CdO films were deposited on substrates from glass, Silicon and Porous silicon by thermal chemical spray pyrolysis technique with different thicknesses (130 and 438.46) nm. Measurements of X-ray diffraction of CdO thin film proved that the structure of the Polycrystalline is cubic lattice, and its crystallite size is located within nano scale range where the perfect orientation is (200). The results show that the surface’s roughness and the root mean square increased with increasing the thickness of prepared films. The UV-Visible measurements show that the CdO films with different thicknesses possess an allowed direct transition with band gap (4) eV. AFM measurement revealed that the silicon porosity located in nano range. Cadmium oxide f

in this paper, the current work was devoted to the manufacture of TiO2 nanoparticles doped with manganese,  synthesis by the sol-gel technique using a dip-conting device, for their hydrophilic properties and photocatalytic activity, and the products were characterized by X-ray diffraction, scanning electron microscopy, and Uv-Visible absorption, and the results  XRD showed an  phase Anatase  ,  and the results of the SEM Explained the shape of the morphology of the samples after the doping process compared with pure TiO2, and the results of a shift in light absorption from ultraviolet rays to visible light were evident. The results showed that the thin films have a high wettability   under visible rays

Spin coating technique used to prepare ZnPc, CdS and ZnPc/CdS blend thin films, these films annealed at 423K for 1h, 2h and 3h. Optical behavior of these films were examined using UV-Vis. and PL. The absorption spectrum of ZnPc shows a decreasing in absorption with the increase of annealing time while CdS spectrum give a clearly absorption peak at~510 nm. Energy gap of ZnPc increases from 1.41 to 1.52 eV by increasing the annealing time. E_g of CdS decrease by increasing annealing time, from 2.3 eV to 2.2 eV. The intensities of the peaks obtained from PL spectra were strongly dependent on annealing time and confirmed the results obtained from UV-Vis. D.C. conductivity measurement showed that all the thin films have two differen

ZnIn2(Se1-xTex)4 (ZIST) chalcopyrite semiconductor thin films at various contents (x = 0.0, 0.2, and 0.4) are deposited on glass and p type silicon (111) substrate to produce heterojunction solar cell by using the thermal evaporation technique at RT where the thickness of 500 nm with a vacuum of 1×10-5 mbar and a deposited rates of 5.1 nm/s. This study focuses on how differing x content effect on the factors affecting the solar cell characteristics of ZIST thin film and n-ZIST/p-Si heterojunction. X-ray diffraction XRD investigation shows that this structure of ZIST film is polycrystalline and tetragonal, with (112) preferred orientation at 2θ ≈ 27.01. Moreover, atomic force microscopy AFM is studying the external morphology of

This paper proposes improving the structure of the neural controller based on the identification model for nonlinear systems. The goal of this work is to employ the structure of the Modified Elman Neural Network (MENN) model into the NARMA-L2 structure instead of Multi-Layer Perceptron (MLP) model in order to construct a new hybrid neural structure that can be used as an identifier model and a nonlinear controller for the SISO linear or nonlinear systems. Two learning algorithms are used to adjust the parameters weight of the hybrid neural structure with its serial-parallel configuration; the first one is supervised learning algorithm based Back Propagation Algorithm (BPA) and the second one is an intelligent algorithm n

A novel design and implementation of a cognitive methodology for the on-line auto-tuning robust PID controller in a real heating system is presented in this paper. The aim of the proposed work is to construct a cognitive control methodology that gives optimal control signal to the heating system, which achieve the following objectives: fast and precise search efficiency in finding the on- line optimal PID controller parameters in order to find the optimal output temperature response for the heating system. The cognitive methodology (CM) consists of three engines: breeding engine based Routh-Hurwitz criterion stability, search engine based particle
swarm optimization (PSO) and aggregation knowledge engine based cultural algorithm (CA)