217 research outputs found
Development of electronics for microultrasound capsule endoscopy
Development of intracorporeal devices has surged in the last decade due to advancements in the semiconductor industry, energy storage and low-power sensing systems. This work aims to present a thorough systematic overview and exploration of the microultrasound (µUS) capsule endoscopy (CE) field as the development of electronic components will be key to a successful applicable µUSCE device. The research focused on investigating and designing high-voltage (HV, < 36 V) generating and driving circuits as well as a low-noise amplifier (LNA) for battery-powered and volume-limited systems.
In implantable applications, HV generation with maximum efficiency is required to improve the operational lifetime whilst reducing the cost of the device. A fully integrated hybrid (H) charge pump (CP) comprising a serial-parallel (SP) stage was designed and manufactured for > 20 V and 0 - 100 µA output capabilities. The results were compared to a Dickson (DKCP) occupying the same chip area; further improvements in the SPCP topology were explored and a new switching scheme for SPCPs was introduced. A second regulated CP version was excogitated and manufactured to use with an integrated µUS pulse generator. The CP was manufactured and tested at different output currents and capacitive loads; its operation with an US pulser was evaluated and a novel self-oscillating CP mechanism to eliminate the need of an auxiliary clock generator with a minimum area overhead was devised.
A single-output universal US pulser was designed, manufactured and tested with 1.5 MHz, 3 MHz, and 28 MHz arrays to achieve a means of fully-integrated, low-power transducer driving. The circuit was evaluated for power consumption and pulse generation capabilities with different loads. Pulse-echo measurements were carried out and compared with those from a commercial US research system to characterise and understand the quality of the generated pulse. A second pulser version for a 28 MHz array was derived to allow control of individual elements. The work involved its optimisation methodology and design of a novel HV feedback-based level-shifter.
A low-noise amplifier (LNA) was designed for a wide bandwidth µUS array with a centre frequency of 28 MHz. The LNA was based on an energy-efficient inverter architecture. The circuit encompassed a full power-down functionality and was investigated for a self-biased operation to achieve lower chip area. The explored concepts enable realisation of low power and high performance LNAs for µUS frequencies
Toward Fault-Tolerant Applications on Reconfigurable Systems-on-Chip
L'abstract è presente nell'allegato / the abstract is in the attachmen
Low Power Memory/Memristor Devices and Systems
This reprint focusses on achieving low-power computation using memristive devices. The topic was designed as a convenient reference point: it contains a mix of techniques starting from the fundamental manufacturing of memristive devices all the way to applications such as physically unclonable functions, and also covers perspectives on, e.g., in-memory computing, which is inextricably linked with emerging memory devices such as memristors. Finally, the reprint contains a few articles representing how other communities (from typical CMOS design to photonics) are fighting on their own fronts in the quest towards low-power computation, as a comparison with the memristor literature. We hope that readers will enjoy discovering the articles within
Function Implementation in a Multi-Gate Junctionless FET Structure
Title from PDF of title page, viewed September 18, 2023Dissertation advisor: Mostafizur RahmanVitaIncludes bibliographical references (pages 95-117)Dissertation (Ph.D.)--Department of Computer Science and Electrical Engineering, Department of Physics and Astronomy. University of Missouri--Kansas City, 2023This dissertation explores designing and implementing a multi-gate junctionless field-effect transistor (JLFET) structure and its potential applications beyond conventional devices. The JLFET is a promising alternative to conventional transistors due to its simplified fabrication process and improved electrical characteristics. However, previous research has focused primarily on the device's performance at the individual transistor level, neglecting its potential for implementing complex functions. This dissertation fills this research gap by investigating the function implementation capabilities of the JLFET structure and proposing novel circuit designs based on this technology.
The first part of this dissertation presents a comprehensive review of the existing literature on JLFETs, including their fabrication techniques, operating principles, and performance metrics. It highlights the advantages of JLFETs over traditional metal-oxide-semiconductor field-effect transistors (MOSFETs) and discusses the challenges associated with their implementation. Additionally, the review explores the limitations of conventional transistor technologies, emphasizing the need for exploring alternative device architectures.
Building upon the theoretical foundation, the dissertation presents a detailed analysis of the multi-gate JLFET structure and its potential for realizing advanced functions. The study explores the impact of different design parameters, such as channel length, gate oxide thickness, and doping profiles, on the device performance. It investigates the trade-offs between power consumption, speed, and noise immunity, and proposes design guidelines for optimizing the function implementation capabilities of the JLFET.
