Crystalline NiO and doped with rare earth lutetium oxide (Lu2O3) at (6%wt)., have been prepared by pulsed laser deposition (PLD), The Q-switched Nd:YAG laser beam was incident at an angle of 45° on the target surface, and the energy of the laser was 500 mJ, wavelengths of 532nm, and frequency 6Hz. XRD pattern shows all doped and undoped films are polycrystalline, and cubic structure. The 200nm thin NiO showed an average optical energy band gap of 3.4eV, and increase with doping at 6% Lu2O3. The Hall Effect measurements confirmed that holes were predominant charges in the conduction process (i.e p-type). D.C conductivity measurements with temp-erature (T), show that the films prepared have the two activation energy increase with doping of Lu2O3. Capacitance-voltage (C-V) measurements were performed for films prepared, where the built in voltage has been determined and decreases in value when doping with the rare earth. In this study we assumed an energy band diagram for p-NiO /n-Si heterojunction.
Energy Band Diagram of NiO: Lu2 O3/n-Si heterojunction
Thin film of NiO
Rare Earth
PLD
Energy Band diagram
Publication Date
Wed Apr 25 2018
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Different Estimation Methods for System Reliability Multi-Components model: Exponentiated Weibull Distribution
Exponentiated Weibull Distribution (EWD)
Reliability of multi-component Stress – Strength models R(s
k)
Maximum likelihood estimator (MLE)
Moment estimator (MOM)
shrinkage method (Sh)
Least Squares Estimator (LS)
Rank Set Sampling (RSS). and mean squared error (MSE).
In this paper, estimation of system reliability of the multi-components in stress-strength model R(s,k) is considered, when the stress and strength are independent random variables and follows the Exponentiated Weibull Distribution (EWD) with known first shape parameter θ and, the second shape parameter α is unknown using different estimation methods. Comparisons among the proposed estimators through Monte Carlo simulation technique were made depend on mean squared error (MSE) criteria
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