On the Modeling of the Donor/Acceptor Compensation Ratio in Carbon‐Doped GaN to Univocally Reproduce Breakdown Voltage and Current Collapse in Lateral GaN Power HEMTs

The intentional doping of lateral GaN power high electron mobility transistors (HEMTs) with carbon (C) impurities is a common technique to reduce buffer conductivity and increase breakdown voltage. Due to the introduction of trap levels in the GaN bandgap, it is well known that these impurities give rise to dispersion, leading to the so‐called “current collapse” as a collateral effect. Moreover, first‐principles calculations and experimental evidence point out that C introduces trap levels of both acceptor and donor types. Here, we report on the modeling of the donor/acceptor compensation ratio (CR), that is, the ratio between the density of donors and acceptors associated with C doping, to consistently and univocally reproduce experimental breakdown voltage (VBD) and current‐collapse magnitude (ΔICC). By means of calibrated numerical device simulations, we confirm that ΔICC is controlled by the effective trap concentration (i.e., the difference between the acceptor and donor densities), but we show that it is the total trap concentration (i.e., the sum of acceptor and donor densities) that determines VBD, such that a significant CR of at least 50% (depending on the technology) must be assumed to explain both phenomena quantitatively. The results presented in this work contribute to clarifying several previous reports, and are helpful to device engineers interested in modeling C‐doped lateral GaN power HEMTs

High-Density Solid-State Memory Devices and Technologies

This Special Issue aims to examine high-density solid-state memory devices and technologies from various standpoints in an attempt to foster their continuous success in the future. Considering that broadening of the range of applications will likely offer different types of solid-state memories their chance in the spotlight, the Special Issue is not focused on a specific storage solution but rather embraces all the most relevant solid-state memory devices and technologies currently on stage. Even the subjects dealt with in this Special Issue are widespread, ranging from process and design issues/innovations to the experimental and theoretical analysis of the operation and from the performance and reliability of memory devices and arrays to the exploitation of solid-state memories to pursue new computing paradigms

A simple figure of merit to identify the first layer to degrade and fail in dual layer SiOx/HfO2 gate dielectric stacks

Understanding the degradation dynamics and the breakdown sequence of a bilayer high-k (HK) gate dielectric stack is crucial for the improvement of device reliability. We present a new Figure of Merit (FoM), the IL/HK Degradation Index, that depends on fundamental materials properties (the dielectric breakdown strength and the dielectric constant) and can be used to easily and quickly identify the first layer to degrade and fail in a bilayer SiO2/HK dielectric stack. Its dependence on IL and HK material parameters is investigated and its validity is demonstrated by means of accurate physics-based simulations of the degradation process. The proposed FoM can be easily used to understand the degradation dynamics of the gate dielectric stack, providing critical insights for device reliability improvement

Modulating the Filamentary-Based Resistive Switching Properties of HfO2 Memristive Devices by Adding Al2O3 Layers

The resistive switching properties of HfO2 based 1T-1R memristive devices are electrically modified by adding ultra-thin layers of Al2 O3 into the memristive device. Three different types of memristive stacks are fabricated in the 130 nm CMOS technology of IHP. The switching properties of the memristive devices are discussed with respect to forming voltages, low resistance state and high resistance state characteristics and their variabilities. The experimental I–V characteristics of set and reset operations are evaluated by using the quantum point contact model. The properties of the conduction filament in the on and off states of the memristive devices are discussed with respect to the model parameters obtained from the QPC fit

Multiscale modeling for application-oriented optimization of resistive random-access memory

Memristor-based neuromorphic systems have been proposed as a promising alternative to von Neumann computing architectures, which are currently challenged by the ever-increasing computational power required by modern artificial intelligence (AI) algorithms. The design and optimization of memristive devices for specific AI applications is thus of paramount importance, but still extremely complex, as many dierent physical mechanisms and their interactions have to be accounted for, which are, in many cases, not fully understood. The high complexity of the physical mechanisms involved and their partial comprehension are currently hampering the development of memristive devices and preventing their optimization. In this work, we tackle the application-oriented optimization of Resistive Random-Access Memory (RRAM) devices using a multiscale modeling platform. The considered platform includes all the involved physical mechanisms (i.e., charge transport and trapping, and ion generation, diusion, and recombination) and accounts for the 3D electric and temperature field in the device. Thanks to its multiscale nature, the modeling platform allows RRAM devices to be simulated and the microscopic physical mechanisms involved to be investigated, the device performance to be connected to the material's microscopic properties and geometries, the device electrical characteristics to be predicted, the effect of the forming conditions (i.e., temperature, compliance current, and voltage stress) on the device's performance and variability to be evaluated, the analog resistance switching to be optimized, and the device's reliability and failure causes to be investigated. The discussion of the presented simulation results provides useful insights for supporting the application-oriented optimization of RRAM technology according to specific AI applications, for the implementation of either non-volatile memories, deep neural networks, or spiking neural networks

