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The zinc oxide thin films, highly transparent, doped aluminium were prepared on glass substrates by the reactive chemical spray method. The incorporation nature of Al atoms in the ZnO lattice was determined by X-ray diffraction and optical analyses. Indeed, for low doping ⩽2%, the results of X-ray spectra analysis show a simultaneous reduction of lattice parameters (a and c), this variation, which follows VEGARD’s law, tends to indicate a substitution of Zn by Al. By against for doping >2% the increase in the lattice parameters thus the grain sizes, in accordance with the VEGARD’s law can be explained by occupation of the interstitial sites by Al atoms. Beyond 4%, the material tends to get disorderly and the crystallites orientation is random. The studied optical properties show that the variation of the optical gap follows a law of the x3/2 form for x

Purpose. In recent years, the photovoltaic systems (PV) become popular due to several advantages among the renewable energy. Tracking maximum power point in PV systems is an important task and represents a challenging issue to increase their efficiency. Many different maximum power point tracking (MPPT) control methods have been proposed to adjust the peak power output and improve the generating efficiency of the PV system connected to the grid. Methods. This paper presents a Beta technique based MPPT controller to effectively track maximum power under all weather conditions. The effectiveness of this algorithm based MPPT is supplemented by a comparative study with incremental conductance (INC), particle swarm optimization (PSO), and fuzzy logic control (FLC). Results Faster MPPT, lower computational burden, and higher efficiency are the key contributions of the Beta based MPPT technique than the other three techniques.

We propose the use of a pattern search optimization technique in combination with a seed preprocessing procedure to determine the optical constants and thickness of thin films using only the transmittance spectra. The approach is quite flexible, straightforward to implement, and efficient in reaching the best fitting. We demonstrate the effectiveness of the method in extracting optical constants, even when the films are not displaying interference fringes. Comparison to a real-coded genetic algorithm shows that the modified pattern search is fast, almost accurate, and does not need any parameter adjustments. The approach is successfully applied to extract the thickness and optical constants of spray pyrolyzed nanocrystalline CdO thin films.