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handle: 10261/244237 , 11441/162387
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.
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)
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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| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
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