FUNDAMENTAL ISSUE IN SPACE ELECTRONICS RELIABILITY: NEGATIVE BIAS TEMPERATURE INSTABILITY

Negative Bias Temperature Instability (NBTI) in silicon based metal-oxide-semiconductor-field-effect-transistors (MOSFETs) has been recognized as a critical reliability issue for advanced space qualified electronics. The phenomenon manifests itself as a modification of threshold voltage (Vth) resulting in degraded signal timing paths, and ultimately circuit failure. Despite the obvious importance of the issue, a standard measurement protocol has yet to be determined. This is a consequence of a large amount of complexity introduced by the strong dependencies of NBTI on temperature, electric field, frequency, duty cycle, and gate dielectric composition. We have improved upon the traditional measurement techniques which suffered from an underestimation of the magnitude of Vth shifts because they failed to account for trapped charge relaxation. Specifically, we have developed a means for measuring the maximum effect of NBTI by virtue of a method that can continuously monitor the Vth(t) without having to remove the stressing voltage. The interpretation methodology for this technique is explained in detail and the relevant approximations are justified. We have evidenced temperature and vertical electric field dependent Vth shifts in SiO2 and HfSiON devices. Furthermore, we have collected substantial evidence that the traditional \uf044Vth=At\uf061 analysis fails to explain the experimental data in the early time domain. Finally, we have discovered that \uf044Vth(t) on p-channel field effect transistors with HfSiON gate dielectrics is dependent upon the magnitude of Vds during the stressing cycle. To our knowledge this is not anticipated by any prior modeling attempts. We justify the exclusion of short channel effects as a possibility, leading us to conclude that positive charge in the dielectric stack is laterall

Design of a reliability methodology: Modelling the influence of temperature on gate Oxide reliability

An Integrated Reliability Methodology (IRM) is presented that encompasses the changes that technology growth has brought with it and includes several new device degradation models. Each model is based on a physics of failure approach and includes on the effects of temperature. At all stages the models are verified experimentally on modern deep sub-micron devices. The research provides the foundations of a tool which gives the user the opportunity to make appropriate trade-offs between performance and reliability, and that can be implemented in the early stages of product development

On variability and reliability of poly-Si thin-film transistors

In contrast to conventional bulk-silicon technology, polysilicon (poly-Si) thin-film transistors (TFTs) can be implanted in flexible substrate and can have low process temperature. These attributes make poly-Si TFT technology more attractive for new applications, such as flexible displays, biosensors, and smart clothing. However, due to the random nature of grain boundaries (GBs) in poly-Si film and self-heating enhanced negative bias temperature instability (NBTI), the variability and reliability of poly-Si TFTs are the main obstacles that impede the application of poly-Si TFTs in high-performance circuits. The primary focus of this dissertation is to develop new design methodologies and modeling techniques for facilitating new applications of poly-Si TFT technology. In order to do that, a physical model is first presented to characterize the GB-induced transistor threshold voltage (V th)variations considering not only the number but also the position and orientation of each GB in 3-D space. The fast computation time of the proposed model makes it suitable for evaluation of GB-induced transistor Vthvariation in the early design phase. Furthermore, a self-consistent electro-thermal model that considers the effects of device geometry, substrate material, and stress conditions on NBTI is proposed. With the proposed modeling methodology, the significant impacts of device geometry, substrate, and supply voltage on NBTI in poly-Si TFTs are shown. From a circuit design perspective, a voltage programming pixel circuit is developed for active-matrix organic light emitting diode (AMOLED) displays for compensating the shift of Vth and mobility in driver TFTs as well as compensating the supply voltage degradation. In addition, a self-repair design methodology is proposed to compensate the GB-induced variations for liquid crystal displays (LCDs) and AMOLED displays. Based on the simulation results, the proposed circuit can decrease the required supply voltage by 20% without performance and yield degradation. In the final section of this dissertation, an optimization methodology for circuit-level reliability tests is explored. To effectively predict circuit lifetime, accelerated aging (i.e. elevated voltage and temperature) is commonly applied in circuit-level reliability tests, such as constant voltage stress (CVS) and ramp voltage stress (RVS) tests. However, due to the accelerated aging, shifting of dominant degradation mechanism might occur leading to the wrong lifetime prediction. To get around this issue, we proposed a technique to determine the proper stress range for accelerated aging tests

As-grown-Generation (A-G) Model for Positive Bias Temperature Instability (PBTI)

Positive Bias Temperature Instability (PBTI) is poised to cause significant degradation to nFETs with deep scaling into nanometers. It is commonly modelled by a power law fitted with measured threshold voltage shift. For the first time, this work shows that such models do not warrant PBTI prediction outside the stress conditions used for the fitting. The underlying cause for this failure is the errors in the extracted power exponent. Based on the understanding of different types of defects, we develop a robust As-grown-Generation (A-G) model and demonstrate its capability for accurate prediction of PBTI under both DC and AC conditions. The generation-induced degradation is found to play a key role. Analysis reveals that, although PBTI is usually smaller than NBTI within the typical test time window, it can exceed NBTI by the end of device lifetime

