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.
Original language | English |
---|---|
Article number | 9459448 |
Pages (from-to) | 4039-4044 |
Number of pages | 6 |
Journal | IEEE Transactions on Electron Devices |
Volume | 68 |
Issue number | 8 |
Publication status | Published - 1 Aug 2021 |
Keywords
- Bias temperature instability (BTI)
- maximum current fluctuation (MCF)
- random telegraph noise (RTN)
- time-dependent variability (TDV)
- transistor