Solid molecular dynamics

Eds Ciccotti G., Frenkel D., McDonald I. R.) Simulation of Liquids and Solids Molecular Dynamics and Monte Carlo Methods in Statistical Mechanics (North-Holland Physics Publishing, Amsterdam) (1987). 

Molecular Simulations Molecular simulations are useful for predicting properties of bulk fluids and solids. Molecular dynamics (MD) simulations solve Newton s equations of motion for a small number (on the order of 10 ) of molecules to obtain the time evolution of the system. MD methods can be used for equilibrium and transport properties. Monte Carlo (MC) simulations use a model for the potential energy between molecules to simulate configurations of the molecules in proportion to their probability of occurrence. Statistical averages of MC configurations are useful for equilibrium properties, particularly for saturated densities, vapor pressures, etc. Property estimations using molecular simulation techniques are not illustrated in the remainder of this section as commercial software implementations are not generally available at this time. 

Molecular dynamics calculations have been made on atomic crystals using a Lennard-Jones potential. These have to be done near the melting point in order for the iterations not to be too lengthy and have yielded density functioi). as one passes through the solid-vapor interface (see Ref. 45). The calculations showed considerable mobility in the surface region, amounting to the presence of a... 

Molecular dynamics and density functional theory studies (see Section IX-2) of the Lennard-Jones 6-12 system determine the interfacial tension for the solid-liquid and solid-vapor interfaces [47-49]. The dimensionless interfacial tension ya /kT, where a is the Lennard-Jones molecular size, increases from about 0.83 for the solid-liquid interface to 2.38 for the solid-vapor at the triple point [49], reflecting the large energy associated with a solid-vapor interface. 

Molecular graphics representation ofihe paths generated by 32 hard spherical particles in the solid (left) and ht) phase. (Reproduced from Alder B J and T E Wainwright 1959. Studies in Molecular Dynamics. I. Method. Journal of Chemical Physics. 31. 459-466.)... 

In this chapter we shall consider four important problems in molecular n iudelling. First, v discuss the problem of calculating free energies. We then consider continuum solve models, which enable the effects of the solvent to be incorporated into a calculation witho requiring the solvent molecules to be represented explicitly. Third, we shall consider the simi lation of chemical reactions, including the important technique of ab initio molecular dynamic Finally, we consider how to study the nature of defects in solid-state materials. 

Catlow C R A1994. Molecular Dynamics Studies of Defects in Solids. In NATO ASI Series C 418 (Defects and Disorder in Crystalline and Amorphous Solids), pp. 357-373. 

In Chapter 2, a brief discussion of statistical mechanics was presented. Statistical mechanics provides, in theory, a means for determining physical properties that are associated with not one molecule at one geometry, but rather, a macroscopic sample of the bulk liquid, solid, and so on. This is the net result of the properties of many molecules in many conformations, energy states, and the like. In practice, the difficult part of this process is not the statistical mechanics, but obtaining all the information about possible energy levels, conformations, and so on. Molecular dynamics (MD) and Monte Carlo (MC) simulations are two methods for obtaining this information... 

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. 

Molecular mechanics methods have been used particularly for simulating surface-liquid interactions. Molecular mechanics calculations are called effective potential function calculations in the solid-state literature. Monte Carlo methods are useful for determining what orientation the solvent will take near a surface. Molecular dynamics can be used to model surface reactions and adsorption if the force held is parameterized correctly. 

M. R. Philpott, J. N. Glosli. Molecular dynamics simulation of interfacial electrochemical processes electric double layer screening. In G. Jerkiewicz, M. P. Soriaga, K. Uosaki, A. Wieckowski, eds. Solid Liquid Electrochemical Interfaces, Vol. 656 of ACS Symposium Series. Washington ACS, 1997, Chap. 2, pp. 13-30. 

These apparent restrictions in size and length of simulation time of the fully quantum-mechanical methods or molecular-dynamics methods with continuous degrees of freedom in real space are the basic reason why the direct simulation of lattice models of the Ising type or of solid-on-solid type is still the most popular technique to simulate crystal growth processes. Consequently, a substantial part of this article will deal with scientific problems on those time and length scales which are simultaneously accessible by the experimental STM methods on one hand and by Monte Carlo lattice simulations on the other hand. Even these methods, however, are too microscopic to incorporate the boundary conditions from the laboratory set-up into the models in a reahstic way. Therefore one uses phenomenological models of the phase-field or sharp-interface type, and finally even finite-element methods, to treat the diffusion transport and hydrodynamic convections which control a reahstic crystal growth process from the melt on an industrial scale. 

In literature, some researchers regarded that the continuum mechanic ceases to be valid to describe the lubrication behavior when clearance decreases down to such a limit. Reasons cited for the inadequacy of continuum methods applied to the lubrication confined between two solid walls in relative motion are that the problem is so complex that any theoretical approach is doomed to failure, and that the film is so thin, being inherently of molecular scale, that modeling the material as a continuum ceases to be valid. Due to the molecular orientation, the lubricant has an underlying microstructure. They turned to molecular dynamic simulation for help, from which macroscopic flow equations are drawn. This is also validated through molecular dynamic simulation by Hu et al. [6,7] and Mark et al. [8]. To date, experimental research had "got a little too far forward on its skis however, theoretical approaches have not had such rosy prospects as the experimental ones have. Theoretical modeling of the lubrication features associated with TFL is then urgently necessary. 

Due to particles extrusion, crystal lattice deformation expands to the adjacent area, though the deformation strength reduces gradually (Figs. 10(a)-10(other hand, after impacting, the particle may retain to plow the surface for a short distance to exhaust the kinetic energy of the particle. As a result, parts of the free atoms break apart from the substrate and pile up as atom clusters before the particle. The observation is consistent with results of molecular dynamics simulation of the nanometric cutting of silicon [15] and collision of the nanoparticle with the solid surface [16]. 

Molecular dynamics simulation (MDS) is a powerful tool for the processing mechanism study of silicon surface fabrication. When a particle impacts with a solid surface, what will happen Depending on the interaction between cluster and surface, behaviors of the cluster fall into several categories including implantation [20,21], deposition [22,23], repulsion [24], and emission [25]. Owing to limitations of computer time, the cluster that can be simulated has a diameter of only a few nanometres with a small cohesive energy, which induces the cluster to fragment after collision. 

Fig. 7 Molecular dynamics calculations, open circles, for the velocity of the crystal-melt interface versus the temperature of the interface. The solid curve corresponds to eq. (1) and the dashed curve to eq. (3).

Keywords Co-assembly Functionalization Molecular dynamics Self-assembly Solid phase synthesis... 

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