Reliability of HfO2-Based Ferroelectric FETs: A Critical Review of Current and Future Challenges

Ferroelectric transistors (FeFETs) based on doped hafnium oxide (HfO2) have received much attention due to their technological potential in terms of scalability, highspeed, and low-power operation. Unfortunately, however, HfO2-FeFETs also suffer from persistent reliability challenges, specifically affecting retention, endurance, and variability. A deep understanding of the reliability physics of HfO2-FeFETs is an essential prerequisite for the successful commercialization of this promising technology. In this article, we review the literature about the relevant reliability aspects of HfO2-FeFETs. We initially focus on the reliability physics of ferroelectric capacitors, as a prelude to a comprehensive analysis of FeFET reliability. Then, we interpret key reliability metrics of the FeFET at the device level (i.e., retention, endurance, and variability) based on the physical mechanisms previously identified. Finally, we discuss the implications of device-level reliability metrics at both the circuit and system levels. Our integrative approach connects apparently unrelated reliability issues and suggests mitigation strategies at the device, circuit, or system level. We conclude this article by proposing a set of research opportunities to guide future development in this field

Bias Temperature Instability Modelling and Lifetime Prediction on Nano-scale MOSFETs

Bias Temperature Instability (BTI) is one of the most important reliability concerns for Metal Oxide Semiconductor Field Effect Transistors (MOSFET), the basic unit in integrated circuits. As the development MOSFET manufacturing technology, circuit designers need to consider device reliability during design optimization. An accurate BTI lifetime prediction methodology becomes a prerequisite. Typical BTI lifetime standard is ten years, accelerated BTI tests under high stress voltages are mandatory. BTI modelling is needed to project BTI lifetime from high voltages (accelerated condition) to operating voltage. The existing two mainstream BTI models: 1). The Reaction-Diffusion (R-D) framework and 2). The Two-Stage model cannot provide accurate lifetime prediction. Quite a few fitting parameters and unjustifiable empirical equations are needed in the R-D framework to predict the lifetime, questioning its predicting capability. The Two-stage model cannot project device lifetime from high voltages to operating voltage. Moreover, the scaling down of MOSFET feature size brings new challenges to nano-scale device lifetime prediction: 1). Nano-scale devices’ current is fluctuating due to the impact of a single charge is increasing as MOSFET scaling down, repetitive tests need to be done to achieve meaningful averaged results; 2). Nano-scale devices have significant Device-to-Device variability, making the lifetime a distribution instead of a single value. In this work a comprehensive As-grown Generation (A-G) framework based on the A-G model and defect centric theory is proposed and successfully predicts the Time Dependent Variability and lifetime on nano-scale devices. The predicting capability is validated by the good agreement between the test data and predicted values. It is speculated that the good predicting capability is due to the correct understanding of different types of defects. In the A-G framework, Time Dependent Variability is experimentally separated into Within-Device Fluctuation and the averaged degradation. Within-Device Fluctuation can be directly measured and the averaged degradation can be modelled using the A-G model. The averaged degradation in the A-G model contains: Generated Defects, As-grown Traps and Energy Alternating Defects. These defects have different kinetics against stress time thus need separate modelling. Various patterns such as Stress-Discharge-Recharge, multi-Discharging-based Multiple Pulses are designed to experimentally separate these defects based on their different charging/discharging properties. Fast-Voltage Step Stress technique is developed to reduce the testing time by 90% for the A-G framework parameter extraction, making the framework practical for potential use in industry

Opto-Electro-Thermal Approach to Modeling Photovoltaic Performance and Reliability from Cell to Module

