1,273 research outputs found
A Contribution Towards Intelligent Autonomous Sensors Based on Perovskite Solar Cells and Ta2O5/ZnO Thin Film Transistors
Many broad applications in the field of robotics, brain-machine interfaces, cognitive computing, image and speech processing and wearables require edge devices with very constrained power and hardware requirements that are challenging to realize. This is because these applications require sub-conscious awareness and require to be always “on”, especially when integrated with a sensor node that detects an event in the environment. Present day edge intelligent devices are typically based on hybrid CMOS-memristor arrays that have been so far designed for fast switching, typically in the range of nanoseconds, low energy consumption (typically in nano-Joules), high density and endurance (exceeding 1015 cycles). On the other hand, sensory-processing systems that have the same time constants and dynamics as their input signals, are best placed to learn or extract information from them. To meet this requirement, many applications are implemented using external “delay” in the memristor, in a process which enables each synapse to be modeled as a combination of a temporal delay and a spatial weight parameter.
This thesis demonstrates a synaptic thin film transistor capable of inherent logic functions as well as compute-in-memory on similar time scales as biological events. Even beyond a conventional crossbar array architecture, we have relied on new concepts in reservoir computing to demonstrate a delay system reservoir with the highest learning efficiency of 95% reported to date, in comparison to equivalent two terminal memristors, using a single device for the task of image processing. The crux of our findings relied on enhancing our capability to model the unique physics of the device, in the scope of the current thesis, that is not amenable to conventional TCAD simulations. The model provides new insight into the redox characteristics of the gate current and paves way for assessment of device performance in compute-in-memory applications. The diffusion-based mechanism of the device, effectively enables time constants that have potential in applications such as gesture recognition and detection of cardiac arrythmia.
The thesis also reports a new orientation of a solution processed perovskite solar cell with an efficiency of 14.9% that is easily integrable into an intelligent sensor node. We examine the influence of the growth orientation on film morphology and solar cell efficiency. Collectively, our work aids the development of more energy-efficient, powerful edge-computing sensor systems for upcoming applications of the IOT
Emerging Power Electronics Technologies for Sustainable Energy Conversion
This Special Issue summarizes, in a single reference, timely emerging topics related to power electronics for sustainable energy conversion. Furthermore, at the same time, it provides the reader with valuable information related to open research opportunity niches
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
A Review of Bayesian Methods in Electronic Design Automation
The utilization of Bayesian methods has been widely acknowledged as a viable
solution for tackling various challenges in electronic integrated circuit (IC)
design under stochastic process variation, including circuit performance
modeling, yield/failure rate estimation, and circuit optimization. As the
post-Moore era brings about new technologies (such as silicon photonics and
quantum circuits), many of the associated issues there are similar to those
encountered in electronic IC design and can be addressed using Bayesian
methods. Motivated by this observation, we present a comprehensive review of
Bayesian methods in electronic design automation (EDA). By doing so, we hope to
equip researchers and designers with the ability to apply Bayesian methods in
solving stochastic problems in electronic circuits and beyond.Comment: 24 pages, a draft version. We welcome comments and feedback, which
can be sent to [email protected]
Power Semiconductors for An Energy-Wise Society
This IEC White Paper establishes the critical role that power semiconductors play in transitioning to an energy wise society. It takes an in-depth look at expected trends and opportunities, as well as the challenges surrounding the power semiconductors industry. Among the significant challenges mentioned is the need for change in industry practices when transitioning from linear to circular economies and the shortage of skilled personnel required for power semiconductor development. The white paper also stresses the need for strategic actions at the policy-making level to address these concerns and calls for stronger government commitment, policies and funding to advance power semiconductor technologies and integration. It further highlights the pivotal role of standards in removing technical risks, increasing product quality and enabling faster market acceptance. Besides noting benefits of existing standards in accelerating market growth, the paper also identifies the current standardization gaps. The white paper emphasizes the importance of ensuring a robust supply chain for power semiconductors to prevent supply-chain disruptions like those seen during the COVID-19 pandemic, which can have widespread economic impacts.The white paper highlights the importance of inspiring young professionals to take an interest in power semiconductors and power electronics, highlighting the potential to make a positive impact on the world through these technologies.The white paper concludes with recommendations for policymakers, regulators, industry and other IEC stakeholders for collaborative structures and accelerating the development and adoption of standards
Cosmic-ray searches with the MATHUSLA detector
The performance of the proposed MATHUSLA detector as an instrument for
studying the physics of cosmic rays by measuring extensive air showers is
presented. The MATHUSLA detector is designed to observe and study the decay of
long-lived particles produced at the pp interaction point of the CMS detector
at CERN during the HL-LHC data-taking period. The proposed MATHUSLA detector
will be composed of many layers of long scintillating bars that cannot measure
more than one hit per bar and correctly report the hit coordinate in case of
multiple hits. This study shows that adding a layer of RPC detectors with both
analogue and digital readout significantly enhances the capabilities of
MATHUSLA to measure the local densities and arrival times of charged particles
at the front of air showers. We discuss open issues in cosmic-ray physics that
the proposed MATHUSLA detector with an additional layer of RPC detectors could
address and conclude by comparing with other air-shower facilities that measure
cosmic rays in the PeV energy range.Comment: 64 pages, 58 figure
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Dynamic Dark Current Characterisation in CMOS Image Sensors
Understanding the early universe has been the goal of cosmology since its conception and it has not been until recent decades that the technology has existed that the earliest stars and galaxies have been observable. A crucial step in unravelling the mysteries of the early universe is accurate image data. To achieve this it is critical to fully understand and characterise all noise sources which may be present in such data, so that it can be accurately removed while preserving the integrity of the data of interest. Dark current or thermal signal is one such noise source that must be removed from astronomical image data. It is usually assumed that the dark current is linear with exposure time. However, this is not always the case. A number of pixels in an image sensor will display dynamic dark current. The dark current rate will reduce with increasing (signal) exposure time. Therefore, applying a linear dark current model to these pixels will result in an overestimation of the dark signal in the image data and any subsequent subtraction of this overestimated dark signal will result in the destruction of potentially key information.
The experimental characterisation of dynamic dark current in a CMOS image sensor is performed. It is shown that < 1% of pixels in the devices tested displayed dynamic dark current. The semi-empirical model developed is shown to accurately represent the measured data for a total signal comprising solely of dark signal. A simple one dimensional model is presented and is used to demonstrate the fundamental physical processes which lead to a pixel displaying dynamic dark current. The simulations show a good correlation
with the experimental results. This leads to the conclusion that dynamic dark current is generated by sources located close to the depletion edges of the PPD
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
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