To demonstrate the practical applicability of the JLFET structure, this dissertation introduces several novel circuit designs based on this technology. These designs leverage the unique characteristics of the JLFET, such as its steep subthreshold slope and improved on/off current ratio, to implement complex functions efficiently. The proposed circuits include arithmetic units, memory cells, and digital logic gates. Detailed simulations and analyses are conducted to evaluate their performance, power consumption, and scalability.
Furthermore, this dissertation explores the potential of the JLFET structure for emerging technologies, such as neuromorphic computing and bioelectronics. It investigates how the JLFET can be employed to realize energy-efficient and biocompatible devices for applications in artificial intelligence and biomedical engineering. The study investigates the compatibility of the JLFET with various materials and substrates, as well as its integration with other functional components.
In conclusion, this dissertation contributes to the field of nanoelectronics by providing a comprehensive investigation into the function implementation capabilities of the multi-gate JLFET structure. It highlights the potential of this device beyond its individual transistor performance and proposes novel circuit designs based on this technology. The findings of this research pave the way for the development of advanced electronic systems that are more energy-efficient, faster, and compatible with emerging applications in diverse fields.Introduction -- Literature review -- Crosstalk principle -- Experiment of crosstalk -- Device architecture -- Simulation & results -- Conclusio
Reliability Investigations of MOSFETs using RF Small Signal Characterization
Modern technology needs and advancements have introduced various new concepts such as Internet-of-Things, electric automotive, and Artificial intelligence. This implies an increased activity in the electronics domain of analog and high frequency. Silicon devices have emerged as a cost-effective solution for such diverse applications. As these silicon devices are pushed towards higher performance, there is a continuous need to improve fabrication, power efficiency, variability, and reliability. Often, a direct trade-off of higher performance is observed in the reliability of semiconductor devices. The acceleration-based methodologies used for reliability assessment are the adequate time-saving solution for the lifetime's extrapolation but come with uncertainty in accuracy. Thus, the efforts to improve the accuracy of reliability characterization methodologies run in parallel. This study highlights two goals that can be achieved by incorporating high-frequency characterization into the reliability characteristics. The first one is assessing high-frequency performance throughout the device's lifetime to facilitate an accurate description of device/circuit functionality for high-frequency applications. Secondly, to explore the potential of high-frequency characterization as the means of scanning reliability effects within devices. S-parameters served as the high-frequency device's response and mapped onto a small-signal model to analyze different components of a fully depleted silicon-on-insulator MOSFET. The studied devices are subjected to two important DC stress patterns, i.e., Bias temperature instability stress and hot carrier stress. The hot carrier stress, which inherently suffers from the self-heating effect, resulted in the transistor's geometry-dependent magnitudes of hot carrier degradation. It is shown that the incorporation of the thermal resistance model is mandatory for the investigation of hot carrier degradation. The property of direct translation of small-signal parameter degradation to DC parameter degradation is used to develop a new S-parameter based bias temperature instability characterization methodology. The changes in gate-related small-signal capacitances after hot carrier stress reveals a distinct signature due to local change of flat-band voltage. The measured effects of gate-related small-signal capacitances post-stress are validated through transient physics-based simulations in Sentaurus TCAD.:Abstract
Symbols
Acronyms
1 Introduction
2 Fundamentals
2.1 MOSFETs Scaling Trends and Challenges
2.1.1 Silicon on Insulator Technology
2.1.2 FDSOI Technology
2.2 Reliability of Semiconductor Devices
2.3 RF Reliability
2.4 MOSFET Degradation Mechanisms
2.4.1 Hot Carrier Degradation
2.4.2 Bias Temperature Instability
2.5 Self-heating
3 RF Characterization of fully-depleted Silicon on Insulator devices
3.1 Scattering Parameters
3.2 S-parameters Measurement Flow
3.2.1 Calibration
3.2.2 De-embedding
3.3 Small-Signal Model
3.3.1 Model Parameters Extraction
3.3.2 Transistor Figures of Merit
3.4 Characterization Results
4 Self-heating assessment in Multi-finger Devices
4.1 Self-heating Characterization Methodology
4.1.1 Output Conductance Frequency dependence
4.1.2 Temperature dependence of Drain Current
4.2 Thermal Resistance Behavior
4.2.1 Thermal Resistance Scaling with number of fingers
4.2.2 Thermal Resistance Scaling with finger spacing
4.2.3 Thermal Resistance Scaling with GateWidth
4.2.4 Thermal Resistance Scaling with Gate length
4.3 Thermal Resistance Model
4.4 Design for Thermal Resistance Optimization
5 Bias Temperature Instability Investigation
5.1 Impact of Bias Temperature Instability stress on Device Metrics
