“基因工程”纳米电子学

Gerhard Klimeck, C. Salazar-Lazaro, A. Stoica, T. Cwik
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引用次数: 6

摘要

共振隧道二极管(rtd)、量子阱红外探测器(QWIPs)、量子阱激光器和异质结构场效应晶体管(hfet)等纳米电子器件的量子力学功能是通过原子尺度上的材料变化实现的。这种装置的设计和优化需要对这种尺寸的电子传递有基本的了解。纳米电子建模工具(NEMO)是一种基于基本非平衡电子输运理论的通用量子器件设计和分析工具。NEMO结合了并行遗传算法包(PGAPACK)来进化结构和材料参数,以匹配所需的实验数据集。数值实验分析了结构的变化,如层宽度和掺杂浓度,以分析实验电流电压特性。发现遗传算法驱动NEMO模拟参数接近实验规定的层厚度和掺杂分布。有了理论和实验设计之间的这种定量一致,就可以进行综合设计。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
"Genetically engineered" nanoelectronics
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. NEMO 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.
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