A two-stage model for negative bias temperature instability

Grasser, T.; Kaczer, B.; Goes, Wolfgang; Aichinger, Thomas; Hehenberger, Ph.; Nelhiebel, Michael

doi:10.1109/irps.2009.5173221

Cited by 193 publications

(177 citation statements)

References 46 publications

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“…In [5], a model for the charge trapping component of NBTI based on multiphonon theory has been suggested using established features of switching traps (possibly E' centers). According to this model, the logarithmic time dependence is the result of a superposition of individual defects with widely distributed characteristic time constants charging (during stress) and discharging (during recovery) according to exp(−t/τ).…”

Section: Theorymentioning

confidence: 99%

“…In general, with increasing bias and temperature, the time constants become shorter, that is, charge capture and emission are accelerated by bias and temperature. The temperature activation is expected to follow an Arrhenius behavior [5,6,8].…”

Section: Theorymentioning

confidence: 99%

“…1 and 2 show simulation results using the recently suggested two-stage model for NBTI which explains the hole trapping component by a switching trap model [5]. The model was calibrated to data obtained on devices with EOT ~1.4 nm SiON in the temperature range 298K to 473K and −0.6V to −2.0V.…”

Section: Theorymentioning

confidence: 99%

“…Conventionally, this hole trapping has been analyzed using elastic tunneling theory which predicts it to be temperatureindependent [2][3][4]. However, recent results clearly indicate that the hole trapping component contributing to NBTI is thermally activated, which is incompatible with elastic tunneling [5]. Rather, the recorded data are consistent with hole capture according to multiphonon theory [6][7][8].…”

Section: Introductionmentioning

confidence: 99%

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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: Theorymentioning

confidence: 99%

Section: Theorymentioning

confidence: 99%

Section: Theorymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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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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“…Several NBTI models have been proposed, such as the two-stage model [9], reaction-diffusion (RD) based framework [10,11], the composite model [12], and the as-grown-generation (AG) model [13][14][15][16][17]. In order to verify their correctness, a common practice is to demonstrate that they can fit the test data well.…”

Section: Introductionmentioning

confidence: 99%

The as-grown-generation (AG) model: A reliable model for reliability prediction under real use conditions

Zhang

2017

2017 IEEE 24th International Symposium on the Physical and Failure Analysis of Integrated Circuits (IPFA)

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Abstract-Modeling the negative bias temperature instability (NBTI) can optimize circuit design. Several models have been proposed and all of them can fit test data well. These models are extracted typically by fitting short accelerated stress data. Their capability to predict NBTI aging outside the test range has not been fully demonstrated. This predictive capability for long term aging under low operation bias is what needed by circuit designers. In this work, we test the predictive capability of the well-known reaction-diffusion (RD) based framework for samples fabricated by a variety of processes. Results show that the RD model cannot make an acceptable generic prediction. The recently proposed As-grown-Generation (AG) model is then introduced. By dividing defects into two groups, as-grown and generated defects, and measuring the as-grown defects experimentally, we demonstrate that it can make reliable prediction for the same set of data where the RD model failed.

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