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Method for long time scale simulations of solids: Application to crystal growth and dopant clustering

Description: An important challenge in theoretical chemistry is the time scale problem. Atomic motion can be simulated directly by integrating Newton's equations over a time scale of nanoseconds, but most interesting chemical reactions take place on a time scale of seconds. We have developed a methodology to bridge this time scale gap using harmonic transition state theory suitable for solid systems. Possible reactive events and their rates are found with a saddle point finding method called the dimer method. When enough events are found, a kinetic Monte Carlo algorithm is used to choose which event occurs so that the system's position can be advanced in time. This technique has two major advantages over traditional kinetic Monte Carlo -- atoms do not have to map onto lattice sites for classification and kinetic events can be arbitrarily complicated. We have studied the homoepitaxial growth of aluminum and copper using an EAM potential at 80K with experimentally relevant deposition rates of monolayers per minute using a multiple time scale approach. Atomic deposition events are simulated directly with classical dynamics for several picoseconds until the incident energy has dissipated, and the long time between deposition events is simulated with the adaptive kinetic Monte Carlo method. Our simulations indicate that the Al( 100) surface grows much smoother then Cu( 100) at temperature between 0 and 80K due in part to long range multi atom processes which enable aluminum atoms to easily descend from atop islands. The high rate of such processes is due to their low activation energy, which is supported by density functional theory calculations, and the trend that processes involving more atoms tend to have larger prefactors and be favored by entropy. The scheme is efficient enough to model the evolution of systems with ab-initio forces as well, for which I will show an ...
Date: January 1, 2002
Creator: Henkelman, G. A. (Graeme A.); Uberuaga, B. P. (Blas Pedro) & Jónsson, Hannes,
Partner: UNT Libraries Government Documents Department