Prasad Patnaik B S V

A stochastic cellular automata simulator capable of spatiotemporal modeling of the crystallization and amorphization behavior of phase-change materials during the complex annealing cycles used in optical and electrical memory applications is presented. This is based on consideration of bulk and surface energies to generate rates of growth and decay of crystallites built up from "monomers" that may themselves be quite complex molecules. The approach uses a stochastic Gillespie-type time-stepping algorithm to deal with events that may occur on a very wide range of time scales. The simulations are performed at molecular length scale and using an approximation of local free energy changes that depend only on immediate neighbors. The approach is potentially capable of spanning the length scales between ab initio atomistic modeling methods, such as density functional theory, and bulk-scale methods, such the Johnshon-Mehl-Avrami-Kolmogorov formalism. As an example the model is used to predict the crystallization behavior in the chalcogenide Ge2 Sb2 Te5 alloy commonly used in phase-change memory devices. The simulations include annealing cycles with nontrivial spatial and temporal variations in temperature, with good agreement to experimental incubation times at low temperatures while modeling nontrivial crystal size distributions and melting dynamics at higher temperatures. © 2008 American Institute of Physics.

Flow past an isolated circular cylinder and two cylinders in tandem is numerically simulated, under the influence of buoyancy aiding and opposing the flow. A modified velocity correction method is employed, which has second order accuracy in both space and time. The influence of buoyancy on the temporal fluid flow patterns is investigated, with respect to streamlines, isotherms and streaklines. Comparisons are made with respect to mean center line velocities, drag coefficients, Strouhal number and streakline patterns. Degeneration of naturally occurring Karman vortex street into a twin eddy pattern is noticed in the Reynolds number (Re) range of 41-200, under buoyancy aided convection. On the contrary, buoyancy opposed convection could trigger vortex shedding even at a low Re range of 20-40, where only twin eddies are found in the natural wake. Temporal evolution of unsteady eddy patterns is visualized by means of numerical particle release (NPR). Zones of vortex shedding and twin vortices are demarcated on a plot of Richardson number against Strouhal number. Root mean square (RMS) lift coefficients (CL,RMS) and average drag coefficient are obtained as a function of Richardson number (Ri).