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'Genetically Engineered' Nanoelectronics

机译:“基因工程”纳米电子学

摘要

The quantum mechanical functionality of nanoelectronic devices such as resonant tunneling diodes (RTDs), quantum well infrared-photodetectors (QWIPs), quantum well lasers, and heterostructure field effect transistors (HFETs) is enabled by material variations on an atomic scale. The design and optimization of such devices requires a fundamental understanding of electron transport in such dimensions. The Nanoelectronic Modeling Tool (NEMO) is a general-purpose quantum device design and analysis tool based on a fundamental non-equilibrium electron transport theory. NEW was combined with a parallelized genetic algorithm package (PGAPACK) to evolve structural and material parameters to match a desired set of experimental data. A numerical experiment that evolves structural variations such as layer widths and doping concentrations is performed to analyze an experimental current voltage characteristic. The genetic algorithm is found to drive the NEMO simulation parameters close to the experimentally prescribed layer thicknesses and doping profiles. With such a quantitative agreement between theory and experiment design synthesis can be performed.
机译:纳米电子器件的量子力学功能(例如共振隧穿二极管(RTD),量子阱红外光电探测器(QWIP),量子阱激光器和异质结构场效应晶体管(HFET))可以通过原子尺度的材料变化实现。这种装置的设计和优化要求对这种尺寸的电子传输有基本的了解。纳米电子建模工具(NEMO)是基于基本的非平衡电子传输理论的通用量子器件设计和分析工具。 NEW与并行遗传算法软件包(PGAPACK)结合使用,以发展结构和材料参数,以匹配所需的实验数据集。进行了演化诸如层宽和掺杂浓度等结构变化的数值实验,以分析实验电流电压特性。发现遗传算法可以驱动NEMO模拟参数接近实验规定的层厚度和掺杂分布。通过理论和实验设计之间的这种定量协议,可以进行合成。

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