氮化镓
纤锌矿晶体结构
遗传算法
启发式
计算
材料科学
宽禁带半导体
计算机科学
电子迁移率
电场
光电子学
兴奋剂
镓
电子工程
航程(航空)
算法
纳米技术
工程类
物理
人工智能
机器学习
锌
复合材料
冶金
量子力学
图层(电子)
作者
M.A. Abdi,F. Djeffal,N. Lakhdar,T. Bendib,F. Meddour
标识
DOI:10.1109/icscs.2008.4746943
摘要
Recently, the evolutionary techniques, like genetic algorithms (GA), has attracted considerable attention among various heuristic optimization techniques. So, in this paper, a genetic algorithm is implemented to study and model the electron mobility in wurtzite Gallium Nitride-based devices. Further, our obtained results are tested and compared with numerical data where a good agreement has been found for wide range of temperature, doping and applied high electric field. The optimized analytical models have been incorporated into the devices simulators to study the GaN-based MOSFETs for optoelectronics and high frequencies applications.
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