Design of High-Speed Dual Port 8T SRAM Cell with Simultaneous and Parallel READ-WRITE Feature

An innovative 8 transistor (8T) static random access memory (SRAM) architecture with a simple and reliable read operation is presented in this study. LTspice software is used to implement the suggested topology in the 16nm predictive technology model (PTM). Investigations into and comparisons with conventional 6T, 8T, 9T, and 10T SRAM cells have been made regarding read and write operations\u27 delay and power consumption as well as power delay product (PDP). The simulation outcomes show that the suggested design offers the fastest read operation and PDP optimization overall. Compared to the current 6T and 9T topologies, the noise margin is also enhanced. Finally, the comparison of the figure of merit (FoM) indicates the best efficiency of the proposed design

Solid State Circuits Technologies

The evolution of solid-state circuit technology has a long history within a relatively short period of time. This technology has lead to the modern information society that connects us and tools, a large market, and many types of products and applications. The solid-state circuit technology continuously evolves via breakthroughs and improvements every year. This book is devoted to review and present novel approaches for some of the main issues involved in this exciting and vigorous technology. The book is composed of 22 chapters, written by authors coming from 30 different institutions located in 12 different countries throughout the Americas, Asia and Europe. Thus, reflecting the wide international contribution to the book. The broad range of subjects presented in the book offers a general overview of the main issues in modern solid-state circuit technology. Furthermore, the book offers an in depth analysis on specific subjects for specialists. We believe the book is of great scientific and educational value for many readers. I am profoundly indebted to the support provided by all of those involved in the work. First and foremost I would like to acknowledge and thank the authors who worked hard and generously agreed to share their results and knowledge. Second I would like to express my gratitude to the Intech team that invited me to edit the book and give me their full support and a fruitful experience while working together to combine this book

Integrated Circuits/Microchips

With the world marching inexorably towards the fourth industrial revolution (IR 4.0), one is now embracing lives with artificial intelligence (AI), the Internet of Things (IoTs), virtual reality (VR) and 5G technology. Wherever we are, whatever we are doing, there are electronic devices that we rely indispensably on. While some of these technologies, such as those fueled with smart, autonomous systems, are seemingly precocious; others have existed for quite a while. These devices range from simple home appliances, entertainment media to complex aeronautical instruments. Clearly, the daily lives of mankind today are interwoven seamlessly with electronics. Surprising as it may seem, the cornerstone that empowers these electronic devices is nothing more than a mere diminutive semiconductor cube block. More colloquially referred to as the Very-Large-Scale-Integration (VLSI) chip or an integrated circuit (IC) chip or simply a microchip, this semiconductor cube block, approximately the size of a grain of rice, is composed of millions to billions of transistors. The transistors are interconnected in such a way that allows electrical circuitries for certain applications to be realized. Some of these chips serve specific permanent applications and are known as Application Specific Integrated Circuits (ASICS); while, others are computing processors which could be programmed for diverse applications. The computer processor, together with its supporting hardware and user interfaces, is known as an embedded system.In this book, a variety of topics related to microchips are extensively illustrated. The topics encompass the physics of the microchip device, as well as its design methods and applications

ENERGY-EFFICIENT FEATURE EXTRACTION ENGINE AND SECURE CHIP IDENTIFICATION FOR UBIQUITOUS SURVEILLANCE

Ph.DDOCTOR OF PHILOSOPH

Quantum and spin-based tunneling devices for memory systems

Rapid developments in information technology, such as internet, portable computing, and wireless communication, create a huge demand for fast and reliable ways to store and process information. Thus far, this need has been paralleled with the revolution in solid-state memory technologies. Memory devices, such as SRAM, DRAM, and flash, have been widely used in most electronic products. The primary strategy to keep up the trend is miniaturization. CMOS devices have been scaled down beyond sub-45 nm, the size of only a few atomic layers. Scaling, however, will soon reach the physical limitation of the material and cease to yield the desired enhancement in device performance. In this thesis, an alternative method to scaling is proposed and successfully realized. The proposed scheme integrates quantum devices, Si/SiGe resonant interband tunnel diodes (RITD), with classical CMOS devices forming a microsystem of disparate devices to achieve higher performance as well as higher density. The device/circuit designs, layouts and masks involving 12 levels were fabricated utilizing a process that incorporates nearly a hundred processing steps. Utilizing unique characteristics of each component, a low-power tunneling-based static random access memory (TSRAM) has been demonstrated. The TSRAM cells exhibit bistability operation with a power supply voltage as low as 0.37 V. Various TSRAM cells were also constructed and their latching mechanisms have been extensively investigated. In addition, the operation margins of TSRAM cells are evaluated based on different device structures and temperature variation from room temperature up to 200oC. The versatility of TSRAM is extended beyond the binary system. Using multi-peak Si/SiGe RITD, various multi-valued TSRAM (MV-TSRAM) configurations that can store more than two logic levels per cell are demonstrated. By this virtue, memory density can be substantially increased. Using two novel methods via ambipolar operation and utilization of enable/disable transistors, a six-valued MV-TSRAM cell are demonstrated. A revolutionary novel concept of integrating of Si/SiGe RITD with spin tunnel devices, magnetic tunnel junctions (MTJ), has been developed. This hybrid approach adds non-volatility and multi-valued memory potential as demonstrated by theoretical predictions and simulations. The challenges of physically fabricating these devices have been identified. These include process compatibility and device design. A test bed approach of fabricating RITD-MTJ structures has been developed. In conclusion, this body of work has created a sound foundation for new research frontiers in four different major areas: integrated TSRAM system, MV-TSRAM system, MTJ/RITD-based nonvolatile MRAM, and RITD/CMOS logic circuits

Intrinsic variability of nanoscale CMOS technology for logic and memory.

