(5cu) Multi-Scale Simulation of Self-Assembly in Al(110) Homoepitaxial Growth

Homoepitaxial growth on Al(110) exhibits nanoscale atomic self-assembly [1] due to an interplay between the thermodynamic interactions between atoms and the kinetics of atomic diffusion and deposition. After 30 ML deposition with a flux of 1 ML/min at 450 K, 3D hut-shaped nanostructures called ?nanohuts? were seen in AFM images, which self-organize over the micron scale. Nanohuts have smooth and well-defined (100) and (111) facets and reach heights of up to 50 nm. Morphology during homoepitaxial growth under other conditions and structural evolution of nanohuts during deposition are presently not clear. We conducted multi-scale simulation studies to understand, predict and control self-assembly in this system.

We obtained accurate physical details of atomic diffusion and interactions in this system using ab initio calculations. We studied the key adatom diffusion moves responsible for the self-assembly and obtained their energy barriers [2] using the climbing-image nudged elastic band method [3]. We found several new mechanisms for adatom diffusion and also refined the energy barriers for the known mechanisms [4]. The energy barriers for adatom diffusion are sensitive to the local environment due to atomic interactions at the initial and transition states. Under certain configurations of neighboring atoms, the energy barriers for some diffusion moves are significantly reduced compared to that of single atom moves. Thus, we found that atoms assist each other to achieve moves that are kinetically difficult for single atoms, and lead to interesting self-assemblies. To accurately describe high-order many-body atomic interactions at surfaces, we developed the Connector Model [5] which can predict interactions at the initial states with accuracy close to ab initio calculations. We found that the connector model is more accurate and efficient in describing many-body interactions on Al(110) and Al(100) compared to the traditional lattice-gas approach [5,6].

The insights gained at the nanometer and pico-seconds scale were incorporated in a 3D kinetic Monte Carlo (kMC) model to extend the simulations to close to micron and minutes scale. Using our 3D kMC model, we simulated self-assembly under different deposition conditions in Al(110) homoepitaxial growth by modifying deposition flux and temperatures [7]. Further, we proposed innovative approaches to achieve the desired shapes and spatial distributions of nanostructures.

[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] Y. Tiwary and K. A. Fichthorn, to be published.

[3] G. Henkelman, B.P. Uberuaga, and H. Jonsson, J. Chem. Phys. 113, 9901 (2000).

[4] W. Zhu, F. Buatier de Mongeot, U. Valbusa, E. G. Wang, and Z. Y. Zhang, Phys. Rev. Lett. 92, 106102 (2004).

[5] Y. Tiwary and K. A. Fichthorn, Phys. Rev. B 78, 205418 (2008).

[6] Y. Tiwary and K. A. Fichthorn, Phys. Rev. B 75, 235451 (2007).

[7] Y. Tiwary and K. A. Fichthorn, to be published.