(613a) Multi-Scale Simulation of Quantum Dot Formation in Metal Thin-Film Epitaxy

Homoepitaxial growth on fcc(110) surfaces is perhaps the simplest example of self-assembled nanostructures that form during thin-film epitaxy. In experimental studies of Al(110) and Cu(110) homoepitaxy, it is observed that over a certain temperature window, three-dimensional huts, with dimensions on the 20-30 nm scale, form and self-organize over the micron scale [1,2]. The factors leading to this kinetic self-organization are currently unclear.

To understand how these structures form and evolve, we simulated multi-layer, homoepitaxial growth on Al(110) and Ag(110) using ab initio kinetic Monte Carlo (KMC) simulations. In these simulations, we use the three-dimensional anisotropic bond-breaking model [3] to obtain the rates for atom diffusion. The energetic inputs to this model are obtained with first-principles, total-energy, density-functional theory calculations using VASP. At the high temperatures, where nano-huts form, the KMC simulations are slow because the diffusion of isolated adatoms is a very fast process. To tackle this problem, we developed a KMC method in which isolated adatoms are allowed to make multiple moves in one step. We achieve high efficiency with this algorithm and we are able to explore very high temperatures on large simulation lattices. We uncover a variety of interesting morphologies that depend on the growth temperature. In the low temperature regime we observe that, as the temperature increases, cross-channel <001> ripples, anisotropic mounds and in-channel <110> ripples form. These features are seen experimentally in studies of Ag(110) homoepitaxy [4]. Various dormant processes in the low temperature regime are activated at higher temperatures to form nano-huts up to 50 monolayers high, with well defined and smooth (111) and (100) facets. Such huts are seen experimentally in Al(110) homoepitaxy [1].

By varying the interaction energies and the barriers for various rate processes, we have discerned the factors that determine the hut sizes and aspect ratios, as well as hut self-organization. The insight gained in this study could be employed to achieve selective nano-structure assembly in other growth scenarios.

[1] F. Buatier de Mongeot, W. Zhu, A. Molle, R. Buzio, C. Boragno, U. Valbusa, E. Wang, and Z. Zhang, Phys. Rev. Lett. 91, 016102 (2003).

[2] K. Fichthorn and M. Scheffler, Nature 429, 617 (2004).

[3] A. Videcoq, F. Hontinfinde, R. Ferrando, Surface Science 515, 575-587 (2002).

[4] F. Buatier de Mongeot, G. Costantini, C. Boragno, U. Valbusa, Phys. Rev. Lett. 84, 2445 (2000).