Monolithic integration of a half bridge on the same GaN-on-Si wafer is very challenging because the devices share a common conductive Si substrate. In this letter, we propose to use GaN-on-SOI (siliconon-insulator) to isolate the devices by trench etching through the GaN/Si(111) layers and stopping in the SiO 2 buried layer. By well-controlled epitaxy and device fabrication, high-performance 200 V enhancement-mode (e-mode) p-GaN high electron mobility transistors with a gate width of 36 mm are achieved. This letter demonstrates that by using GaN-on-SOI in combination with trench isolation, it is very promising to monolithically integrate GaN power systems on the same wafer to reduce the parasitic inductance and die size.
InN films were grown by metal-organic vapour phase epitaxy (MOVPE). The growth was performed in a MOVPE apparatus with a vertical reactor geometry optimized for the growth of GaN. The reactor geometry is found to cause enhanced cracking of NH 3 , and the growth rate is limited by the amount of reactive indium in the temperature range of 550-650 1C. The grown films are characterized comprehensively. Experimental results indicate that the InN films, grown on sapphire substrates, contain metallic indium and the film surface consist of hexagonal islands. Growth temperature has a strong effect on the surface island size, optical quality and electrical properties of the InN layer. The desorption of nitrogen is assumed to cause the formation of metallic indium above 550 1C. r
Transformation of self-assembled InAs quantum dots (QDs) on InP(100) into quantum rings (QRs) is studied. In contrast to the typical approach to III--V semiconductor QR growth, the QDs are not capped to form rings. Atomic force micrographs reveal a drastic change from InAs QDs into rings after a growth interruption in tertiarybutylphosphine ambient. Strain energy relief in the InAs QD is discussed and a mechanism for dot-to-ring transformation by As/P exchange reactions is proposed.
A novel genetic algorithm (GA) utilizing independent component analysis (ICA) was developed for x-ray reflectivity (XRR) curve fitting. EFICA was used to reduce mutual information, or interparameter dependences, during the combinatorial phase. The performance of the new algorithm was studied by fitting trial XRR curves to target curves which were computed using realistic multilayer models. The median convergence properties of conventional GA, GA using principal component analysis and the novel GA were compared. GA using ICA was found to outperform the other methods with problems having 41 parameters or more to be fitted without additional XRR curve calculations. The computational complexity of the conventional methods was linear but the novel method had a quadratic computational complexity due to the applied ICA method which sets a practical limit for the dimensionality of the problem to be solved. However, the novel algorithm had the best capability to extend the fitting analysis based on Parratt's formalism to multiperiodic layer structures.
IIIPublication III J. Tiilikainen, V. Bosund, M. Mattila, T. Hakkarainen, J. Sormunen and H. Lipsanen, Fitness function and nonunique solutions in x-ray reflectivity curve fitting: Crosserror between surface roughness and mass density,
AbstractNonunique solutions of the x-ray reflectivity (XRR) curve fitting problem were studied by modelling layer structures with neural networks and designing a fitness function to handle the nonidealities of measurements. Modelled atomic-layer-deposited aluminium oxide film structures were used in the simulations to calculate XRR curves based on Parratt's formalism. This approach reduced the dimensionality of the parameter space and allowed the use of fitness landscapes in the study of nonunique solutions. Fitness landscapes, where the height in a map represents the fitness value as a function of the process parameters, revealed tracks where the local fitness optima lie. The tracks were projected on the physical parameter space thus allowing the construction of the crosserror equation between weakly determined parameters, i.e. between the mass density and the surface roughness of a layer. The equation gives the minimum error for the other parameters which is a consequence of the nonuniqueness of the solution if noise is present. Furthermore, the existence of a possible unique solution in a certain parameter range was found to be dependent on the layer thickness and the signal-to-noise ratio.
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