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Article title MONTE CARLO SIMULATION OF ARSENIC TETRAMER FLUX EFFECT ON GAAS/GAAS(001) EPITAXIAL GROWTH
Authors S.V. Balakirev, M.M. Eremenko, M.S. Solodovnik
Section SECTION III. NANOMATERIALS
Month, Year 09, 2015 @en
Index UDC 621.793.14
DOI
Abstract The model of GaAs/GaAs(001) molecular beam epitaxial growth considering arsenic tetramer flux influence on geometrical characteristics of nucleating island arrays is presented in the paper. The simulation is carried out with a kinetic Monte Carlo method and takes into account the surface specifics, multicomponent composition of the growing film and adatom local environment. Due to the large mobility of arsenic on the surface, arsenic molecule diffusion step was taken equal to its average diffusion length. It made it possible to accelerate computations essentially without significant corruption of the simulation results. It is shown that islands are preferentially forme in the trenches of (2x4)-reconstructe surface of GaAs(001) an favor elongation along the [110] direction. The island density increases with the surface coverage increase and reaches a saturation value. The increase of arsenic flux from 3·1014 до 4·1015 cm-2s-1 leads to the increase of the island density from 3,1·1012 to 4,6·1012 cm-2 at the coverage equal to 0,2 monolayer of GaAs. At the same time the average size decreases from 3,6 to 2,5 nm. The influence of arsenic flux on the average island size is growing with the surface coverage increase. The island size distribution function shows that the island characteristics are affected by arsenic flux more significantly in the range of large values. This is attributed to the shortage of gallium atoms in comparison with deposited arsenic molecules that prevents large island formation and leads to the dramatic growth of little island concentration. The simulation results are in good agreement with experimental data.

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Keywords Nanotechnology; nanostructures; nanomaterials; semiconductors; molecular beam epitaxy; gallium arsenide; arsenic flux; kinetic modeling; Monte Carlo method.
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