experimental information to provide the necessary data for the mesoscale models. The information generated from molecular dynamics simulations of HMX using the Smith and Bharadwaj model [142] includes shear viscosity, self-diffusion [146] and thermal conductivity [147] of liquid HMX. Sewell et al. have also assessed the validity of the HMX flexible model proposed by Smith and Bharadwaj in molecular dynamics studies of HMX crystalline polymorphs. 

We think that judicious application of molecular simulation tools for the calculation of thermophysical and mechanical properties is a viable strategy for obtaining some of the information required as input to mesoscale equations of state. Given a validated potential-energy surface, simulations can serve as a complement to experimental data by extending intervals in pressure and temperature for which information is available. Furthermore, in many cases, simulations provide the only realistic means to obtain key properties e.g., for explosives that decompose upon melting, measurement of liquid-state properties is extremely difficult, if not impossible, due to extremely fast reaction rates, which nevertheless correspond to time scales that must be resolved in mesoscale simulations of explosive shock initiation. By contrast, molecular dynamics simulations can provide converged values for those properties on time scales below the chemical reaction induction times. Finally,... 

This chapter presents a review of the progress relating flammability measurements and properties deduced from microscale experiments of milligram size samples with measurements obtained from mesoscale experiments of sample size about 100 g. We present a comprehensive and integrated approach based on sound scientific method, yet practical for assessing the flammability of nanocomposite polymers in the early stage of their formulations where only milligram order quantities are available. Our approach does not extend to quantum chemistry or molecular dynamics to... 

The dynamic viscosity and storage modulus of the melt polymer can characterize (1) the degree of dispersity (i.e., intercalation) of the nanocomposite polymer [1,2], (2) the dripping tendency in mesoscale or large-scale fires [3,4], and (3) the structure of the char layer formed during pyrolysis in mesoscale or large-scale fires [5-7]. 

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