A Comparison of Very Fast to Very Slow Components in Degradation and Recovery Due to NBTI and Bulk Hole Trapping to Existing Physical Models

Reisinger, H.; Blank, Oliver; Heinrigs, W.; Gustin, Wolfgang; Schlunder, C.

doi:10.1109/tdmr.2007.898229

Cited by 70 publications

(51 citation statements)

References 30 publications

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“…During stress, even with a measurement resolution of 1µs, the degradation takes place outside the measurement range [10]. Similarly, during recovery, discharging occurs earlier than the measurement window [11,12]. We remark that reports exist claiming that the minimum time constants are in the order of 1µs [13,14]; however, this is not in agreement with other data that show degradation and recovery are already in full flight at 1µs [10][11][12].…”

Section: Theorycontrasting

confidence: 81%

On the thermal activation of negative bias temperature instability

Southwick

Knowlton

Kaczer

2009

2009 IEEE International Integrated Reliability Workshop Final Report

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The temperature dependence of negative bias temperature instability (NBTI) is investigated on 2.0nm SiO 2 devices from temperatures ranging from 300K down to 6K with a measurement window of ~12ms to 100s. Results indicate that classic NBTI degradation is observed down to ~200K and rarely observed at temperatures below 140K in the experimental window. Since experimental results show the charge trapping component contributing to NBTI is thermally activated, the results cannot be explained with the conventionally employed elastic tunneling theory. A new mechanism is observed at temperatures below 200K where device performance during stress conditions improves rather than degrades with time, which is opposite to the "classical" NBTI phenomenon.

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Section: Theorycontrasting

confidence: 81%

On the thermal activation of negative bias temperature instability

Southwick

Knowlton

Kaczer

2009

2009 IEEE International Integrated Reliability Workshop Final Report

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“…Based on the drawbacks identified from these models, as well as observations from several publications such as [19], [20], [24], we present some key guidelines for an NBTI model as follows:…”

Section: A Guidelines For An Nbti Modelmentioning

confidence: 99%

“…4) For an AC stress case where the stress duration is equal to the relaxation time period, the model must predict larger fractional recovery, with lower stress times [20]. Previous works using an NBTI model [4], [15] and numerical solutions of the model in [17], [19] all predict 50% recovery, when the ratio of the relaxation time to the stress time is equal to one, irrespective of the actual duration of the stress time. 5) The model must predict some form of frequency independence, i.e., the number of interface traps generated must approximately be the same asymptotically, irrespective of the frequency of operation.…”

Section: A Guidelines For An Nbti Modelmentioning

confidence: 99%

“…UFM-based techniques, which can measure the V th degradation during the recovery phase, within 1µs after removal of the stress, have been employed in [18], [19]. Experimental results show that there is a uniform recovery of V th during the relaxation phase, with an almost identical amount of fractional recovery in every decade.…”

Section: B a Note On Otfm And Ufm Techniques And Validity Of The R-dmentioning

confidence: 99%

“…Experimental results show that there is a uniform recovery of V th during the relaxation phase, with an almost identical amount of fractional recovery in every decade. Subsequently, [17], [19] show results comparing the large differences between an R-D theory-based model for recovery, and the experimental data, suggesting that the R-D mechanism does not provide a satisfactory explanation for the physical action during recovery. Further, [17] explains the various drawbacks of the R-D theory-based analytical model proposed by Alam in [4], such as: 1) 50% recovery in V th predicted after τ seconds of recovery, following τ seconds of stress, irrespective of the value of τ , whereas experimental results show a dependence on τ , particularly with smaller values of τ producing larger fractional recovery.…”

Section: B a Note On Otfm And Ufm Techniques And Validity Of The R-dmentioning

confidence: 99%

See 2 more Smart Citations

A Finite-Oxide Thickness-Based Analytical Model for Negative Bias Temperature Instability

Kumar

Kim

Sapatnekar

2009

IEEE Trans. Device Mater. Relib.

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Abstract-Negative Bias Temperature Instability (NBTI) in PMOS transistors has become a serious reliability concern in present day digital circuit design. With continued technology scaling, and reducing oxide thickness, it has become imperative to accurately determine its effects on temporal circuit degradation, and thereby ensure reliable operation for a finite period of time. A reaction-diffusion (R-D) based framework is developed for determining the number of interface traps as a function of time, for both the DC (static NBTI) and the AC (dynamic NBTI) stress cases. The effects of finite oxide thickness, and the influence of trap generation and annealing in polysilicon, are incorporated. The model provides a good fit with experimental data, and also provides a satisfying explanation for most of the physical effects associated with the dynamics of NBTI. A generalized framework for estimating the impact of NBTI-induced temporal degradation in present day digital circuits, is also discussed.

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Perspective of 2D Integrated Electronic Circuits: Scientific Pipe Dream or Disruptive Technology?

et al. 2022

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Within the last decade, considerable efforts have been devoted to fabricating transistors utilizing 2D semiconductors. Also, small circuits consisting of a few transistors have been demonstrated, including inverters, ring oscillators, and static random access memory cells. However, for industrial applications, both time‐zero and time‐dependent variability in the performance of the transistors appear critical. While time‐zero variability is primarily related to immature processing, time‐dependent drifts are dominated by charge trapping at defects located at the channel/insulator interface and in the insulator itself, which can substantially degrade the stability of circuits. At the current state of the art, 2D transistors typically exhibit a few orders of magnitude higher trap densities than silicon devices, which considerably increases their time‐dependent variability, resulting in stability and yield issues. Here, the stability of currently available 2D electronics is carefully evaluated using circuit simulations to determine the impact of transistor‐related issues on the overall circuit performance. The results suggest that while the performance parameters of transistors based on certain material combinations are already getting close to being competitive with Si technologies, a reduction in variability and defect densities is required. Overall, the criteria for parameter variability serve as guidance for evaluating the future development of 2D technologies.

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A Comparison of Very Fast to Very Slow Components in Degradation and Recovery Due to NBTI and Bulk Hole Trapping to Existing Physical Models

Cited by 70 publications

References 30 publications

On the thermal activation of negative bias temperature instability

On the thermal activation of negative bias temperature instability

A Finite-Oxide Thickness-Based Analytical Model for Negative Bias Temperature Instability

Perspective of 2D Integrated Electronic Circuits: Scientific Pipe Dream or Disruptive Technology?

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