A Novel TCAD Approach to Temperature Dependent DC FinFET Variability Analysis

S. Guerrieri, F. Bonani, G. Ghione
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引用次数: 5

Abstract

This paper presents a new approach to extract the temperature-dependent sensitivity of electron devices DC current through efficient, yet accurate, physics-based analysis. The novel technique is based on a Green's function approach, where the response of the device to lattice (ambient) temperature variations is recovered by means of the linearization of the device equations around the nominal device working point and temperature. The same Green's Functions are also used for other device variability analyses, e.g. random doping fluctuations or geometrical variations. A linear superposition of the device response to temperature variations with any other parameter variation, allows for a temperature-dependent device variability analysis, with virtually the same numerical burden as the fixed temperature one. In this paper we verify the technique against non-linearized (MonteCarlo) analyses. A metal gate FinFET is considered in two case studies: temperature-dependent deterministic variations of the fin doping concentration; temperature-dependent random workfunction variations due to metal granularity. The approach is extremely accurate up to 80 K above ambient temperature with a huge reduction in simulation time with respect to MonteCarlo approach.
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温度相关直流FinFET可变性分析的TCAD新方法
本文提出了一种新的方法,通过有效而准确的物理分析来提取电子器件直流电流的温度依赖性灵敏度。该新技术基于格林函数方法,其中器件对晶格(环境)温度变化的响应通过器件方程在标称器件工作点和温度周围的线性化来恢复。同样的格林函数也用于其他器件可变性分析,例如随机掺杂波动或几何变化。器件对温度变化的响应与任何其他参数变化的线性叠加,允许温度相关的器件可变性分析,几乎与固定温度相同的数值负担。在本文中,我们对非线性(MonteCarlo)分析验证了该技术。在两个案例研究中考虑了金属栅极FinFET:翅片掺杂浓度的温度依赖性确定性变化;由金属粒度引起的温度依赖性随机工作函数变化。与蒙特卡罗方法相比,该方法在高于环境温度80 K的情况下非常精确,并且大大减少了模拟时间。
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