The continuous downscaling of CMOS technology, the main engine of development of the semiconductor Industry, is limited by factors that become important for nanoscale device size, which undermine proper device operation completely offset gains from scaling. One of the main problems is device variability: nominally identical devices are different at the microscopic level due to fabrication tolerance and the intrinsic granularity of matter. For this reason, structures, devices and materials for the next technology nodes will be chosen for their robustness to process variability, in agreement with the ITRS (International Technology Roadmap for Semiconductors). Examining the dispersion of various physical and geometrical parameters and the effect these have on device performance becomes necessary. In this thesis, I focus on the study of the dispersion of the threshold voltage due to intrinsic variability in nanoscale CMOS technology for logic and for memory. In order to describe this, it is convenient to have an analytical model that allows, with the assistance of a small number of simulations, to calculate the standard deviation of the threshold voltage due to the various contributions

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

Self-diagnosis implantable optrode for optogenetic stimulation

PhD ThesisAs a cell type-specific neuromodulation method, optogenetic technique holds remarkable potential for the realisation of advanced neuroprostheses. By genetically expressing light-sensitive proteins such as channelrhodopsin-2 (ChR2) in cell membranes, targeted neurons could be controlled by blue light. This new neuromodulation technique could then be applied into extensive brain networks and be utilised to provide effective therapies for neurological disorders. However, the development of novel optogenetic implants is still a key challenge in the field. The major requirements include small device dimensions, suitable spatial resolution, high safety, and strong controllability. In particular, appropriate implantable electronics are expected to be built into the device, accomplishing a new-generation intelligent optogenetic implant. To date, different microfabrication techniques, such as wave-guided laser/light-emitting diode (LED) structure and μLED-on-optrode structure, have been widely explored to create and miniaturise optogenetic implants. However, although these existing devices meet the requirements to some extent, there is still considerable room for improvement. In this thesis, a Complementary Metal-Oxide-Semiconductor (CMOS)-driven μLED approach is proposed to develop an advanced implantable optrode. This design is based on the μLED-on-optrode structure, where Gallium Nitride (GaN) μLEDs can be directly bonded to provide precise local light delivery and multi-layer stimulation. Moreover, an in-built diagnostic sensing circuitry is designed to monitor optrode integrity and degradation. This self-diagnosis function greatly improves system reliability and safety. Furthermore, in-situ temperature sensors are incorporated to monitor the local thermal effects of light emitters. This ensures both circuitry stability and tissue health. More importantly, external neural recording circuitry is integrated into the implant, which could observe local neural signals in the vicinity of the stimulation sites. Therefore, a CMOS-based multi-sensor optogenetic implant is achieved, and this closed-loop neural interface is capable of performing multichannel optical neural stimulation and electrical neural recording simultaneously. This optrode is expected to represent a promising neural interface for broad neuroprosthesis applications

Low-Power Soft-Error-Robust Embedded SRAM

Soft errors are radiation-induced ionization events (induced by energetic particles like alpha particles, cosmic neutron, etc.) that cause transient errors in integrated circuits. The circuit can always recover from such errors as the underlying semiconductor material is not damaged and hence, they are called soft errors. In nanometer technologies, the reduced node capacitance and supply voltage coupled with high packing density and lack of masking mechanisms are primarily responsible for the increased susceptibility of SRAMs towards soft errors. Coupled with these are the process variations (effective length, width, and threshold voltage), which are prominent in scaled-down technologies. Typically, SRAM constitutes up to 90% of the die in microprocessors and SoCs (System-on-Chip). Hence, the soft errors in SRAMs pose a potential threat to the reliable operation of the system. In this work, a soft-error-robust eight-transistor SRAM cell (8T) is proposed to establish a balance between low power consumption and soft error robustness. Using metrics like access time, leakage power, and sensitivity to single event transients (SET), the proposed approach is evaluated. For the purpose of analysis and comparisons the results of 8T cell are compared with a standard 6T SRAM cell and the state-of-the-art soft-error-robust SRAM cells. Based on simulation results in a 65-nm commercial CMOS process, the 8T cell demonstrates higher immunity to SETs along with smaller area and comparable leakage power. A 32-kb array of 8T cells was fabricated in silicon. After functional verification of the test chip, a radiation test was conducted to evaluate the soft error robustness. As SRAM cells are scaled aggressively to increase the overall packing density, the smaller transistors exhibit higher degrees of process variation and mismatch, leading to larger offset voltages. For SRAM sense amplifiers, higher offset voltages lead to an increased likelihood of an incorrect decision. To address this issue, a sense amplifier capable of cancelling the input offset voltage is presented. The simulated and measured results in 180-nm technology show that the sense amplifier is capable of detecting a 4 mV differential input signal under dc and transient conditions. The proposed sense amplifier, when compared with a conventional sense amplifier, has a similar die area and a greatly reduced offset voltage. Additionally, a dual-input sense amplifier architecture is proposed with corroborating silicon results to show that it requires smaller differential input to evaluate correctly.1 yea