Yannick Wimmer

Predictive Hot-Carrier Modeling of n-Channel MOSFETs

We present a physics-based hot-carrier degradation (HCD) model and validate it against measurement data on SiON n-channel MOSFETs of various channel lengths, from ultrascaled to long-channel transistors. The HCD model is capable of representing HCD in all these transistors stressed under different conditions using a unique set of model parameters. The degradation is modeled as a dissociation of Si-H bonds induced by two competing processes. It can be triggered by solitary highly energetical charge carriers or by excitation of multiple vibrational modes of the bond. In addition, we show that the influence of electron-electron scattering (EES), the dipole-field interaction, and the dispersion of the Si-H bond energy are crucial for understanding and modeling HCD. All model ingredients are considered on the basis of a deterministic Boltzmann transport equation solver, which serves as the transport kernel of a physics-based HCD model. Using this model, we analyze the role of each ingredient and show that EES may only be neglected in long-channel transistors, but is essential in ultrascaled devices.

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

Recent studies have clearly shown that oxide defects are more complicated than typically assumed in simple two-state 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-functional-theory (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.

Gate-sided hydrogen release as the origin of "permanent" NBTI degradation: From single defects to lifetimes

The negative bias temperature instability (NBTI) in pMOS transistors is typically assumed to consist of a recoverable (R) and a so-called permanent (P) component. While R has been studied in great detail, the investigation of P is much more difficult due to the large time constants involved and the fact that P is almost always obscured by R. As such, it is not really clear how to measure P and whether it will in the end dominate device lifetime. We address these questions by introducing a pragmatic definition of P, which allows us to collect long-term data on both large and nanoscale devices. Our results suggest that (i) P is considerably smaller than R, (ii) that P is dominated by oxide rather than interface traps and therefore (iii) shows a very similar bias dependence as R, and finally (iv) that P is unlikely to dominate device lifetime. We argue that a hydrogen-release mechanism from the gate-side of the oxide, which has been suspected to cause reliability problems for a long time [1-6], is consistent with our data. Based on these results as well as our density-functional-theory (DFT) calculations we suggest a microscopic model to project the results to operating conditions.

The “permanent” component of NBTI revisited: Saturation, degradation-reversal, and annealing

While the defects constituting the recoverable component R of NBTI have been very well analyzed recently, the slower defects forming the more “permanent” component P are much less understood. Using a pragmatic definition for P, we study the evolution of P at elevated temperatures in the range 200°C to 350°C to accelerate these very slow processes. We demonstrate for the first time that P not only clearly saturates, with the saturation value depending on the gate bias, but also that the degradation at constant gate bias can also slowly reverse. Furthermore, at temperatures higher than about 300° C, a significant amount of additional defects is created, which are primarily uncharged around Vth but contribute strongly to P at higher VG. Our new data are consistent with our recently suggested hydrogen release model which will be studied in detail using newly acquired long-term data.

A predictive physical model for hot-carrier degradation in ultra-scaled MOSFETs

We present and validate a novel physics-based model for hot-carrier degradation. The model incorporates such essential ingredients as a superposition of the multivibrational bond dissociation process and single-carrier mechanism, dispersion of the bond-breakage energy, interaction of the electric field and the dipole moment of the bond, and electron-electron scattering. The main requirement is that the model has to be able to cover HCD observed in a family of MOSFETs of identical architecture but with different gate lengths under diverse stress conditions using a unique set of parameters.

Role of hydrogen in volatile behaviour of defects in SiO2-based electronic devices.

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.

Origins and implications of increased channel hot carrier variability in nFinFETs

Channel hot carrier (CHC) stress is observed to result in higher variability of degradation in deeply-scaled nFinFETs than bias temperature instability (BTI) stress. Potential sources of this increased variation are discussed and the intrinsic time-dependent variability component is extracted using a novel methodology based on matched pairs. It is concluded that in deeply-scaled devices, CHC-induced time-dependent distributions will be bimodal, pertaining to bulk charging and to interface defect generation, respectively. The latter, high-impact mode will control circuit failure fractions at high percentiles.

Modeling of Hot-Carrier Degradation in nLDMOS Devices: Different Approaches to the Solution of the Boltzmann Transport Equation

We propose two different approaches to describe carrier transport in n-laterally diffused MOS (nLDMOS) transistor and use the calculated carrier energy distribution as an input for our physical hot-carrier degradation (HCD) model. The first version relies on the solution of the Boltzmann transport equation using the spherical harmonics expansion method, while the second uses the simpler drift-diffusion (DD) scheme. We compare these two versions of our model and show that both approaches can capture HCD. We, therefore, conclude that in the case of nLDMOS devices, the DD-based variant of the model provides good accuracy and at the same time is computationally less expensive. This makes the DD-based version attractive for predictive HCD simulations of LDMOS transistors.

Advanced modeling of charge trapping: RTN, 1/f noise, SILC, and BTI

In the course of years, several models have been put forward to explain noise phenomena, bias temperature instability (BTI), and gate leakage currents amongst other reliability issues. Mostly, these models have been developed independently and without considering that they may be caused by the same physical phenomenon. However, new experimental techniques have emerged, which are capable of studying these reliability issue on a microscopic level. One of them is the time-dependent defect spectroscopy (TDDS). Its intensive use has led to several interesting findings, including the fact that the recoverable component of BTI is due to reaction-limited processes. As a consequence, a quite detailed picture of the processes governing BTI has emerged. Interestingly, this picture has also been found to match the observations made for other reliability issues, such as random telegraph noise, 1/f noise, as well as gate leakage currents. Furthermore, the findings based on TDDS have lead to the development of capture/emission time (CET) maps, which can be used to understand the dynamic response of the defects given their widely distributed parameters.

Physical modeling of hot-carrier degradation in nLDMOS transistors

Our physics-based HCD model has been validated using scaled CMOS transistors in our previous work. In this work we apply this model for the first time to a high-voltage nLDMOS device. For the calculation of the degrading behaviour the Boltzmann transport equation solver ViennaSHE is used which also requires high quality adaptive meshing. We discuss the influence of the different model components in the different device regions. Finally we compare the model to experimental degradation results and show that each one gives a significant contribution to the result and that all of them are needed in order to satisfactorily fit the experimental data.