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Optoelectronic performance and artificial neural networks (ANNs) modeling of n-InSe/p-Si solar cell

机译:n-InSe / p-Si太阳能电池的光电性能和人工神经网络(ANN)建模

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摘要

Nanostructure thin film of InSe deposited on p-Si single crystal to fabricate n-InSe/p-Si heterojunction. Electrical and photoelectrical have been studied by the current density-voltage (J-V). The fabricated cell exhibited rectifying characteristics. Analyzing the results of dark forward J-V shows that there are differrent conduction mechanisms. At low voltages, the current density is controlled by a Schottky emission mechanism. While at a relatively high voltage, a space charge-limited-conduction mechanism is observed with a single trap level. The cell also exhibited a photovoltaic characteristic with a power conversion efficiency of 3.42%. Moreover, artificial neural networks (ANNs) are adopted to model the J-V through the obtained functions. Different network configurations and many runs were trying to achieve good performance and finally obtained the current density, J, as a function of the junction temperature, 7", and applied voltage, V. In all cases studied, we compared our obtained functions produced by the ANN technique with the corresponding experimental data and the excellent matching was so clear.
机译:InSe纳米结构薄膜沉积在p-Si单晶上以制造n-InSe / p-Si异质结。已经通过电流密度-电压(J-V)研究了电学和光电学。制成的电池表现出整流特性。分析暗前向J-V的结果表明存在不同的传导机制。在低电压下,电流密度由肖特基发射机制控制。在较高电压下,可以观察到单个陷阱能级限制空间电荷的传导机制。该电池还表现出光伏特性,功率转换效率为3.42%。此外,通过获得的函数,采用人工神经网络(ANN)对J-V进行建模。不同的网络配置和许多运行都试图获得良好的性能,并最终获得了作为结温7“和施加电压V的函数的电流密度J。在研究的所有情况下,我们都比较了由人工神经网络技术与相应的实验数据和出色的匹配非常清晰。

著录项

  • 来源
    《Superlattices and microstructures》 |2015年第7期|299-309|共11页
  • 作者单位

    Department of Physics, Faculty of Science, University of Tabuk, P.O. Box 741, Tabuk 71491, Saudi Arabia,Department of Physics, Faculty of Education at Al-Mahweet, Sana'a University, Al-Mahweet, Yemen;

    Department of Physics, Faculty of Science, University of Tabuk, P.O. Box 741, Tabuk 71491, Saudi Arabia,Department of Physics, Faculty of Science, Al-Fayoum University, Al-Fayoum 6351, Egypt;

    Department of Physics, Faculty of Education, Ain Shams University, Roxy Square 11757, Cairo, Egypt;

    Department of Physics, Faculty of Education, Ain Shams University, Roxy Square 11757, Cairo, Egypt;

    Department of Physics, Faculty of Science, University of Tabuk, P.O. Box 741, Tabuk 71491, Saudi Arabia,Department of Physics, Faculty of Education, Ain Shams University, Roxy Square 11757, Cairo, Egypt;

    Department of Physics, Faculty of Education, Ain Shams University, Roxy Square 11757, Cairo, Egypt;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Electrical; Photovoltaic; Solar cell; ANN modeling;

    机译:电气;光伏太阳能电池;人工神经网络建模;

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