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    Solid phase epitaxial thickening of boron and phosphorus doped polycrystalline silicon thin films formed by aluminium induced crystallization technique on glass substrate
    (Elsevier Science Sa, 2019) Özmen, Özge Tüzün; Karaman, Mehmet; Sedani, Salar Habibpur; Sagban, H. Muzaffer; Turan, Raşit
    Aluminium induced crystallization (AIC) technique can be used to form the high-quality and large-grained polycrystalline silicon (poly-Si) thin films, which are with the thickness of similar to 200 nm and used as a seed layer, on silicon nitride coated glass substrate. Thanks to aluminium metal in AIC process, the natural doping of AIC thin films is p(+) type (similar to 2 x 10(18) cm(-3)). On the other hand, recombination of carriers can be controlled by partial doping through the defects that may have advantages to improve the thin film quality by the overdoping induced passivation. In this study, boron (B) and phosphorus (P) doped AIC seed layers were thicken to similar to 2 mu m by solid phase epitaxy (SPE) technique at 800 degrees C for 3 h under nitrogen flow in a tube furnace. During the crystallization annealing, exodiffusion of dopants was formed through the SPE film from the AIC seed layer. Optical microscope and electron back scattering diffraction technique (EBSD) were used to analyse the structural quality of the Si films. The poly-Si layer with an average grain size value of similar to 32 mu m was formed by AIC + SPE technique for P doped samples while EBSD analysis gave no results for B doped samples due to the quite deterioration on the surface of the films. AIC + SPE films were analyzed in terms of structural properties by using micro-Raman Spectroscopy and X-ray diffraction systems. The results showed that the crystallinity of compressive stress formed AIC + SPE films reached up to 98.55%. Additionally, the Raman analysis pointed out that no temperature-induced stress were generated in the AIC + SPE films while compressive stress was induced by increasing the annealing duration for doped AIC film. For all samples, the preferred orientation was < 100 >, and the crystallite size up to 44.4 nm was formed by phosphorus doping of AIC films. The doping efficiency was determined by time-of-flight secondary ion mass spectroscopy for doped samples. A graded n(+)n doping profile was obtained by exo-diffusion of phosphorus from the overdoped seed layer during the epitaxial thickening while boron doping of SPE film has failed with exo-diffusion of boron from AIC seed layer into SPE film. Finally, high-quality n(+)n type poly-Si films were fabricated on glass substrate by using AIC + SPE technique.
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    Whale optimization and sine-cosine optimization algorithms with cellular topology for parameter identification of chaotic systems and Schottky barrier diode models
    (Springer, 2021) Turgut, Mert Sinan; Sagban, H. Muzaffer; Turgut, Oguz Emrah; Ozmen, Ozge Tuzun
    This research study aims to enhance the optimization accuracy of the two recently emerged metaheuristics of whale and sine-cosine optimizers by means of the balanced improvements in intensification and diversification phases of the algorithms provided by cellular automata (CA). Stagnation at the early phases of the iterations, which leads to entrapment in local optimum points in the search space, is one of the inherent drawbacks of the metaheuristic algorithms. As a favorable solution alternative to this problem, different types of cellular topologies are implemented into these two algorithms with a view to ameliorating their search mechanisms. Exploitation of the fertile areas in the search domain is maintained by the interaction between the topological neighbors, whereas the improved exploration is resulted from the smooth diffusion of the available population information among the structured neighbors. Numerical experiments have been carried out to assess the optimization performance of the proposed cellular-based algorithms. Optimization benchmark problems comprised of unimodal and multimodal test functions have been applied and numerical results have been compared with those found by some of the state-of-the-art literature optimizers including particle swarm optimization, differential evolution, artificial cooperative search and differential search. Cellular variants have been outperformed by the base algorithms for multimodal benchmark problems of Levy and Penalized1 functions. Then, the proposed cellular algorithms have been applied to two different parameter identification cases in order to test their efficiencies on real-world optimization problems. Extensive performance evaluations on different parameter optimization cases reveal that incorporating the CA concepts on these algorithms not only improves the optimization accuracy but also provides considerable robustness to acquired solutions.