We propose a concurrently coupled hybrid molecular dynamics (MD) and kinetic Monte Carlo (KMC) algorithm to simulate the motion of grain boundaries between fcc and hcp islands during epitaxial growth on a fcc (111) surface. The method combines MD and KMC in an adaptive spatial domain decomposition, so that near the grain boundary, atoms are treated using MD but away from the boundary atoms are simulated by KMC. The method allows the grain boundary to interact with structures that form on spatial scales significantly larger than that of the MD domain but with a negligible increase in computational cost.
Transparent glass ceramic materials, with microstructures comprised of dispersed nanocrystallites in a residual glass matrix, offer the prospect of nonlinear optical properties. However, good transparency requires low optical scattering and low atomic absorption. The attenuation of light due to scattering (turbidity) will depend upon the difference in refractive index of the two phases and the size and distribution of crystals in the glass. Here, we model the glass ceramic as a late-stage phase-separated structure, and compute scattering in this model. We find that the turbidity follows a k8R7 relationship, where k is the wave vector of light in the glass ceramic and R is the average radius of the crystals in the glass.
We study the coalescence of nanoscale metal clusters in an inert-gas atmosphere using constant-energy molecular dynamics. The coalescence proceeds via atomic diffusion with the release of surface energy raising the temperature. If the temperature exceeds the melting point of the coalesced cluster, a molten droplet forms. If the temperature falls between the melting point of the larger cluster and those of the smaller clusters, a metastable molten droplet forms and freezes.
We present direct experimental evidence that water droplets can spontaneously penetrate non-wetting capillaries, driven by the action of Laplace pressure due to high droplet curvature. Using high-speed optical imaging, microcapillaries of radius 50 to 150 micron, and water microdroplets of average radius between 100 and 1900 micron, we demonstrate that there is a critical droplet radius below which water droplets can be taken up by hydrophobised glass and polytetrafluoroethylene (PTFE) capillaries. The rate of capillary uptake is shown to depend strongly on droplet size, with smaller droplets being absorbed more quickly. Droplet size is also shown to influence meniscus motion in a pre-filled non-wetting capillary, and quantitative measurements of this effect result in a derived water-PTFE static contact angle between 96 degrees and 114 degrees. Our measurements confirm recent theoretical predictions and simulations for metal nanodroplets penetrating carbon nanotubes (CNTs). The results are relevant to a wide range of technological applications, such as microfluidic devices, ink-jet printing, and the penetration of fluids in porous materials.
We explore changes in the electrical conductance of a percolating Bi nanocluster film due to coalescence. A power law increase in conductance is observed immediately after deposition and we show this corresponds to power law changes in the radius of the necks between clusters. The power-law exponent $(\ensuremath{\lesssim}0.04)$ is much smaller than expected from classical models of microparticle coalescence. Atomistic kinetic Monte Carlo simulations reveal similar behavior during a late stage of coalescence where faceting near the necks slows the effects of surface diffusion.
Zinc oxide is known to produce a wide variety of nanostructures that show promise for a number of applications. The use of electrochemical deposition techniques for growing ZnO nanostructures can allow tight control of the morphology of ZnO through the wide range of deposition parameters available. Here we model the growth of the rods under typical electrochemical conditions, using the Nernst-–Planck equations in two dimensions to predict the growth rate and morphology of the nanostructures as a function of time. Generally good quantitative and qualitative agreement is found between the model predictions and recent experimental results. doi:10.1017/S1446181109000157
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