5.1.1 Experimental Details
5.1.2 DC Parameters Drift
5.1.3 RF Small-Signal Parameters Drift
5.2 S-parameter based on-the-fly Bias Temperature Instability Characterization Method
5.2.1 Measurement Methodology
5.2.2 Results and Discussion
6 Investigation of Hot-carrier Degradation
6.1 Impact of Hot-carrier stress on Device performance
6.1.1 DC Metrics Degradation
6.1.2 Impact on small-signal Parameters
6.2 Implications of Self-heating on Hot-carrier Degradation in n-MOSFETs
6.2.1 Inclusion of Thermal resistance in Hot-carrier Degradation modeling
6.2.2 Convolution of Bias Temperature Instability component in Hot-carrier Degradation
6.2.3 Effect of Source and Drain Placement in Multi-finger Layout
6.3 Vth turn-around effect in p-MOSFET
7 Deconvolution of Hot-carrier Degradation and Bias Temperature Instability using Scattering parameters
7.1 Small-Signal Parameter Signatures for Hot-carrier Degradation and Bias Temperature Instability
7.2 TCAD Dynamic Simulation of Defects
7.2.1 Fixed Charges
7.2.2 Interface Traps near Gate
7.2.3 Interface Traps near Spacer Region
7.2.4 Combination of Traps
7.2.5 Drain Series Resistance effect
7.2.6 DVth Correction
7.3 Empirical Modeling based deconvolution of Hot-carrier Degradation
8 Conclusion and Recommendations
8.1 General Conclusions
8.2 Recommendations for Future Work
A Directly measured S-parameters and extracted Y-parameters
B Device Dimensions for Thermal Resistance Modeling
C Frequency response of hot-carrier degradation (HCD)
D Localization Effect of Interface Traps
Bibliograph
MOCAST 2021
The 10th International Conference on Modern Circuit and System Technologies on Electronics and Communications (MOCAST 2021) will take place in Thessaloniki, Greece, from July 5th to July 7th, 2021. The MOCAST technical program includes all aspects of circuit and system technologies, from modeling to design, verification, implementation, and application. This Special Issue presents extended versions of top-ranking papers in the conference. The topics of MOCAST include:Analog/RF and mixed signal circuits;Digital circuits and systems design;Nonlinear circuits and systems;Device and circuit modeling;High-performance embedded systems;Systems and applications;Sensors and systems;Machine learning and AI applications;Communication; Network systems;Power management;Imagers, MEMS, medical, and displays;Radiation front ends (nuclear and space application);Education in circuits, systems, and communications
Reclaiming Fault Resilience and Energy Efficiency With Enhanced Performance in Low Power Architectures
Rapid developments of the AI domain has revolutionized the computing industry by the introduction of state-of-art AI architectures. This growth is also accompanied by a massive increase in the power consumption. Near-Theshold Computing (NTC) has emerged as a viable solution by offering significant savings in power consumption paving the way for an energy efficient design paradigm. However, these benefits are accompanied by a deterioration in performance due to the severe process variation and slower transistor switching at Near-Threshold operation. These problems severely restrict the usage of Near-Threshold operation in commercial applications. In this work, a novel AI architecture, Tensor Processing Unit, operating at NTC is thoroughly investigated to tackle the issues hindering system performance. Research problems are demonstrated in a scientific manner and unique opportunities are explored to propose novel design methodologies
AI/ML Algorithms and Applications in VLSI Design and Technology
An evident challenge ahead for the integrated circuit (IC) industry in the
nanometer regime is the investigation and development of methods that can
reduce the design complexity ensuing from growing process variations and
curtail the turnaround time of chip manufacturing. Conventional methodologies
employed for such tasks are largely manual; thus, time-consuming and
resource-intensive. In contrast, the unique learning strategies of artificial
intelligence (AI) provide numerous exciting automated approaches for handling
complex and data-intensive tasks in very-large-scale integration (VLSI) design
and testing. Employing AI and machine learning (ML) algorithms in VLSI design
and manufacturing reduces the time and effort for understanding and processing
the data within and across different abstraction levels via automated learning
algorithms. It, in turn, improves the IC yield and reduces the manufacturing
turnaround time. This paper thoroughly reviews the AI/ML automated approaches
introduced in the past towards VLSI design and manufacturing. Moreover, we
discuss the scope of AI/ML applications in the future at various abstraction
levels to revolutionize the field of VLSI design, aiming for high-speed, highly
intelligent, and efficient implementations
Pentimento: Data Remanence in Cloud FPGAs
Cloud FPGAs strike an alluring balance between computational efficiency,
energy efficiency, and cost. It is the flexibility of the FPGA architecture
that enables these benefits, but that very same flexibility that exposes new
security vulnerabilities. We show that a remote attacker can recover "FPGA
pentimenti" - long-removed secret data belonging to a prior user of a cloud
FPGA. The sensitive data constituting an FPGA pentimento is an analog imprint
from bias temperature instability (BTI) effects on the underlying transistors.
