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Measurements, modeling, and simulation of semiconductor/gate dielectric defects using random telegraph signals.

机译:使用随机电报信号进行半导体/栅极介电缺陷的测量,建模和仿真。

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摘要

Constructing an effective statistical model and a simulation tool that can predict the phenomenon of random telegraph signals (RTS) is the objective of this work. The continuous scaling down of metal oxide -- semiconductor field effect transistors (MOSFETs) makes charging/discharging traps(s) located at the silicon/silicon dioxide interface or deep in the oxide bulk by mobile charge(s) a more pronounced problem for both analog and digital applications. The intent of this work is to develop an RTS statistical model and a simulation tool based on first principles and supported by extensive experimental data. The newly developed RTS statistical model and its simulation tool should be able to replicate and predict the RTS in time and frequency domains.;First, room temperature RTS measurements are performed which provide limited information about the trap. They yield the extraction of some trap and RTS characteristics such as average capture and emission times associated with RTS traces, trap position in the oxide with respect to the Si/SiO 2 interface and along the channel with respect to the source, capture cross section, and trap energies in the Si and SiO2 band -- gaps. Variable temperature measurements, on the other hand, yield much more valuable information. Variable temperature RTS measurements from room temperature down to 80 K were performed, with the MOSFET biased from threshold voltage to strong inversion, in the linear and saturation regions. Variable temperature RTS measurements yield the extraction of trap characteristics such as capture cross -- section prefactor, capture and emission activation energies, change in entropy and enthalpy, and relaxation energy associated with a trap from which the nature and origin of a defect center can be identified.;The newly developed Random Telegraph Signals Simulation (RTSSIM) is based on several physical principles and mechanisms e.g. (1) capturing and emitting a mobile charge from and to the channel is governed by phonon- assisted- tunneling, (2) traps only within a few kBT of the Fermi energy level are considered electrically active, (3) trap density is taken as U -- shaped in energy in the silicon band-gap, (4) device scalability is accounted for, (5) and temperature dependence of all parameters is considered. RTSSIM reconstructs the RTS traces in time domain from which the power spectral density (PSD) is evaluated. If there is 20 or more active traps, RTSSIM evaluates the PSD from the superposition of the RTS spectra. RTSSIM extracts RTS and trap characteristics from the simulated RTS data and outputs them to MS Excel files for further analyses and study.;The novelty of this work is: (1) it is the first time quantum trap states have been accurately assigned to each switching level in a complex RTS corresponding to dependently and independently interacting traps, (2) new physics-based measurement-driven model and simulation tool has been developed for RTS phenomenon in a MOSFET, (3) and it is the first time a species in SiO2 responsible for RTS has been identified through time-domain measurements and extensive analysis using four trap characteristics at the same time.
机译:建立有效的统计模型和仿真工具以预测随机电报信号(RTS)的现象是这项工作的目标。金属氧化物的不断缩小-半导体场效应晶体管(MOSFET)使得位于硅/二氧化硅界面处或由于移动电荷而位于氧化物体深处的充电/放电陷阱对于这两种情况而言都是更为突出的问题模拟和数字应用。这项工作的目的是在第一原理的基础上并以大量实验数据为支持,开发RTS统计模型和仿真工具。新开发的RTS统计模型及其仿真工具应该能够在时域和频域中复制和预测RTS。首先,进行室温RTS测量,这些信息提供有关陷阱的有限信息。他们提取了一些陷阱和RTS特性,例如与RTS迹线相关的平均捕获和发射时间,氧化物相对于Si / SiO 2界面以及沿沟道相对于源的捕获位置,捕获截面,并在Si和SiO2带隙中捕获能量。另一方面,可变温度测量会产生更多有价值的信息。进行了从室温到80 K的可变温度RTS测量,其中MOSFET在线性和饱和区域中从阈值电压偏置到强反相。可变温度RTS测量可提取陷阱特征,例如捕获横截面前因子,捕获和发射活化能,熵和焓的变化以及与陷阱相关的弛豫能量,从中可以确定缺陷中心的性质和来源新开发的随机电报信号仿真(RTSSIM)基于多种物理原理和机制,例如(1)通过声子辅助隧穿控制从通道捕获和向通道发射移动电荷,(2)仅在费米能级几kBT以内的陷阱被认为是电活跃的,(3)陷阱密度为硅带隙中的能量呈U形,(4)考虑了器件的可扩展性,(5)考虑了所有参数的温度依赖性。 RTSSIM在时域中重建RTS迹线,从中可以评估功率谱密度(PSD)。如果有20个或更多的活动陷阱,则RTSSIM会根据RTS光谱的叠加来评估PSD。 RTSSIM从模拟的RTS数据中提取RTS和陷阱特征并将其输出到MS Excel文件中以进行进一步的分析和研究。这项工作的新颖性是:(1)这是首次将量子陷阱状态精确地分配给每个开关(2)针对MOSFET中的RTS现象开发了新的基于物理学的,基于测量的驱动模型和仿真工具(3),这是SiO2中的第一个物种通过时域测量和同时使用四个陷阱特征的广泛分析,已经确定了负责RTS的因素。

著录项

  • 作者

    Nour, Mohamed.;

  • 作者单位

    The University of Texas at Arlington.;

  • 授予单位 The University of Texas at Arlington.;
  • 学科 Electrical engineering.;Nanotechnology.
  • 学位 Ph.D.
  • 年度 2015
  • 页码 218 p.
  • 总页数 218
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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