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Articles by A. Lennie
Total Records ( 4 ) for A. Lennie
  A. Lennie , H. Abdullah , S. Shaari and K. Sopian
  The main objectives was to investigate and enhance the short circuit current density, Jsc and also to improve the efficiency of silicon solar cell by fabricating a layer of silicon dioxide (SiO2) and silicon nitride (Si3N4) coatings on silicon solar cell. This fabrication carried out on high temperature during annealing process from 800-1050°C and variable thickness of antireflection coating (ARC) layer from 50-90 nm thick. The photovoltaic properties of Si3N4 layer have been compared with SiO2 layer to determine which material is suitable in fabricating single layer ARC. Solar cell simulation could be useful for time saving and cost consumption. Problem statement: The Silvaco software is not widely used in designing the 2D solar cell devices because there are lots of 1D, 2D and 3D-simulation beside Silvaco software such as MicroTec, SCAPS-1D. Approach: The silicon dioxide (SiO2) and silicon nitride (Si3N4) coating have been modeled and fabricated on silicon solar cell by using Silvaco software packaging. Results: For SiO2 results, the FF value is approximately 0.758 and η maximum 9.43%. In annealing process, the temperature becomes higher resulted increasing of pn junction depth. However, not to Voc and Jsc values, both parameters were slowly decreased when temperature increased. Meanwhile, when the thickness of SiO2 layer is increased, the parameters of pn junction depth, Jsc, Voc, FF and η were decreased slowly. As for Si3N4 result, the calculated FF approximately 0.758 and η maximum is 9.57%. During annealing process, the temperature increasing constantly follows the increasing of pn junction depth and Jsc, meanwhile the Voc is decreased slowly. In variable Si3N4 thickness simulation, the output parameters of pn junction depth, Jsc, Voc, FF and η were decreased when the thickness increased 10 nm each simulation. Conclusion: The optimum temperature during annealing process for SiO2 is 950°C, while for Si3N4 is 1050°C. For the thickness analysis, the optimum ARC thickness for SiO2 and Si3N4 layer is 50 nm both.
  H. Abdullah , A. Lennie , M.J. Saifuddin and I. Ahmad
  Problem statement: This project discusses on the method to resolve the optical losses problem that have been hindering the totality efficiency of the photovoltaic. Solar cell simulation could be useful for time saving and cost consumption. The Silvaco software is not widely used in designing the 2D solar cell devices because there is lots of 1D, 2D and 3D-simulation beside Silvaco software such as MicroTec, SCAPS-1D. Approach: The different models surface texturing on GaAs solar cell had been simulated by using the Virtual Wafer Fab (VWF), SILVACO software in this project. Results: It was expected that modification of surface texturing might distinctly improved the spectral sensitivity of the photovoltaic by reducing the light reflection and improving the light trapping. There are four models surface texture of photovoltaic devices. It is the simple structure, V-trench structure, fours-sided structure and semi-sphere structure. Hence, the incoming light will hit the GaAs surface several times. Light, which is not absorbed in its first passage through the cell, has the additional opportunities to be absorbed into the cell. It had been shown that modified surface of GaAs solar cell had improved the efficiency up to more than 2% and its quality application performance about 10%. Conclusion: From the simulation result, the V-trench structure is the best surface texture for GaAs solar cell compared to the others, which has Jsc is 3.575 mA cm-2, Voc is 0.807 V and efficiency is 23.07% in 90° incident light.
  H. Abdullah , A. Lennie and I. Ahmad
  In this study, simulated single layer Anti-Reflective Coating (ARC) on silicon solar cell that based on the refractive index limit of silicon dioxide (SiO2), zinc oxide (ZnO) and zinc sulphide (ZnS) are presented. Two simulations of ZnO and ZnS coating were simulated to compare with SiO2 ARC on silicon solar cell surface. These simulations carried out with variable coating thickness that is 50, 60, 70 and 80 nm by using ATLAS simulator. From the simulation obtained, it was found that the value of Voc and Jsc are 397.69 mV and 15.646 mA cm-2, respectively, from silicon solar cell with 0.05 μm SiO2 coating. For the Fill Factor (FF) and power conversion efficiency (η) of this solar cell is 0.758 and 4.72% were computed. As for the ARC simulation, the spectral response of ZnO and ZnS coating was increased around 600 and 700 nm, respectively, which are capable of reducing the refractivity over a wide range of wavelengths compared to SiO2 increased around 400 nm wavelength. This can be concluded that when the refractive index value is high, the available photocurrent also can be high in wide range wavelength and more reducing the refractivity. In ARC analysis, the ZnS coating could perform more efficiency on wide range of wavelength compared to SiO2 and ZnO ARC.
  A. Lennie , S. Abdullah , Z.M. Nopiah and M.N. Baharin
  This study presents an analysis on variable amplitude loading strains data by using amplitude probability distribution function, power spectral density function and cross correlation function techniques. The objectives of this study are to observe the capability of these techniques in investigating the time series behaviour in terms of distribution and statistical values and also detecting the similarity of pattern signal. In this study, the data consisting of non-stationary variable amplitude loading strains data exhibiting a random behaviour was used as a set of case study. This random data was collected on the lower suspension arm of an automobile component travelling on pavé and highway route. The data was repetitively measured for 60 sec at the sampling rate of 500 Hz, which provided 30,000 discrete data points. The collected data was then calculated and analysed for the signal distribution, statistics parameter and cross correlation values. Higher calculated cross correlation values were then selected to analyse fatigue damage prediction. From amplitude probability distribution function and power spectral density function diagrams, the result can be concluded that the non-Gaussian distribution can be related to a broad band signal, while for Gaussian distribution for a narrow band signal. The findings from this study are expected to be used in determining the pattern behavior that exists in VA signals.
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