Numerical Simulation of Downstream Kinetics of an Atmospheric Pressure Nitrogen Plasma Jet Using Laminar, Modified Laminar, and Turbulent Models

We present numerical simulation of the nitrogen atmospheric pressure plasma jet (APPJ) using three fluid models—namely, laminar model, modified laminar model, and turbulent (k-ε) model—coupled with gas-phase reaction kinetics. The spatial profiles of the light emission intensities, gas temperature, and NO density predicted by the turbulent model show a better agreement with the experimental observations, compared with laminar and modified laminar models. We have demonstrated that the turbulent model shows more oxygen entrainment, more mixing with the ambient air, and a lower axial velocity at the downstream. These allow the turbulent model to more precisely capture the APPJ characteristics than the laminar and modified laminar models do.     

Transient molecular dynamics simulations of viscosity for simple fluids

A transient molecular dynamics (TMD) method has been developed for simulation of fluid viscosity. In this method a sinusoidal velocity profile is instantaneously overlaid onto equilibrated molecular velocities, and the subsequent decay of that velocity profile is observed. The viscosity is obtained by matching in a least-squares sense the analytical solution of the corresponding momentum transport boundary-value problem to the simulated decay of the initial velocity profile. The method was benchmarked by comparing results obtained from the TMD method for a Lennard-Jones fluid with those previously obtained using equilibrium molecular dynamics (EMD) simulations. Two different constitutive models were used in the macroscopic equations to relate the shear rate to the stress. Results using a Newtonian fluid model agree with EMD results at moderate densities but exhibit an increasingly positive error with increasing density at high densities. With the initial velocity profiles used in this study, simulated transient velocities displayed clear viscoelastic behavior at dimensionless densities above 0.7. However, the use of a linear viscoelastic model reproduces the simulated transient velocity behavior well and removes the high-density bias observed in the results obtained under the assumption of Newtonian behavior. The viscosity values obtained using the viscoelastic model are in excellent agreement with the EMD results over virtually the entire fluid domain. For simplicity, the Newtonian fluid model can be used at lower densities and the viscoelastic model at higher densities; the two models give equivalent results at intermediate densities.     

CFD-PBM approach for the gas-liquid flow in a nanobubble generator with honeycomb structure

In recent years, nanobubble technologies have drawn great attention due to their wide applications in many fields of science and technology. From previous studies, a kind of honeycomb structure for high efficiency nanobubble generation has been proposed. In this paper, the numerical simulations of bubbly flow in the honeycomb structure were performed by using a computational fluid dynamics–population balance model (CFD-PBM) coupled model. The numerical model was based on the Eulerian multiphase model and the population balance model (PBM) was used to calculate the bubble size distribution. The bubble size distributions in the honeycomb structure under different work conditions were predicted. Two different drag force models (Schiller-Naumann model and Tomiyama model) and two different aggregation models (Luo model and turbulent aggregation model) were investigated. Both two drag models gave similar prediction of bubble number density distribution at the outlet. The results obtained from Luo model had better reflection of the trend of number density distribution. The turbulence dissipation rate ε can be used to evaluate the nanobubble generating ability. The water tank was not included in the CFD model in this work. The bubbles in the water tank should be studied in the future.     

Simulation of DNA electrophoresis in systems of large number of solvent particles by coarse-grained hybrid molecular dynamics approach

Simulation of DNA electrophoresis facilitates the design of DNA separation devices. Various methods have been explored for simulating DNA electrophoresis and other processes using implicit and explicit solvent models. Explicit solvent models are highly desired but their applications may be limited by high computing cost in simulating large number of solvent particles. In this work, a coarse-grained hybrid molecular dynamics (CGH-MD) approach was introduced for simulating DNA electrophoresis in explicit solvent of large number of solvent particles. CGH-MD was tested in the simulation of a polymer solution and computation of nonuniform charge distribution in a cylindrical nanotube, which shows good agreement with observations and those of more rigorous computational methods at a significantly lower computing cost than other explicit-solvent methods. CGH-MD was further applied to the simulation of DNA electrophoresis in a polymer solution and in a well-studied nanofluidic device. Simulation results are consistent with observations and reported simulation results, suggesting that CGH-MD is potentially useful for studying electrophoresis of macromolecules and assemblies in nanofluidic, microfluidic, and microstructure array systems that involve extremely large number of solvent particles, nonuniformly distributed electrostatic interactions, bound and sequestered water molecules.     

