Statistical Characterization of Time-Dependent Variability Defects Using the Maximum Current Fluctuation

This article presents a new methodology to extract, at a given operation condition, the statistical distribution of the number of active defects that contribute to the observed device time-dependent variability, as well as their amplitude distribution. Unlike traditional approaches based on complex...

Full description

Saved in:
Bibliographic Details
Published in:IEEE transactions on electron devices 2021-08, Vol.68 (8), p.4039-4044
Main Authors: Saraza-Canflanca, P., Martin-Martinez, J., Castro-Lopez, R., Roca, E., Rodriguez, R., Fernandez, F. V., Nafria, M.
Format: Article
Language:English
Subjects:
Bias temperature instability (BTI)
Current measurement
Defects
Logic gates
maximum current fluctuation (MCF)
Measurement
Noise measurement
random telegraph noise (RTN)
Threshold voltage
Time dependence
Time measurement
time-dependent variability (TDV)
transistor
Transistors
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:This article presents a new methodology to extract, at a given operation condition, the statistical distribution of the number of active defects that contribute to the observed device time-dependent variability, as well as their amplitude distribution. Unlike traditional approaches based on complex and time-consuming individual analysis of thousands of current traces, the proposed approach uses a simpler trace processing, since only the maximum and minimum values of the drain current during a given time interval are needed. Moreover, this extraction method can also estimate defects causing small current shifts, which can be very complex to identify by traditional means. Experimental data in a wide range of gate voltages, from near-threshold up to nominal operation conditions, are analyzed with the proposed methodology.
ISSN:0018-9383
1557-9646
DOI:10.1109/TED.2021.3086448