<p>Sensor technology is evolving rapidly, offering new opportunities for environmental data collection. Yet, despite the large number of sensors now available, there is a lack of logging platforms that can be used to operate these sensors in situ. To address this shortfall, River Restoration Intelligence and Verification (RRIV) has developed an environmental data logger that meets the needs of the environmental sensing community. This platform has several advantages that reduce the time, effort, and technical know-how required to deploy environmental sensors. An extensive low-power mode is available, and hardware such as a real-time clock with an independent power source is incorporated. A driver system has been developed that allows users to incorporate sensors into the platform with minimal effort. RRIV loggers also include a command line interface that allows user to add or remove sensors, calibrate sensors, or configure deployments without the need for C/C++ programming, something that is not possible with out-of-the-box microcontrollers such as Arduino and ST Nucleo products. The technology incorporated into RRIV and how it is applied and deployed in the field is described. This includes a description of power consumption. Protocols and descriptions of case construction are also included. RRIV loggers configured to monitor carbon dioxide and methane are used to demonstrate how this platform is used in the field.</p>

<p>To facilitate indoor air quality (IAQ) monitoring, the research described herein develops and implements methods for the electronic integration of two types of gas sensor, each functionalized with a polymer blend tailored for CO₂ detection. A highly sensitive and tunable electronic chemiresistive sensor interface was developed and experimentally validated. This device achieved analog-to-digital conversion (ADC) through a pulse width modulated (PWM) signal, temporary data storage with an efficient data buffering system, and noise reduction and signal amplification utilizing an instrumentation amplifier integrator circuit. These techniques can used beyond CO₂-specific applications to compensate for certain undesirable chemiresistive sensor characteristics, such as low response magnitude and signal noise. Additionally, resonant mass sensing circuitry was combined with an on-chip field programmable gate array (FPGA) implemented frequency counter. Hz-level resolution was achieved with an Alorium Snō FPGA board and a Verilog data acquisition and communication program. This device can monitor up to 16 sensor channels simultaneously and has a straightforward interface with a controllable output. Furthermore, the functionality of each integrated sensor was experimentally validated. With additional work, these integrated designs have the potential to be inexpensive, low-power, highly sensitive devices that are suitable for practical use in IAQ monitoring applications.</p>

<p>Most work on amplifier linearity has focused on the transconductance (gm) linearity, but there is increasing evidence that the voltage-dependence of the gate-source capacitance (Cgs) plays an important role in the linearity of emerging devices. This work addresses the capacitance contribution by incorporating the nonlinearities attributed to the voltage dependency of Cgs of a general FET on a circuit-level Cg amplifier model.</p> <p>An amplifier model including a voltage-dependent Cgs, and a voltage-dependent gm is studied using harmonic analysis and Volterra series. A closed form expression for the  third-order intercept point (IP3) of the amplifier, which depends on the nonlinear coefficients of Cgs, is obtained. A simple design rule, and a formula for the reduction of the IP3 due to the voltage-dependent Cgs are also presented. </p> <p>As application examples, the linearity of an amplifier based on a specific device is analyzed for two cases by extracting the nonlinear circuit parameters of the device. First for an analytic model of a bulk mosfet. Second for a one-dimensional, ballistic, coaxially gated Si nanowire. For low frequencies of design, the distortion introduced by gm is predominant, but for high frequencies it is obscured by the distortion coming from Cgs.</p> <p>We conclude that taking into account the voltage-dependence of Cgs is crucial when predicting the linearity behavior of a Cg amplifier, either designed for high-frequency operation, or based on a device operating near the quantum capacitance limit. </p>

<p>Neuromorphic computing endeavors to develop computational systems capable of emulating the brain’s capacity to execute intricate tasks concurrently and with remarkable energy efficiency. By utilizing new bioinspired computing architectures, these systems have the potential to revolutionize high-performance computing and enable local, low-energy computing for sensors and robots. Organic and soft materials are particularly attractive for neuromorphic computing as they offer biocompatibility, low-energy switching, and excellent tunability at a relatively low cost. Additionally, organic materials provide physical flexibility, large-area fabrication, and printability.</p><p>This doctoral dissertation showcases the research conducted in fabricating a comprehensive spiking organic neuron, which serves as the fundamental constituent of a circuit system for neuromorphic computing. The major contribution of this dissertation is the development of the organic, flexible neuron composed of spiking synapses and somas utilizing ultra-low voltage organic field-effect transistors (OFETs) for information processing. The synaptic and somatic circuits are implemented using physically flexible and biocompatible organic electronics necessary to realize the Polymer Neuromorphic Circuitry. An Axon-Hillock (AH) somatic circuit was fabricated and analyzed, followed by the adaptation of a log-domain integrator (LDI) synaptic circuit and the fabrication and analysis of a differential-pair integrator (DPI). Finally, a spiking organic neuron was formed by combining two LDI synaptic circuits and one AH synaptic circuit, and its characteristics were thoroughly examined. This is the first demonstration of the fabrication of an entire neuron using solid-state organic materials over a flexible substrate with integrated complementary OFETs and capacitors.</p>

