Simulation and experimental study of InN nanoparticles synthesized by ion implantation technology.

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In order to synthesize InN nanoparticles (NPs), we have simulated the co-implantation of indium (In) and nitrogen (N) ions on silicon (Si) and silicon oxide (SiO2) substrates with flat-top profiles. The choice of flat-top profile is to increase the possibility of creating homogeneous zone with well-distributed InN nanoparticles over the entire implanted layer. In this view and to obtain these flat-top profiles, we must do several implantations with different doses and energies optimized by our program. The simulation results performed on a silicon substrate < 111 > , give an average dose of 4.30 × 1016 at./cm2 and the implantation energies were In (10, 46, and 180 keV) and N (13 and 35 keV). But for the SiO2 substrate, the total mean dose is about 5.20 × 1016at./cm2 for each Indium and nitrogen ion. The respective implantation energies were In (23, 63, and 120 keV) and N (12 and 28 keV) in an average depth of approximately 100 nm. The implantations were performed in a 206-nm-thick (SiO2) layer thermally grown on < 100 > silicon. Subsequent thermal treatments (500-900°C) lead to the formation of nanoparticles precipitates of the compound semiconductor (InN) and to cure the oxide defects during different periods of time. To verify that indium (In) and nitrogen (N) ions were located according to flat curves, we used RBS technical and study the formation (InN) stoichiometric compound several techniques, were used such as X-ray diffraction, UV-visible-IR, and photoluminescence (PL) spectroscopy. The simulated profiles have been chosen with the aim that the implanted element not exceeding 5-10 at %maximum concentration for each species. We have elaborated our program to simulate these profiles using data as input values from SRIM2008 code taking into account the sputtering factor. The optimal conditions are determined, which are the expected depth impact energies (Rp), the standard deviation (ΔRp) and the sputtering corrosion factor (Fs). Through these results, a simulation program has been created which allows building flat "distribution" curves for ion implantation for each element (In and N), so that each curve is obtained from three Gaussian functions whose values are carefully chosen in relation to the optimal experimental conditions.