Research on radiation-tolerant electronics has increased rapidly over the past few years, resulting in many interesting approaches to modeling radiation effects and designing radiation-hardened integrated circuits and embedded systems. This research is strongly driven by the growing need for radiation-hardened electronics for space applications, high-energy physics experiments such as those on the Large Hadron Collider at CERN, and many terrestrial nuclear applications including nuclear energy and nuclear safety. With the progressive scaling of integrated circuit technologies and the growing complexity of electronic systems, their susceptibility to ionizing radiation has raised many exciting challenges, which are expected to drive research in the coming decade. In this book we highlight recent breakthroughs in the study of radiation effects in advanced semiconductor devices, as well as in high-performance analog, mixed signal, RF, and digital integrated circuits. We also focus on advances in embedded radiation hardening in both FPGA and microcontroller systems and apply radiation-hardened embedded systems for cryptography and image processing, targeting space applications.

This book collects a selection of papers presented at ELECTRIMACS 2019, the 13th international conference of the IMACS TC1 Committee, held in Salerno, Italy, on 21st-23rd May 2019. The conference papers deal with modelling, simulation, analysis, control, power management, design optimization, identification and diagnostics in electrical power engineering. The main application fields include electric machines and electromagnetic devices, power electronics, transportation systems, smart grids, electric and hybrid vehicles, renewable energy systems, energy storage, batteries, supercapacitors and fuel cells, and wireless power transfer. The contributions included in Volume 1 are particularly focused on electrical engineering simulation aspects and innovative applications.

This book describes machine learning-based new principles, methods of design and optimization of high-speed integrated circuits, included in one electronic system, which can exchange information between each other up to 128/256/512 Gbps speed. The efficiency of methods has been proven and is described on the examples of practical designs. This will enable readers to use them in similar electronic system designs. The author demonstrates newly developed principles and methods to accelerate communication between ICs, working in non-standard operating conditions, considering signal deviation compensation with linearity self-calibration. The observed circuit types also include but are not limited to mixed-signal, high performance heterogeneous integrated circuits as well as digital cores.

Advanced Field-Effect Transistors: Theory and Applications offers a fresh perspective on the design and analysis of advanced field-effect transistor (FET) devices and their applications. The text emphasizes both fundamental and new paradigms that are essential for upcoming advancement in the field of transistors beyond complementary metal–oxide–semiconductors (CMOS). This book uses lucid, intuitive language to gradually increase the comprehension of readers about the key concepts of FETs, including their theory and applications. In order to improve readers’ learning opportunities, Advanced Field-Effect Transistors: Theory and Applications presents a wide range of crucial topics: • Design and challenges in tunneling FETs • Various modeling approaches for FETs • Study of organic thin-film transistors • Biosensing applications of FETs • Implementation of memory and logic gates with FETs The advent of low-power semiconductor devices and related implications for upcoming technology nodes provide valuable insight into low-power devices and their applicability in wireless, biosensing, and circuit aspects. As a result, researchers are constantly looking for new semiconductor devices to meet consumer demand. This book gives more details about all aspects of the low-power technology, including ongoing and prospective circumstances with fundamentals of FET devices as well as sophisticated low-power applications.

This Springer Handbook comprehensively covers the topic of semiconductor devices, embracing all aspects from theoretical background to fabrication, modeling, and applications. Nearly 100 leading scientists from industry and academia were selected to write the handbook's chapters, which were conceived for professionals and practitioners, material scientists, physicists and electrical engineers working at universities, industrial R&D, and manufacturers. Starting from the description of the relevant technological aspects and fabrication steps, the handbook proceeds with a section fully devoted to the main conventional semiconductor devices like, e.g., bipolar transistors and MOS capacitors and transistors, used in the production of the standard integrated circuits, and the corresponding physical models. In the subsequent chapters, the scaling issues of the semiconductor-device technology are addressed, followed by the description of novel concept-based semiconductor devices. The last section illustrates the numerical simulation methods ranging from the fabrication processes to the device performances. Each chapter is self-contained, and refers to related topics treated in other chapters when necessary, so that the reader interested in a specific subject can easily identify a personal reading path through the vast contents of the handbook.

This book presents recent advances towards the goal of enabling efficient implementation of machine learning models on resource-constrained systems, covering different application domains. The focus is on presenting interesting and new use cases of applying machine learning to innovative application domains, exploring the efficient hardware design of efficient machine learning accelerators, memory optimization techniques, illustrating model compression and neural architecture search techniques for energy-efficient and fast execution on resource-constrained hardware platforms, and understanding hardware-software codesign techniques for achieving even greater energy, reliability, and performance benefits. Discusses efficient implementation of machine learning in embedded, CPS, IoT, and edge computing; Offers comprehensive coverage of hardware design, software design, and hardware/software co-design and co-optimization; Describes real applications to demonstrate how embedded, CPS, IoT, and edge applications benefit from machine learning.

In this book, a global team of experts from academia, research institutes and industry presents their vision on how new nano-chip architectures will enable the performance and energy efficiency needed for AI-driven advancements in autonomous mobility, healthcare, and man-machine cooperation. Recent reviews of the status quo, as presented in CHIPS 2020 (Springer), have prompted the need for an urgent reassessment of opportunities in nanoelectronic information technology. As such, this book explores the foundations of a new era in nanoelectronics that will drive progress in intelligent chip systems for energy-efficient information technology, on-chip deep learning for data analytics, and quantum computing. Given its scope, this book provides a timely compendium that hopes to inspire and shape the future of nanoelectronics in the decades to come.