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Abstract This thesis lies in three chapters; introduction, experimental work and results and discussion. It contains (120) pages, (74) figures and (1) table in addition to the appendix that includes the program codes. Chapter I (Introduction) The first chapter discusses the introduction and the development of the ceramic materials and Zinc oxide varistors, the models concerning the physics of the subject and shows a scientific presentation concerned with varistors (types, physical properties, role of dopants, features ,applications, and Manufacturing of ZnO-based varistors ) ceramic and its characteristics (chemical composition, microstructure and surface energy). Also it shows microstructure and effects of microstructural disorder of ZnO varistor doped with other metal oxides such as rare metals, rare earth metals and alkaline earth metals. Chapter II (Literature survey) The second chapter represents the literature survey and the history for the microstructure of ZnO doped with some oxides, shows real microstructure pictures for scanning electronic microscope (SEM), Illustrate effect of sintering, mole ratio of dopants, grain size and other factors affect microstructure. As well, characteristics of ZnO varistors in general and chemical composition of different ZnO varistor with different dopants are reported. Chapter III (Computer Modeling) The third chapter represents a computer simulation modeling program which lead us directly in future to predict the morphology and surface energy of zinc oxid varistors doped with several metal oxides. Firstly, calculating of ZnO parameters (number of bond, number of atoms in plane, surface area of SUMMERY plane, coordination number, NA and enthalpy of sublimation ΔHO) which used in calculating the surface energy and displaying real SEM image with their equivalent simulated SEM. These photos illustrate de-wetting in the binary systems and wetting in the ternary system can be interpreted in terms of the difference in the surface energy of metal oxide crystals for (microstructure) of some binary and ternary ZnO varistor systems. Estimating the surface energies of varistors have been obtained through measuring the surface energy of the doping oxides and assuming that the energetic of the ZnO is constant. However, since the surface energy of a varistor is closely related to the surface temperature and doping ions ratio. The program of the study will proceed according to the following three steps: 1. Calculation of the surface energy of the appeared phases in the ceramic, utilizing the chemical composition. 2. The surface energy for ZnO doped with several metal oxides like TiO2, Y2O3, MgO, V2O5, BaO, MnO2, MoO3, CuO, LiO2, Al2O3, SiO2, Bi2O3, Pr2O3 have been calculated. If ZnO surface energy higher than surface energy of doping oxide, the dopant should coated ZnO surface, but when surface energy of ZnO lower than surface energy of doping oxide, the dopant made phase between grains of ZnO oxide. 3. Correlation of the microstructure and the obtained values of the surface energy at different cleavage plains. 4. Computer simulation for the microstructure of ZnO varistor systems. In which, the surface energies for zinc oxide (ZnO) surfaces doped with some metal oxides like Y2O3, MgO,V2O5, BaO, MnO2, MoO3,CuO, LiO2, Al2O3, SiO2, Bi2O3, Pr2O3 and Gd2O3 have been calculated by using a simulation modeling program. This was demonstrated by a direct comparison between the computed values and images which obtained from scanning electronic SUMMERY microscope (SEM) for many doping oxides. To this end, a simulation modeling via Matlab program has been built up. In which, draw factional image for ZnO microstructure doped with some oxides side by side with real images for these oxides with different doping ratio. Our findings indicate that this simulation modeling program will lead us directly in future to predict the morphology of the metal oxides, calculating its related parameters like the surface energy and displacing real SEM image with their equivalent simulated SEM. MATLAB helps you take your ideas beyond the desktop. You can run your analyses on larger data sets and scale up to clusters and clouds. MATLAB code can be integrated with other languages, enabling you to deploy algorithms and applications within web, enterprise, and production systems. |