Statistical Model for the Circuit Bandwidth Dependence of Low-Frequency Noise in Deep-Submicrometer MOSFETs

Wirth, Gilson; Silva, Roberto da; Brederlow, R.

doi:10.1109/ted.2006.888672

Cited by 25 publications

(13 citation statements)

References 14 publications

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“…As shown in Figure 11, the degradation rate changes rapidly when α~0 or 1, while the change is gradual for intermediate duty cycles. This behavior is due to the change in the voltage dependent time constants [12], and well predicted by a single equation in the long-term prediction (Fig. 11).…”

Section: Constant Stresssupporting

confidence: 61%

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Logarithmic modeling of BTI under dynamic circuit operation: Static, dynamic and long-term prediction

Velamala

Sutaria

Shimuzu

et al. 2013

2013 IEEE International Reliability Physics Symposium (IRPS)

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Bias temperature instability (BTI) is the dominant source of aging in nanoscale transistors. Recent works show the role of charge trapping/de-trapping (T-D) in BTI through discrete V th shifts, with the degradation exhibiting an excessive amount of randomness. Furthermore, modern circuits employ dynamic voltage scaling (DVS) where V dd is tuned, complicating the aging effect. It becomes challenging to predict long-term aging in an actual circuit under statistical variation and DVS. To accurately predict the degradation in these circumstances, this work (1 ) examines the principles of T-D, thereby proposing static and cycle-to-cycle (dynamic) models under voltage tuning in DVS; (2) presents a long-term model, estimating a tight upper bound of dynamic aging;(3) comprehensively validates the new set of models with 65nm silicon data. The proposed aging models accurately capture the recovery behavior in dynamic operations, reducing the unnecessary margin and enhancing the simulation efficiency for aging estimation during the design stage. Keywords-Trapping/de-trapping, statistical variations, compact modeling, negative bias temperature instability, DVS.I.

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Section: Constant Stresssupporting

confidence: 61%

“…To develop a compact aging model, the primary assumptions are summarized in Table I. These assumptions are in accordance with modeling framework for low frequency noise [9][10][11][12][13][14]. Monte-Carlo simulations are performed based on above assumptions which are used for validation of the model.…”

Section: T-d Properties and Static Bti Modelingmentioning

confidence: 99%

Logarithmic modeling of BTI under dynamic circuit operation: Static, dynamic and long-term prediction

Velamala

Sutaria

Shimuzu

et al. 2013

2013 IEEE International Reliability Physics Symposium (IRPS)

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“…are here translated as averaged capture time (τ c ), and averaged emission time (τ e ) respectively. Although many works consider the analysis in the frequency domain of RTS (to cite a few ones [5,6,7,8,9,10]), on the other hand, time-domain analysis (see for example [11,12,13,14]) deserves more attention from researchers in this kind of modeling. Time-domain analysis is important for example to understand the degradation phenomena in semiconductor devices from experimental [15], and theoretical point of view [16].…”

Section: Introductionmentioning

confidence: 99%

Estimating time constants of the RTS noise in semiconductor devices: a complete description of the observation window in the time domain

Silva¹,

Wirth²

2022

Preprint

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We obtained a semi-analytical treatment obtaining estimators for the sample variance and variance of sample variance for the RTS noise. Our method suggests a way to experimentally determine the constants of capture and emission in the case of a dominant trap and universal behaviors for the superposition from many traps. We present detailed closed-form expressions corroborated by MC simulations. We are sure to have an important tool to guide developers in building and analyzing low-frequency noise in semiconductor devices.

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“…Regarding the device-based performance, this peculiar LFN behavior has increased by a great extent the LFN variability [1], related to the significant trap number variations from device to device due to small area or GR centers, leading to further limitations in device performance and reliability [7]. Inevitably, these limitations concern the safe operation of a whole circuit, as it has been reported that LFN/RTN has a major impact on both digital and analog circuits [8]- [11]. More specifically, in the case of SRAMs, the presence of RTN limits the minimum supply voltage, Vdd, due to Vt shifts.…”

Section: Introductionmentioning

confidence: 99%

Model Implementation of Lorentzian Spectra for Circuit Noise Simulations in the Frequency Domain

Tataridou

Ghibaudo

Theodorou

2022

IEEE J. Electron Devices Soc.

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This work presents a new method for the Verilog-A implementation of Lorentzian noise models, in a module called VERILOR, which can automatically generate either Lorentzian or 1/f-like noise spectra depending on the trap density and gate oxide area, for all bias conditions, in a one-step simulation. Based on statistical experimental data, we demonstrate the importance of Lorentzian noise modeling in contrast to classic frequency domain 1/f or time domain Random Telegraph Noise (RTN) modeling, in terms of PSD, total noise power, and device-to-device noise variability reproduction. Moreover, we validate the applicability of VERILOR in circuit simulators in both frequency and time domain, and how it can enable precise noise variability studies at a circuit level. Finally, fundamental digital and analog circuits such as the Ring Oscillator are used to showcase the usefulness and applicability of the VERILOR model in circuit noise simulations.

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Statistical Model for the Circuit Bandwidth Dependence of Low-Frequency Noise in Deep-Submicrometer MOSFETs

Cited by 25 publications

References 14 publications

Logarithmic modeling of BTI under dynamic circuit operation: Static, dynamic and long-term prediction

Logarithmic modeling of BTI under dynamic circuit operation: Static, dynamic and long-term prediction

Estimating time constants of the RTS noise in semiconductor devices: a complete description of the observation window in the time domain

Model Implementation of Lorentzian Spectra for Circuit Noise Simulations in the Frequency Domain

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