Xingsheng Wang
Paper Publications
Geometry, Temperature, and Body Bias Dependence of Statistical Variability in 20-nm Bulk CMOS Technology: A Comprehensive Simulation Analysis
Release time:2018-06-07 Hits:
Indexed by:Journal paper
First Author:Xingsheng Wang
Correspondence Author:Xingsheng Wang
Co-author:Fikru Adamu-Lema,Binjie Cheng,Asen Asenov
Journal:IEEE Transactions on Electron Devices
Included Journals:SCI、EI
Affiliation of Author(s):University of Glasgow
Volume:60
Issue:5
Page Number:1547–1554
Key Words:Body bias
,
channel width
,
CMOS
,
gate length
,
temperature
,
variability
DOI number:10.1109/TED.2013.2254490
Date of Publication:2013-05-01
Abstract:Conventional bulk CMOS, which is arguably most vulnerable to statistical variability (SV), is the workhorse of the electronic industry for more than three decades. In this paper, the dependence of the SV of key figures of merit on gate geometry, temperature, and body bias in 25-nm gate-length MOSFETs, representative for the 20-nm CMOS technology generation, is systematically investigated using 3-D statistical simulations. The impact of all relevant sources of SV is taken into account. The geometry dependence of the threshold-voltage dispersion (and indeed the dispersion of other key transistor figures of merit) does not necessarily follow the Pelgrom's law due to the complex nonuniform channel doping and the interplay of different SV sources. The DIBL variation, for example, follows a log-normal distribution. The temperature significantly affects the magnitudes of threshold voltage, subthreshold slope, ON/OFF currents, and the corresponding statistical distributions. Reverse body bias increases the threshold voltage and its fluctuation, while forward body bias reduces both of them.
Links to published journals:https://ieeexplore.ieee.org/document/6502684