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

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

Research output: Contribution to journalArticleResearchpeer-review


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.

Original languageEnglish
Article number9459448
Pages (from-to)4039-4044
Number of pages6
JournalIEEE Transactions on Electron Devices
Issue number8
Publication statusPublished - 1 Aug 2021


  • Bias temperature instability (BTI)
  • maximum current fluctuation (MCF)
  • random telegraph noise (RTN)
  • time-dependent variability (TDV)
  • transistor


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