基于软计算的砷化镓衬底量子点纳米结构分类与设计

A. Ürmös, Z. Farkas, T. Sandor, Á. Nemcsics
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引用次数: 0

摘要

纳米结构可以显著改善半导体器件的参数。因此,有必要制造具有给定参数的纳米结构。本文将讨论自组织纳米结构的软计算设计和一种新的分类模型。这些纳米结构是通过液滴外延在复合半导体衬底上形成的。纳米结构的参数(类型、尺寸、分布)取决于应用的技术。该工艺的关键因素(衬底温度、Ga通量、As压力、退火时间和退火温度)将被确定为设计参数。设置这些参数是为了生产具有所需性能的纳米结构。本文还讨论了先前介绍的基于纳米结构模糊分类模型的修正版本。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Soft-computing based classification and design of quantum dot nanostructures on GaAs substrate
The parameters of the semiconductor devices can be improved by nanostructures significantly. For this reason, it is necessary to produce nanostructures with given parameters. The soft-computing design of the self-organized nanostructures and a new classification model will be discussed in this paper. These nanostructures are formed by droplet epitaxy on compound semiconductor substrate. The parameters of the nanostructures (type, size, distribution) depend on the applied technology. The key factors of the technology (substrate temperature, Ga flux, As pressure, annealing time and annealing temperature) will be determined as design parameters. These parameters are set in order to produce nanostructures with the desired property. The revised version of previously introduced nanostructure fuzzy-based classification model will be also discussed.
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