On the kinetics of the capillary imbibition of a simple fluid through a designed nanochannel using the molecular dynamics simulation approach

A molecular dynamics (MD) approach was employed to simulate the imbibition of a designed nanopore by a simple fluid (i.e., a Lennard-Jones (LJ) fluid). The length of imbibition as a function of time for various interactions between the LJ fluid and the pore wall was recorded for this system (i.e., the LJ fluid and the nanopore). By and large, the kinetics of imbibition was successfully described by the Lucas-Washburn (LW) equation, although deviation from it was observed in some cases. This lack of agreement is due to the neglect of the dynamic contact angle (DCA) in the LW equation. Two commonly used models (i.e., hydrodynamic and molecular-kinetic (MK) models) were thus employed to calculate the DCA. It is demonstrated that the MK model is able to justify the simulation results in which are not in good agreement with the simple LW equation. However, the hydrodynamic model is not capable of doing that. Further investigation of the MD simulation data revealed an interesting fact that there is a direct relationship between the wall-fluid interaction and the speed of the capillary imbibition. More evidence to support this claim is presented.     

Direct correlation functions of binary mixtures of hard Gaussian overlap molecules

We study the direct correlation function (DCF) of a classical fluid mixture of nonspherical molecules. The components of the mixture are two types of hard ellipsoidal molecules with different elongations, interacting through the hard Gaussian overlap (HGO) model. Two different approaches are used to calculate the DCFs of this fluid, and the results are compared. Here, the Pynn approximation [J. Chem. Phys. 60, 4579 (1974)] is extended to calculate the DCF of the binary mixtures of HGO molecules, then we use a formalism based on the weighted density functional theory introduced by Chamoux and Perera [J. Chem. Phys. 104, 1493 (1996)]. These results are fairly in agreement with each other. The pressure of this system is also calculated using the Fourier zero components of the DCF. The results are in agreement with the Monte Carlo molecular simulation.     

Group contribution methods for molecular mixtures. III. Solution of groups tested via computer simulation

In this paper computer simulation results for model molecular fluids are used to test ideas underlying group contribution methods. The focus of attention is on the extent to which group contributions in one fluid (or two) can be used to estimate properties in other mixtures. This study is based on group—group distribution functions that were introduced in the first paper in this series.We propose two versions of an approach to a ”solution of groups“: a one-fluid theory and a two-fluid theory. The one-fluid theory subdivides into two forms and both result in group contributions to the residual internal energy that are independent of composition. The strong form of the one-fluid theory fails in comparisons with simulation data, but the weak form reliably predicts residual internal energies at low temperatures and low-to-moderate densities. The two-fluid version of the theory is somewhat better at estimating residual and excess internal energies.     

Modeling molecular transport in slit pores

We examine the transport of methane in microporous carbon by performing equilibrium and nonequilibrium molecular dynamics simulations over a range of pore sizes, densities, and temperatures. We interpret these simulation results using two models of the transport process. At low densities, we consider a molecular flow model, in which intermolecular interactions are neglected, and find excellent agreement between transport diffusion coefficients determined from simulation, and those predicted by the model. Simulation results indicate that the model can be applied up to fluid densities of the order to 0.1-1 nm(-3). Above these densities, we consider a slip flow model, combining hydrodynamic theory with a slip condition at the solid-fluid interface. As the diffusion coefficient at low densities can be accurately determined by the molecular flow model, we also consider a model where the slip condition is supplied by the molecular flow model. We find that both density-dependent models provide a useful means of estimating the transport coefficient that compares well with simulation.     

