2026-04-13T02:30:51Zhttps://recercat.cat/oai/request

oai:recercat.cat:2072/4572612026-03-13T07:46:00Zcom_2072_98col_2072_378192

00925njm 22002777a 4500 dc Saraza-Canflanca, Pablo author Martin Martinez, Javier author Castro-Lopez, Rafael author Roca, Elisenda author Rodríguez Martínez, Rosana author Fernandez, Francisco V. author Nafría i Maqueda, Montserrat author 2021 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. Bias temperature instability (BTI) Maximum current fluctuation (MCF) Random telegraph noise (RTN) Time-dependent variability (TDV) Transistor Statistical characterization of time-dependent variability defects using the maximum current fluctuation