Response of a single trap to AC negative Bias Temperature stress

Toledano-Luque, M.; Kaczer, B.; Roussel, Ph.; Grasser, T.; Wirth, Gilson; Franco, J.; Vrancken, C.; Horiguchi, N.; Groeseneken, G.

doi:10.1109/irps.2011.5784501

Cited by 59 publications

(57 citation statements)

References 16 publications

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“…The analytic CET map uses a recoverable (R) and a permanent (P) component, both of which are represented by bivariate normal distributions for the effective activation energies of the correlated capture and emission times. Given recent experimental evidence [21,24,[32][33][34], all time constants are assumed to be thermally activated,…”

Section: Capture/emission Time Map Model For Btimentioning

confidence: 99%

“…In particular, this implies that the predictions of the DC and lowfrequency behavior are not affected by this extension of the model, provided the stress and relaxation times are larger than τ c1 and τ e1 . As with the two-state model [7,33], the response of the three-state defect to an AC signal can be evaluated in closed form, without the tedious requirement to resolve millions of cycles. While the derivation of the expressions is rather cumbersome compared to the elegant and simple solution of the two-state defect, they lead to a very simple results.…”

Section: Advanced Cet Map Modelmentioning

confidence: 99%

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On the frequency dependence of the bias temperature instability

Kaczer

Reisinger

Wagner

et al. 2012

2012 IEEE International Reliability Physics Symposium (IRPS)

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Abstract-An accurate understanding of the duty-factor and frequency dependence of the bias temperature instability (BTI) is essential since it can transfer to significant lifetime benefits. Contradictory reports regarding the frequency dependence have been published in literature, with particularly older studies and those interpreted in the framework of the reaction-diffusion model claiming BTI to be frequency-independent. Newer studies, on the other hand, clearly show a frequency-dependent component of BTI. Here we discuss this frequency dependence using the recently suggested capture/emission time map model, which explains BTI as a collection of a large number of independent first-order reactions of defects with two states. While this model can explain most features observed in DC and low-frequency AC stress experiments, it does not fully capture the experimentally observed frequency and duty-factor dependence. However, when a more accurate defect model is considered, which describes charging of the defect via an intermediate state, good accuracy with experimental data is obtained.

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Section: Capture/emission Time Map Model For Btimentioning

confidence: 99%

Section: Advanced Cet Map Modelmentioning

confidence: 99%

On the frequency dependence of the bias temperature instability

Kaczer

Reisinger

Wagner

et al. 2012

2012 IEEE International Reliability Physics Symposium (IRPS)

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“…From the former approach, a new technique named time dependent defect spectroscopy (TDDS) [6] has been developed allowing the study of the kinetic properties of single defects as a function of stress/recovery bias conditions and temperature [4,[18][19][20][21]. These studies have revealed interesting facts about the charge trapping component that we summarize in the next section.…”

Section: Bias Temperature Instability Bti In Large and In Nm-scaled Dmentioning

confidence: 99%

Defect-centric perspective of time-dependent BTI variability

Toledano-Luque

Kaczer

Franco

et al. 2012

Microelectronics Reliability

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“…Only occupied defects make contributions to the device threshold voltage. Following the models in [7], the timing characteristics of each defect corresponding to the charge trapping and detrapping events, namely the capture and emission time and , are strongly dependent on voltage and temperature. In digital circuits, the voltage dependence effect is simplified by the fact that there are only two nontransient voltage stageslogic 1 and logic 0 -corresponding to two static modes of stress and relaxation.…”

Section: A Bti Variability Under Charge Trapping Modelmentioning

confidence: 99%

“…The occupancy probability (i.e., the probability of charge trapping) of a single defect under AC stress is derived in [7] to be a function of total time t and duty factor DF as follows, , , * * * 1 exp 1…”

Section: A Bti Variability Under Charge Trapping Modelmentioning

confidence: 99%

Understanding the impact of transistor-level BTI variability

Fang

Sapatnekar

2012

2012 IEEE International Reliability Physics Symposium (IRPS)

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Abstract-Recent work has shown large variations due to biastemperature instability (BTI) at the device level, and we study its impact on the behavior of larger circuits. We propose an analytical method that is over 600x faster than Monte Carlo simulation and accurate for technologies down to 16nm, and demonstrate it on circuits with up to 68,000 transistors. Results show that the impact of BTI variability at the circuit level is significantly smaller than at the device level, but increases with device downscaling.

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Response of a single trap to AC negative Bias Temperature stress

Cited by 59 publications

References 16 publications

On the frequency dependence of the bias temperature instability

On the frequency dependence of the bias temperature instability

Defect-centric perspective of time-dependent BTI variability

Understanding the impact of transistor-level BTI variability

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