Surface imprinted polymers for oil denitrification with the combination of computational simulation and multi‐template molecular imprinting

Multi‐template molecular imprinting technique was employed for the theoretical study about industrial oil denitrification. Prior to the preparation of multi‐template molecularly imprinted polymers (MT‐MIPs), density functional theory was used for simulating the imprinted pre‐assembly systems composed of template (aniline, indole, or 3‐methylinndole) and monomer [methacrylic acid, acrylamide (AM), and 4‐vinylpyridine]. MT‐MIPs were synthesized as surface MIPs simply and successively by seeded emulsion polymerization or two‐stage precipitation polymerization. The experimental results were consistent with the simulative results, which demonstrated that AM was more suitable monomer together. In addition, seeded emulsion polymerization synthesized MT‐MIPs with better performance compared with two‐stage precipitation polymerization. The adsorption kinetics and adsorption isotherm of MT‐MIP prepared with AM using seeded emulsion polymerization were fitted with different models. The fitting results indicated that pseudo‐second‐order kinetics model and Freundlich isotherm model were suitable for describing the adsorption process of AM seeded emulsion polymerization. This study will provide a certain guidance and theoretical basis for introducing the combination of multi‐template molecular imprinting technique and computational simulation into the field of industrial denitrification. Copyright © 2015 John Wiley & Sons, Ltd.     

Comparison of various implicit solvent models in molecular dynamics simulations of immunoglobulin G light chain dimer

The present study tests performance of different solvation models applied to molecular dynamics simulation of a large, dimeric protein molecule. Analytical Continuum Electrostatics (ACE) with two different parameter sets, older V98 and new V01, and Effective Energy Function (EEF) are employed in molecular dynamics simulation of immunoglobulin G (IgG) light chain dimer and variable domain of IgG light chain. Results are compared with explicit solvent and distance dependent dielectric constant (DDE) calculations. The overall analysis shows that the EEF method yields results comparable to explicit solvent simulations; however, the stability of simulations is lower. On the other hand, the ACE_V98 model does not seem to achieve the accuracy or stability expected in nanosecond timescale MD simulation for the studied systems. The ACE_V01 model greatly improves stability of the calculation; nonetheless, changes in radius of gyration and solvent accessible surface of the studied systems may indicate that the parameter set still needs to be improved if the method is supposed to be used for simulations of large, polymeric proteins. Additionally, electrostatic contribution to the solvation free energy calculated in the ACE model is compared with a numerical treatment of the dielectric continuum model. Wall clock time of all simulations is compared. It shows that EEF calculation is six times faster than corresponding ACE and 50 times faster than explicit solvent simulations.     

Multiscale coarse-graining of ionic liquids

A recently developed multiscale coarse-graining (MS-CG) approach for obtaining coarse-grained force fields from fully atomistic molecular dynamics simulation is applied to the challenging case of the EMIM+NO3- ionic liquid. The force-matching in the MS-CG methodology is accomplished with an explicit separation of bonded and nonbonded forces. While the nonbonded forces are adopted from this force-matching approach, the bonded forces are obtained from fitting the statistical configurational data from the atomistic simulations. The many-body electronic polarizability is also successfully broken into effective pair interactions. With a virial constraint fixing the system pressure, the MS-CG models rebuild satisfactory structural and thermodynamic properties for different temperatures. The MS-CG model developed from a modest atomistic simulation is therefore suitable for simulating much larger systems, because the coarse-grained models show significant time integration efficiency. This approach is expected to be general for coarse-graining other ionic liquids, as well as many other liquid-state systems. The limitations of the present coarse-graining procedure are also discussed.     

微孔中简单流体粘度的分子动力学模拟及关联模型

用分子动力学模拟计算了微孔介质中流体氩在不同温度、不同密度和不同孔径下的剪切粘度.并根据Chapman-Enskog关于硬球流体传递性质的理论以及Heyes的关于Lennard-Jones流体粘度的表达式,提出了两个描述微孔介质中流体粘度的模型,该模型可以计算微孔中流体氩在不同状态下的粘度值.通过与计算机模拟值的比较,证明这两个微孔流体粘度模型是可用的.     

