噪音(视频)
计算机科学
电阻随机存取存储器
可靠性(半导体)
电子工程
电气工程
物理
电压
人工智能
工程类
功率(物理)
量子力学
图像(数学)
作者
Francesco Maria Puglisi,Andrea Padovani,Luca Larcher,Paolo Pavan
出处
期刊:
日期:2017-07-01
卷期号:: 1-9
被引量:31
标识
DOI:10.1109/ipfa.2017.8060057
摘要
In this paper, we delve into one of the most relevant defects-related phenomena causing failures in the operation of modern nanoscale electron devices, namely Random Telegraph Noise (RTN). Due to its detrimental impact on devices and circuits performances, RTN mechanism must be thoroughly understood, which requires establishing a self-consistent framework encompassing automated measurement techniques, data analysis algorithms, and physics-based modeling. This platform is not only required to understand the physics of RTN-related failures, but also to enable RTN analysis as a tool to investigate device reliability. Starting from the analysis of RTN signal statistical properties, we propose a set of guidelines to perform correct RTN measurements and data analysis, in order to get reliable results that are needed for an unbiased physical interpretation. This is achieved by combining automated experiments with sophisticated data analysis, consistency check, and comprehensive physics-based simulations. RTN analysis is then applied to two different devices for logic and memory applications, respectively: FinFETs and RRAMs. Particularly, the analysis of the statistical properties of RTN simultaneously measured on the drain and on the gate current of FinFETs allows understanding the details of the defects generation during stress. The analysis of RTN measured during the read operation in RRAM devices allows understanding the physical origin of RTN in these devices and identifying the defects species involved in this phenomenon.
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