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    請使用永久網址來引用或連結此文件: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/96079

    題名: Device Simulation-Based Multiobjective Evolutionary Algorithm for Process Optimization of Semiconductor Solar Cells
    作者: Li, Yiming;Chen, Yu-Yu;Chen, Chieh-Yang;Shen, Cheng-Han;Cheng, Hui-Wen;Lo, I-Hsiu;Chen, Chun-Nan
    貢獻者: 淡江大學物理學系
    關鍵詞: Amorphous silicon;Design optimization;Material and structural parameters;MOEA;Multiobjective;Simulation-based evolutionary method;Thin film solar
    日期: 2013-03
    上傳時間: 2014-02-20 15:18:55 (UTC+8)
    出版者: Philadelphia: Taylor & Francis Inc.
    摘要: This article implements for the first time a numerical semiconductor device simulation-based multiobjective evolutionary algorithm (MOEA) for the characteristic optimization of amorphous silicon thin-film solar cells, based upon a unified optimization framework (UOF). To calculate the device's characteristic, a set of coupled solar cell transport equations consisting of the Poisson equation, the electron-hole current continuity equations, and the photo-generation model is solved numerically. Electrical characteristics, the short-circuited current, the open-circuited voltage, and the conversion efficiency are calculated to analyze the properties of the explored solar cells. The aforementioned device simulation results are used to evaluate the fitness score and access the evolutionary quality of designing parameters via the implemented non-dominating sorting genetic algorithm (NSGA-II) in the UOF. Notably, designing parameters including the material and structural parameters, and the doping concentrations are simultaneously optimized for the explored solar cells. The simulation-based MOEA methodology is useful in optimal structure design and manufacturing of semiconductor solar cells.
    關聯: Materials and Manufacturing Processes 28(7), pp.761-767
    DOI: 10.1080/10426914.2013.792433
    顯示於類別:[物理學系暨研究所] 期刊論文





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