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Low Cost Fabrication of UV Photodetector Based on Hexagonal Nanocrystal ZnO:Al/p-Si Heterojunction
Li Duan,Feng Wei,Jibin Fan,Xiaochen Yu,Wenxue Zhang,Yan Zhang,Fengni He,Xiaojiao Cheng,Ye Tian 성균관대학교(자연과학캠퍼스) 성균나노과학기술원 2016 NANO Vol.11 No.2
ZnO:Al/p-Si heterojunction was fabricated by depositing a hexagonal nanocrystal ZnO:Al film on p-type Si substrate using a simple chemical bath deposition (CBD) method. The vertically aligned hexagonal ZnO:Al nanocrystals reduce the grain boundary scattering and provide good conductivity. The ZnO:Al/Si heterojunction shows obvious photocurrent under ultraviolet (UV) illumination. A high UV-to-visible rejection ratio of the ZnO:Al/Si heterojunction indicates that the hexagonal nanocrystal ZnO:Al film is a good material for fabricating UV photodetectors. Furthermore, the response speed of the photodetector based on ZnO:Al hexagonal nanocrystal film is faster than that of most previously reported photodetectors based on ZnO:Al nanorods. We infer it is because the ZnO:Al nanocrystals film has a smaller surface to volume ratio than the ZnO:Al nanorod array.
Quantum Bacterial Foraging Optimization for Cognitive Radio Spectrum Allocation
( Fei Li ),( Jiulong Wu ),( Wenxue Ge ),( Wei Ji ) 한국인터넷정보학회 2015 KSII Transactions on Internet and Information Syst Vol.9 No.2
This paper proposes a novel swarm intelligence optimization method which integrates bacterial foraging optimization (BFO) with quantum computing, called quantum bacterial foraging optimization (QBFO) algorithm. In QBFO, a multi-qubit which can represent a linear superposition of states in search space probabilistically is used to represent a bacterium, so that the quantum bacteria representation has a better characteristic of population diversity. A quantum rotation gate is designed to simulate the chemotactic step for the sake of driving the bacteria toward better solutions. Several tests are conducted based on benchmark functions including multi-peak function to evaluate optimization performance of the proposed algorithm. Numerical results show that the proposed QBFO has more powerful properties in terms of convergence rate, stability and the ability of searching for the global optimal solution than the original BFO and quantum genetic algorithm. Furthermore, we examine the employment of our proposed QBFO for cognitive radio spectrum allocation. The results indicate that the proposed QBFO based spectrum allocation scheme achieves high efficiency of spectrum usage and improves the transmission performance of secondary users, as compared to color sensitive graph coloring algorithm and quantum genetic algorithm.