We demonstrate how this slight degradation can be measured using a
time-to-digital (TDC) converter when an adversary programs one into the target
cloud FPGA.
This technique allows an attacker to ascertain previously safe information on
cloud FPGAs, even after it is no longer explicitly present. Notably, it can
allow an attacker who knows a non-secret "skeleton" (the physical structure,
but not the contents) of the victim's design to (1) extract proprietary details
from an encrypted FPGA design image available on the AWS marketplace and (2)
recover data loaded at runtime by a previous user of a cloud FPGA using a known
design. Our experiments show that BTI degradation (burn-in) and recovery are
measurable and constitute a security threat to commercial cloud FPGAs.Comment: 17 Pages, 8 Figure
Reconfigurable Receiver Front-Ends for Advanced Telecommunication Technologies
The exponential growth of converging technologies, including augmented reality, autonomous vehicles, machine-to-machine and machine-to-human interactions, biomedical and environmental sensory systems, and artificial intelligence, is driving the need for robust infrastructural systems capable of handling vast data volumes between end users and service providers. This demand has prompted a significant evolution in wireless communication, with 5G and subsequent generations requiring exponentially improved spectral and energy efficiency compared to their predecessors. Achieving this entails intricate strategies such as advanced digital modulations, broader channel bandwidths, complex spectrum sharing, and carrier aggregation scenarios. A particularly challenging aspect arises in the form of non-contiguous aggregation of up to six carrier components across the frequency range 1 (FR1). This necessitates receiver front-ends to effectively reject out-of-band (OOB) interferences while maintaining high-performance in-band (IB) operation. Reconfigurability becomes pivotal in such dynamic environments, where frequency resource allocation, signal strength, and interference levels continuously change. Software-defined radios (SDRs) and cognitive radios (CRs) emerge as solutions, with direct RF-sampling receivers offering a suitable architecture in which the frequency translation is entirely performed in digital domain to avoid analog mixing issues. Moreover, direct RF- sampling receivers facilitate spectrum observation, which is crucial to identify free zones, and detect interferences. Acoustic and distributed filters offer impressive dynamic range and sharp roll off characteristics, but their bulkiness and lack of electronic adjustment capabilities limit their practicality. Active filters, on the other hand, present opportunities for integration in advanced CMOS technology, addressing size constraints and providing versatile programmability. However, concerns about power consumption, noise generation, and linearity in active filters require careful consideration.This thesis primarily focuses on the design and implementation of a low-voltage, low-power RFFE tailored for direct sampling receivers in 5G FR1 applications. The RFFE consists of a balun low-noise amplifier (LNA), a Q-enhanced filter, and a programmable gain amplifier (PGA). The balun-LNA employs noise cancellation, current reuse, and gm boosting for wideband gain and input impedance matching. Leveraging FD-SOI technology allows for programmable gain and linearity via body biasing. The LNA's operational state ranges between high-performance and high-tolerance modes, which are apt for sensitivityand blocking tests, respectively. The Q-enhanced filter adopts noise-cancelling, current-reuse, and programmable Gm-cells to realize a fourth-order response using two resonators. The fourth-order filter response is achieved by subtracting the individual response of these resonators. Compared to cascaded and magnetically coupled fourth-order filters, this technique maintains the large dynamic range of second-order resonators. Fabricated in 22-nm FD-SOI technology, the RFFE achieves 1%-40% fractional bandwidth (FBW) adjustability from 1.7 GHz to 6.4 GHz, 4.6 dB noise figure (NF) and an OOB third-order intermodulation intercept point (IIP3) of 22 dBm. Furthermore, concerning the implementation uncertainties and potential variations of temperature and supply voltage, design margins have been considered and a hybrid calibration scheme is introduced. A combination of on-chip and off-chip calibration based on noise response is employed to effectively adjust the quality factors, Gm-cells, and resonance frequencies, ensuring desired bandpass response. To optimize and accelerate the calibration process, a reinforcement learning (RL) agent is used.Anticipating future trends, the concept of the Q-enhanced filter extends to a multiple-mode filter for 6G upper mid-band applications. Covering the frequency range from 8 to 20 GHz, this RFFE can be configured as a fourth-order dual-band filter, two bandpass filters (BPFs) with an OOB notch, or a BPF with an IB notch. In cognitive radios, the filter’s transmission zeros can be positioned with respect to the carrier frequencies of interfering signals to yield over 50 dB blocker rejection
- …