Miniaturized Transistors, Volume II

In this book, we aim to address the ever-advancing progress in microelectronic device scaling. Complementary Metal-Oxide-Semiconductor (CMOS) devices continue to endure miniaturization, irrespective of the seeming physical limitations, helped by advancing fabrication techniques. We observe that miniaturization does not always refer to the latest technology node for digital transistors. Rather, by applying novel materials and device geometries, a significant reduction in the size of microelectronic devices for a broad set of applications can be achieved. The achievements made in the scaling of devices for applications beyond digital logic (e.g., high power, optoelectronics, and sensors) are taking the forefront in microelectronic miniaturization. Furthermore, all these achievements are assisted by improvements in the simulation and modeling of the involved materials and device structures. In particular, process and device technology computer-aided design (TCAD) has become indispensable in the design cycle of novel devices and technologies. It is our sincere hope that the results provided in this Special Issue prove useful to scientists and engineers who find themselves at the forefront of this rapidly evolving and broadening field. Now, more than ever, it is essential to look for solutions to find the next disrupting technologies which will allow for transistor miniaturization well beyond silicon’s physical limits and the current state-of-the-art. This requires a broad attack, including studies of novel and innovative designs as well as emerging materials which are becoming more application-specific than ever before

Aging-Aware Design Methods for Reliable Analog Integrated Circuits using Operating Point-Dependent Degradation

The focus of this thesis is on the development and implementation of aging-aware design methods, which are suitable to satisfy current needs of analog circuit design. Based on the well known \gm/\ID sizing methodology, an innovative tool-assisted aging-aware design approach is proposed, which is able to estimate shifts in circuit characteristics using mostly hand calculation schemes. The developed concept of an operating point-dependent degradation leads to the definition of an aging-aware sensitivity, which is compared to currently available degradation simulation flows and proves to be efficient in the estimation of circuit degradation. Using the aging-aware sensitivity, several analog circuits are investigated and optimized towards higher reliability. Finally, results are presented for numerous target specifications

Optimization of Multi-Level Operation in RRAM Arrays for In-Memory Computing

Accomplishing multi-level programming in resistive random access memory (RRAM) arrays with truly discrete and linearly spaced conductive levels is crucial in order to implement synaptic weights in hardware-based neuromorphic systems. In this paper, we implemented this feature on 4-kbit 1T1R RRAM arrays by tuning the programming parameters of the multi-level incremental step pulse with verify algorithm (M-ISPVA). The optimized set of parameters was assessed by comparing its results with a non-optimized one. The optimized set of parameters proved to be an effective way to define non-overlapped conductive levels due to the strong reduction of the device-to-device variability as well as of the cycle-to-cycle variability, assessed by inter-levels switching tests and during 1 k reset-set cycles. In order to evaluate this improvement in real scenarios, the experimental characteristics of the RRAM devices were captured by means of a behavioral model, which was used to simulate two different neuromorphic systems: an 8 × 8 vector-matrix-multiplication (VMM) accelerator and a 4-layer feedforward neural network for MNIST database recognition. The results clearly showed that the optimization of the programming parameters improved both the precision of VMM results as well as the recognition accuracy of the neural network in about 6% compared with the use of non-optimized parameters

High-Voltage Temperature Humidity Bias Test (HV-THB): Overview of Current Test Methodologies and Reliability Performances

2The high voltage temperature humidity bias test (HV-THB) has become increasingly popular for evaluating the performances of power semiconductor devices. Given the new challenges of the power semiconductor industry, several applications and devices need to be designed to withstand harsh environments during working operations, with a remarkable focus on high-humidity conditions. The HV-THB test allows one to activate and study different failure mechanisms which were not highlighted by the standard low voltage THB test, enabling new designs in several energy conversion fields, such as energy harvesting, industry and automotive applications. After a brief introduction of current test standards, this work goes through the current methodologies and state-of-the-art of the HV-THB test. The following sections are then dedicated to the knowledge about the failure mechanisms and the models for accelerated testing. Eventually, there is a section devoted to the main passivation materials in order to understand their effects on the HV-THB capabilities of the devices.openopenDavide Cimmino; Sergio FerreroCimmino, Davide; Ferrero, Sergi

MICROELECTRONIC RELIABILITY MODELS FOR MORE THAN MOORE NANOTECHNOLOGY PRODUCTS

Disruptive technologies face a lack of Reliability Engineering Standards and Physics of Failure (PoF) heritage. Devices based on GaN, SiC, Optoelectronics or Deep-Submicron nanotechnologies or 3D packaging techniques for example are suffering a vital absence of screening methods, qualification and reliability standards when anticipated to be used in Hi-Rel application. To prepare the HiRel industry for just-in-time COTS, reliability engineers must define proper and improved models to guarantee infant mortality free, long term robust equipment that is capable of surviving harsh environments without failure. Furthermore, time-to-market constraints require the shortest possible time for qualification. Breakthroughs technologies are generally industrialized for short life consumer application (typically smartphone or new PCs with less than 3 years lifecycle). How shall we qualify these innovative technologies in long term Hi-Rel equipment operation? More Than Moore law is the paradigm of updating what are now obsolete, inadequate screening methods and reliability models and Standards to meet these demands. A State of the Art overview on Quality Assurance, Reliability Standards and Test Methods is presented in order to question how they must be adapted, harmonized and rearranged. Here, we quantify failure rate models formulated for multiple loads and incorporating multiple failure mechanisms to disentangle existing reliability models to fit the 4.0 industry needs