Thanks to technology advancement in recent decades, the levelized cost of electricity (LCOE) of solar photovoltaics (PV) has finally been driven down close to that of traditional fossil fuels. Still, PV only provides approximately 0.5% of the total electricity consumption in the United States. To make PV more competitive with other energy resources, we must continuously reduce the LCOE of PV through improving their performance and reliability. As PV efficiencies approach the theoretical limit, however, further improvements are difficult. Meanwhile, solar modules in the field regularly fail prematurely before the manufacturers 25-year warranty. Therefore, future PV research needs innovative approaches and inventive solutions to continuously drive LCOE down. In this work, we present a novel approach to PV system design and analysis. The approach, comprised of three components: multiscale, multiphysics, and time, aims at systemically and collaboratively improving the performance and reliability of PV. First, we establish a simulation framework for translating the cell-level characteristics to the module level (multiscale). This framework has been demonstrated to reduce the cell-to-module efficiency gap. The framework also enables the investigation of module-level reliability. Physics-based compact models -the building blocks for this multiscale framework are, however, still missing or underdeveloped for promising materials such as perovskites and CIGS. Hence, we have developed compact models for these two technologies, which analytically describe salient features of their operation as a function of illumination and temperature. The models are also suitable for integration into a large-scale circuit network to simulate a solar module. In the second aspect of the approach, we study the fundamental physics underlying the notorious self-heating effects for PV and examine their detrimental influence on the electrical performance (multiphysics). After ascertaining the sources of self-heating, we propose novel optics-based self-cooling methodologies to reduce the operating temperature. The cooling technique developed in this work has been predicted to substantially enhance the efficiency and durability of commercial Si solar modules. In the third and last aspect of the approach, we have established a simulation framework that can forward predict the future energy yield for PV systems for financial scrutiny and inversely mine the historical field data to diagnose the pathology of degraded solar modules (time). The framework, which physically accounts for environmental factors (e.g., irradiance, temperature), can generate accurate projection and insightful analysis of the geographic-and technology-specific performance and reliability of solar modules. For the forward modeling, we simulate the optimization and predict the performance of bifacial solar modules to rigorously evaluate this emerging technology in a global context. For the inverse modeling, we apply this framework to physically mine the 20-year field data for a nearly worn-out silicon PV system and successfully pin down the primary degradation pathways, something that is beyond the capability of conventional methods. This framework can be applied to solar farms installed globally (an abundant yet unexploited testbed) to establish a rich database of these geographic-and technology-dependent degradation processes, a knowledge prerequisite for the next-generation reliability-aware design of PV systems. Finally, we note that the research paradigm for PV developed in this work can also be applied to other applications, e.g., battery and electronics, which share similar technical challenges for performance and reliability

Experimental Characterization of Random Telegraph Noise and Hot Carrier Aging of Nano-scale MOSFETs

One of the emerging challenges in the scaling of MOSFETs is the reliability of ultra-thin gate dielectrics. Various sources can cause device aging, such as hot carrier aging (HCA), negative bias temperature instability (NBTI), positive bias temperature instability (PBTI), and time dependent device breakdown (TDDB). Among them, hot carrier aging (HCA) has attracted much attention recently, because it is limiting the device lifetime. As the channel length of MOSFETs becomes smaller, the lateral electrical field increases and charge carriers become sufficiently energetic (“hot”) to cause damage to the device when they travel through the space charge region near the drain. Unlike aging that causes device parameters, such as threshold voltage, to drift in one direction, nano-scale devices also suffer from Random Telegraph Noise (RTN), where the current can fluctuate under fixed biases. RTN is caused by capturing/emitting charge carriers from/to the conduction channel. As the device sizes are reduced to the nano-meters, a single trap can cause substantial fluctuation in the current and threshold voltage. Although early works on HCA and RTN have improved the understanding, many issues remain unresolved and the aim of this project is to address these issues. The project is broadly divided into three parts: (i) an investigation on the HCA kinetics and how to predict HCA-induced device lifetime, (ii) a study of the interaction between HCA and RTN, and (iii) developing a new technique for directly measuring the RTN-induced jitter in the threshold voltage. To predict the device lifetime, a reliable aging kinetics is indispensable. Although early works show that HCA follows a power law, there are uncertainties in the extraction of the time exponent, making the prediction doubtful. A systematic experimental investigation was carried out in Chapter 4 and both the stress conditions and measurement parameters were carefully selected. It was found that the forward saturation current, commonly used in early work for monitoring HCA, leads to an overestimation of time exponents, because part of the damaged region is screened off by the space charges near the drain. Another source of errors comes from the inclusion of as-grown defects in the aging kinetics, which is not caused by aging. This leads to an underestimation of the time exponent. After correcting these errors, a reliable HCA kinetics is established and its predictive capability is demonstrated. There is confusion on how HCA and RTN interact and this is researched into in Chapter 5. The results show that for a device of average RTN, HCA only has a modest impact on RTN. RTN can either increase or decrease after HCA, depending on whether the local current under the RTN traps is rising or reducing. For a device of abnormally high RTN, RTN reduces substantially after HCA and the mechanism for this reduction is explored. The RTN-induced threshold voltage jitter, ∆Vth, is difficult to measure, as it is typically small and highly dynamic. Early works estimate this ∆Vth from the change in drain current and the accuracy of this estimation is not known. Chapter 6 focuses on developing a new ‘Trigger-When-Charged’ technique for directly measuring the RTN-induced ∆Vth. It will be shown that early works overestimate ∆Vth by a factor of two and the origin of this overestimation is investigated. This thesis consists of seven chapters. Chapter 1 introduces the project and its objectives. A literature review is given in Chapter 2. Chapter 3 covers the test facilities, measurement techniques, and devices used in this project. The main experimental results and analysis are given in Chapters 4-6, as described above. Finally, Chapter 7 concludes the project and discusses future works