Advanced Modeling of Oxide Defects

Goes, Wolfgang; Schanovsky, F.

doi:10.1007/978-1-4614-7909-3_16

Cited by 15 publications

(10 citation statements)

References 53 publications

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“…However, to the best of our knowledge, their properties are identical to those existing in the pristine sample, that is, they have similar capture and emission times. As such, they can also contribute to stressinduced leakage currents in a similar manner [42], thereby possibly contributing to progressive oxide breakdown. As such it appears to be better to speak of defect activation at preexisting precursor sites rather than the creation of completely new defects anywhere in the oxide.…”

Section: Defect Creation Vs Activationmentioning

confidence: 99%

On the volatility of oxide defects: Activation, deactivation, and transformation

Grasser

Wahl

Goes

et al. 2015

2015 IEEE International Reliability Physics Symposium

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Recent studies have clearly shown that oxide defects are more complicated than typically assumed in simple twostate models, which only consider a neutral and a charged state. In particular, oxide defects can be volatile, meaning that they can be deactivated and re-activated at the same site with the same properties. In addition, these defects can transform and change their properties. The details of all these processes are presently unknown and poorly characterized. Here we employ time-dependent defect spectroscopy (TDDS) to more closely study the changes occurring at the defect sites. Our findings suggest that these changes are ubiquitous and must be an essential aspect of our understanding of oxide defects. Using density-functionaltheory (DFT) calculations, we propose hydrogen-defect interactions consistent with our observations. Our results suggest that standard defect characterization methods, such as the analysis of random telegraph noise (RTN), will typically only provide a snapshot of the defect landscape which is subject to change anytime during device operation.

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Section: Defect Creation Vs Activationmentioning

confidence: 99%

On the volatility of oxide defects: Activation, deactivation, and transformation

Grasser

Wahl

Goes

et al. 2015

2015 IEEE International Reliability Physics Symposium

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“…Here, we summarize our recent efforts to explain the results obtained from TDDS measurements using an NMP model (whose details are published elsewhere [ 11 , 17 , 56 ]). This model provides us a more rigorous framework for the description of the charge-transfer process between the substrate and the oxide defects, and was introduced in the context of RTN and NBTI in the work of Grasser et al [ 11 , 26 ].…”

Section: Defect Characterizationmentioning

confidence: 99%

“…These correspond to the barriers and relaxation energies of the different processes shown in figure 4 . In addition to these parameters, the position of the trap in the oxide, the capture cross section and an attempt frequency should be specified to fully define the transitions [ 11 , 56 ]. These parameters are described in more detail later in the paper.…”

Section: Defect Characterizationmentioning

confidence: 99%

Role of hydrogen in volatile behaviour of defects in SiO ₂ -based electronic devices

et al. 2016

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Charge capture and emission by point defects in gate oxides of metal–oxide–semiconductor field-effect transistors (MOSFETs) strongly affect reliability and performance of electronic devices. Recent advances in experimental techniques used for probing defect properties have led to new insights into their characteristics. In particular, these experimental data show a repeated dis- and reappearance (the so-called volatility) of the defect-related signals. We use multiscale modelling to explain the charge capture and emission as well as defect volatility in amorphous SiO2 gate dielectrics. We first briefly discuss the recent experimental results and use a multiphonon charge capture model to describe the charge-trapping behaviour of defects in silicon-based MOSFETs. We then link this model to ab initio calculations that investigate the three most promising defect candidates. Statistical distributions of defect characteristics obtained from ab initio calculations in amorphous SiO2 are compared with the experimentally measured statistical properties of charge traps. This allows us to suggest an atomistic mechanism to explain the experimentally observed volatile behaviour of defects. We conclude that the hydroxyl-E′ centre is a promising candidate to explain all the observed features, including defect volatility.

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“…first-order processes. As has been shown [21,32], the fourstate defect model of Fig. 2 can be well approximated by such a first-order process, at least under quasi-DC stress conditions.…”

Section: The Wide Distributions: Large-area Devicesmentioning

confidence: 74%

“…Based on the extended TDDS data, a clear picture of the defect dynamics has emerged, which required us to go beyond the traditional two-state description [21,24,28,32], see 1'…”

Section: Individual Defects -Modelingmentioning

confidence: 99%

Characterization and modeling of charge trapping: From single defects to devices

Rzepa

Waltl

Goes

et al. 2014

2014 IEEE International Conference on IC Design &Amp; Technology

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Using time-dependent defect spectroscopy measurements on nanoscale MOSFETs, individual defects have been characterized in much greater detail than ever before. These studies have revealed the existence of metastable defect states which have a significant impact on the capture and emission time constants. For example, these defect states explain the large emission time constants observed in bias temperature measurements as well as the switching behavior of defects sensitive to gate bias changes towards accumulation. By carefully analyzing the properties of the defects contributing to random telegraph noise and the recoverable component of the bias temperature instability, it could be confirmed that both phenomena are due to the same type of defect. The most fundamental property of these defects is that their time constants are widely distributed, leading to the ubiquitous time and frequency dependence. By transferring this knowledge to large area devices, noise as well as the response to bias temperature stress and recovery can be understood in great detail.

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Advanced Modeling of Oxide Defects

Cited by 15 publications

References 53 publications

On the volatility of oxide defects: Activation, deactivation, and transformation

On the volatility of oxide defects: Activation, deactivation, and transformation

Role of hydrogen in volatile behaviour of defects in SiO ₂ -based electronic devices

Characterization and modeling of charge trapping: From single defects to devices

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Advanced Modeling of Oxide Defects

Cited by 15 publications

References 53 publications

On the volatility of oxide defects: Activation, deactivation, and transformation

On the volatility of oxide defects: Activation, deactivation, and transformation

Role of hydrogen in volatile behaviour of defects in SiO 2 -based electronic devices

Characterization and modeling of charge trapping: From single defects to devices

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Role of hydrogen in volatile behaviour of defects in SiO ₂ -based electronic devices