A detailed study of the gate/drain voltage dependence of RTN in bulk pMOS transistors

Random Telegraph Noise (RTN)has attracted increasing interest in the last years. This phenomenon introduces variability in the electrical properties of transistors, in particular in deeply-scaled CMOS technologies, which can cause performance degradation in circuits. In this work, the dependence of RTN parameters, namely current jump amplitude and emission and capture time constants, on the bias conditions, both VG and VD, has been studied on a set of devices, with a high granularity in a broad voltage range. The results obtained for the VG dependences corroborate previous works, but suggest a unique trend for all the devices in a VG range that goes from the near-threshold region up to voltages over the nominal operation bias. However, different trends have been observed in the parameters dependence for the case of VD. From the experimental data, the probabilities of occupation of the associated defects have been evaluated, pointing out large device-to-device dispersion in the VD dependences.Ministerio de Ciencia, Innovación y Universidades TEC2016-75151-C3-R, BES-2017-08016

Determination of the time constant distribution of a defect-centric time-dependent variability model for Sub-100-nm FETs

The origin of some time-dependent variability phenomena in FET technologies has been attributed to the charge carrier trapping/detrapping activity of individual defects present in devices. Although some models have been presented to describe these phenomena from the so-called defect-centric perspective, limited attention has been paid to the complex process that goes from the experimental data of the phenomena up to the final construction of the model and all its components, specifically the one that pertains to the time constant distribution. This article presents a detailed strategy aimed at determining the defect time constant distribution, specifically tailored for small area devices, using data obtained from conventional characterization procedures

On the impact of the biasing history on the characterization of random telegraph noise

Random telegraph noise (RTN) is a time-dependent variability phenomenon that has gained increased attention during the last years, especially in deeply scaled technologies. In particular, there is a wide variety of works presenting different techniques designed to analyze current traces in scaled FET devices displaying RTN, and others focused on modeling the phenomenon using the parameters extracted through such techniques. However, very little attention has been paid to the effects that the biasing conditions of the transistors prior to the measurements may have on the extraction of the parameters that characterize this phenomenon. This article investigates how these biasing conditions actually impact the extracted results. In particular, it is demonstrated that the results obtained when RTN is measured immediately after the device is biased may lead to an overestimation of the RTN impact with respect to situations in which the device has been previously biased for some time. This fact is, first, presented from a theoretical point of view and, after, demonstrated experimentally through measurements obtained from a CMOS-transistor array

Statistical characterization of time-dependent variability defects using the maximum current fluctuation

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

Statistical threshold voltage shifts caused by BTI and HCI at nominal and accelerated conditions

In nowadays deeply scaled CMOS technologies, time-zero and time-dependent variability effects have become important concerns for analog and digital circuit design. For instance, transistor parameter shifts caused by Bias Temperature Instability and Hot-Carrier Injection phenomena can lead to progressive deviations of the circuit performance or even to its catastrophic failure. In this scenario, and to understand the effects of these variability sources, an extensive and accurate device characterization under several test conditions has become an unavoidable step towards trustworthy implementing the stochastic reliability models and simulation tools needed to achieve reliable integrated circuits. In this paper, the statistical distributions of threshold voltage shifts in nanometric CMOS transistors will be studied at nominal and accelerated aging conditions. To this end, a versatile transistor array chip and a flexible measurement setup have been used to reduce the required testing time to attainable values.Peer reviewe

Statistical threshold voltage shifts caused by BTI and HCI at nominal and accelerated conditions

In nowadays deeply scaled CMOS technologies, time-zero and time-dependent variability effects have become important concerns for analog and digital circuit design. For instance, transistor parameter shifts caused by Bias Temperature Instability and Hot-Carrier Injection phenomena can lead to progressive deviations of the circuit performance or even to its catastrophic failure. In this scenario, and to understand the effects of these variability sources, an extensive and accurate device characterization under several test conditions has become an unavoidable step towards trustworthy implementing the stochastic reliability models and simulation tools needed to achieve reliable integrated circuits. In this paper, the statistical distributions of threshold voltage shifts in nanometric CMOS transistors will be studied at nominal and accelerated aging conditions. To this end, a versatile transistor array chip and a flexible measurement setup have been used to reduce the required testing time to attainable values

Unified RTN and BTI statistical compact modeling from a defect-centric perspective

In nowadays deeply scaled CMOS technologies, time-dependent variability effects have become important concerns for analog and digital circuit design. Transistor parameter shifts caused by Bias Temperature Instability and Random Telegraph Noise phenomena can lead to deviations of the circuit performance or even to its fatal failure. In this scenario extensive and accurate device characterization under several test conditions has become an unavoidable step towards trustworthy implementing the stochastic reliability models. In this paper, the statistical distributions of threshold voltage shifts in nanometric CMOS transistors will be studied at near threshold, nominal and accelerated aging conditions. Statistical modelling of RTN and BTI combined effects covering the full voltage range is presented. The results of this work suppose a complete modelling approach of BTI and RTN that can be applied in a wide range of voltages for reliability predictions