Hybrid method coupling fluctuating hydrodynamics and molecular dynamics for the simulation of macromolecules

We present a hybrid computational method for simulating the dynamics of macromolecules in solution which couples a mesoscale solver for the fluctuating hydrodynamics (FH) equations with molecular dynamics to describe the macromolecule. The two models interact through a dissipative Stokesian term first introduced by Ahlrichs and Dunweg [J. Chem. Phys. 111, 8225 (1999)]. We show that our method correctly captures the static and dynamical properties of polymer chains as predicted by the Zimm model. In particular, we show that the static conformations are best described when the ratio sigma/b=0.6, where sigma is the Lennard-Jones length parameter and b is the monomer bond length. We also find that the decay of the Rouse modes' autocorrelation function is better described with an analytical correction suggested by Ahlrichs and Dunweg. Our FH solver permits us to treat the fluid equation of state and transport parameters as direct simulation parameters. The expected independence of the chain dynamics on various choices of fluid equation of state and bulk viscosity is recovered, while excellent agreement is found for the temperature and shear viscosity dependence of center of mass diffusion between simulation results and predictions of the Zimm model. We find that Zimm model approximations start to fail when the Schmidt number Sc < or approximately 30. Finally, we investigate the importance of fluid fluctuations and show that using the preaveraged approximation for the hydrodynamic tensor leads to around 3% error in the diffusion coefficient for a polymer chain when the fluid discretization size is greater than 50 A.     

Coarse-Grained Molecular Dynamics Study based on TorchMD

The coarse grained (CG) model implements the molecular dynamics simulation by simplifying atom properties and interaction between them. Despite losing certain detailed information, the CG model is still the first-thought option to study the large molecule in long time scale with less computing resource. The deep learning model mainly mimics the human studying process to handle the network input as the image to achieve a good classification and regression result. In this work, the TorchMD, a MD framework combining the CG model and deep learning model, is applied to study the protein folding process. In 3D collective variable (CV) space, the modified find density peaks algorithm is applied to cluster the conformations from the TorchMD CG simulation. The center conformation in different states is searched. And the boundary conformations between clusters are assigned. The string algorithm is applied to study the path between two states, which are compared with the end conformations from all atoms simulations. The result shows that the main phenomenon of protein folding with TorchMD CG model is the same as the all-atom simulations, but with a less simulating time scale. The workflow in this work provides another option to study the protein folding and other relative processes with the deep learning CG model.     

Validation of reduced mechanisms for nitrogen chemistry in numerical simulation of a turbulent non-premixed flame

In this paper, the formation of nitrogen pollutants in computational fluid dynamics simulation of turbulent non-premixed flame was modelled by coupling reduced nitrogen chemical reaction mechanisms with comprehensive combustion model.     

The extension of coordination number model by using the local composition theory: mixtures

The extension of a new coordination number model to mixture is presented in this work. Extended model agrees well with the Monte Carlo (MC) simulation results for square-well (SW) mixture fluids and shows better results compared with other models. To test our model, we compare the compressibility factors from various models for SW fluids at different λ values and for SW fluid mixtures at λ=1.5. Although our model is obtained by fitting simulation data at λ=1.5, it shows better results for the different λ values than other coordination number model. Compared with the compressibility factors of various binary mixtures of SW fluids calculated from other models, this model presents better results. Because our model considers the temperature dependency importantly by using the total site number, it predicts coordination number and compressibility factor well in the wide temperature range and enables one to derive an equation of state (EOS) through integration of the coordination number equation.     

The numerical simulation of the mechanical failure behavior of shear thickening fluid/fiber composites: A review

This study reveals the finite element modeling of mechanical failure behavior of shear thickening fluid (STF)/fiber composites under impact. Numerical analysis and finite element modeling of the rheological properties of non-Newtonian fluid, STF are introduced. This review summarizes the model coupling methods in finite element modeling and the mechanical failure behavior prediction models of STF/fiber composites under impact. Further, the influencing factors on the accuracy of mechanical failure simulation models are analyzed. Factors such as the friction between fibers, shear rate, filler particles in the fibers, hysteresis effect and the boundary conditions should be considered in simulating the shear thickening effect of the composites.