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IEEE Transactions on Electron Devices
Article . 2021 . Peer-reviewed
License: IEEE Copyright
Data sources: Crossref
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Statistical Characterization of Time-Dependent Variability Defects Using the Maximum Current Fluctuation

Authors: P. Saraza-Canflanca; J. Martin-Martinez; R. Castro-Lopez; E. Roca; R. Rodriguez; F. V. Fernandez; M. Nafria;

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

Abstract

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.

Country
Spain
Keywords

Random telegraph noise (RTN) ,, Time-dependent variability (TDV), Random telegraph noise (RTN), Maximum current fluctuation (MCF), Transistor, Maximum current fluctuation (MCF) ,, Bias temperature Instability (BTI), Bias temperature instability (BTI)

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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OpenAIRE UsageCountsViews provided by UsageCounts
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