<p>The last few decades have witnessed unprecedented growth in multiple areas of electronics spanning low-power sensing, intelligent computing and high-speed wireless connectivity. In the foreseeable future, there would be hundreds of billions of computing devices, sensors, things and people, wherein the technology will become intertwined with our lives through continuous interaction and collaboration between humans and machines. Such human-centric ideas give rise to the concept of internet of bodies (IoB), which calls for novel and energy-efficient techniques for sensing, processing and secure communication for resource-constrained IoB nodes.As we have painfully learnt during the pandemic, point-of-care diagnostics along with continuous sensing and long-term connectivity has become one of the major requirements in the healthcare industry, further emphasizing the need for energy-efficiency and security in the resource-constrained devices around us.</p> <p>  </p> <p>  With this vision in mind, I’ll divide this dissertation into the following chapters. The first part (Chapter 2) will cover time-domain sensing techniques which allow inherent energy-resolution scalability, and will show the fundamental limits of achievable resolution. Implementations will include 1) a radiation sensing system for occupational dosimetry in healthcare and mining applications, which can achieve 12-18 bit resolution with 0.01-1 µJ energy dissipation, and 2) an ADC-less neural signal acquisition system with direct Analog to Time Conversion at 13pJ/Sample. The second part (Chapters 3 and 4) of this dissertation will involve the fundamentals of developing secure energy-efficient electro-quasistatic (EQS) communication techniques for IoB wearables as well as implants, and will demonstrate  2 examples: 1) Adiabatic Switching for breaking the αCV^2f limit of power consumption in capacitive voltage mode human-body communication (HBC), and 2) Bi-Phasic Quasistatic Brain Communication (BP-QBC) for fully wireless data transfer from a sub-6mm^3, 2 µW brain implant. A custom modulation scheme, along with adiabatic communication enables wireline-like energy efficiencies (<5pJ/b) in HBC-based wireless systems, while the BP-QBC node, being fully electrical in nature, demonstrates sub-50pJ/b efficiencies by eliminating DC power consumption, and by avoiding the transduction losses observed in competing technologies, involving optical, ultrasound and magneto-electric modalities. Next in Chapter 5, we will show an implementation of a reconfigurable system that would include 1) a human-body communication transceiver and 2) a traditional wireless (MedRadio) transceiver on the same integrated circuit (IC), and would demonstrate methods to switch between the two modes by detecting the placement of the transmitter and receiver devices (on-body/away from the body). Finally, in Chapter 6, we shall show a technique of augmenting security in resource-constrained devices through authentication using the Analog/RF properties of the transmitter, which are usually discarded as non-idealities in a digital transceiver chain. This method does not require any additional hardware in the transmitter, making it an extremely promising technique to augment security in highly resource-constrained scenarios. Such energy-efficient intelligent sensing and secure communication techniques, when combined with intelligent in-sensor-analytics at the resource-constrained nodes, can potentially pave the way for perpetual, and even batteryless systems for next-generation IoT, IoB and healthcare applications.</p>

<p>The "Maker Movement" is a cultural phenomena rooted in DIY culture, which stresses making devices and creations on your own rather than purchasing it ready-made. At the core of the Maker Movement, is the "Maker Mindset"; a collection of attitudes, beliefs and behaviors that emphasize the importance of creativity, experimentation and innovation in the learning process. Since the Maker Mindset embodies constructionist principles at its core that push makers to experiment and problem-solve by collaborating with fellow makers through hands-on activities, it can be said that these activities comprise of Creative, Learning and Collaborative experiences. While Internet-of-Things devices have long been used to enhance these activities, research pertaining to using Augmented Reality in tandem with IoT for the purpose of enhancing experiences core to the Maker Mindset is relatively unexplored. Three different systems were developed with the goal of addressing this -- MicrokARts, ShARed IoT and MechARspace. Each system focuses on enhancing one of the three core experiences through AR-compatible IoT devices, whilst ensuring that they do not require prerequisite knowledge in order to author AR experiences. These systems were evaluated through user studies and testing over a variety of age-groups, with each system successfully enhancing one core experience each through the use of AR-IoT interactions.</p>

<p>From idea generation to conceptualization and development of products and technologies is a non-linear and iterative process. The work in this thesis follows a process that initiates with the review of existing technologies and products, examining their unique value proposition in the context of the specific applications for which they are designed. Next, the unmet needs of novel or emerging applications are identified that require new product or technologies. Once these user needs and product requirements are identified, the specific functions to be addressed by the product are specified. The subsequent process of design of products and technologies to meet these functions is enabled by engineering tools such as three-dimensional modelling, physics-based simulations, and manufacturing of a minimum viable prototype. In these steps, un-biased decisions have to be taken using weighted decision matrices to cater to the design requirements. Finally, the minimum viable prototype is tested to demonstrate the principal functionalities. The results obtained from the testing process identify the potential future improvements in the next generations of the prototype that would subsequently inform the final design of product. This thesis adopted this methodology to initiate the design two product-prototypes: i) an image-recognition-integrated service (IRIS) robotic hand for children and ii) cascaded multi-core vapor chamber (CMVC) for improving performance of next-generation computing systems. Minimum viable product-prototypes were manufactured to demonstrate the principal functionalities, followed by clear identification of future potential improvements. Tests of the prosthetic hand indicate that the image-recognition based feedback can successfully drive the actuators to perform the intended grasping motions. Experimental testing with the multi-core vapor chamber demonstrates successful performance of the prototype, which offers notable reduction in temperatures relative to the existing benchmark solid copper spreader. </p>

<p>Sudden unexpected death in epilepsy (SUDEP) is a fatal complication of epilepsy that kills 1̃2 of every 10,000 epileptic patients every year. SUDEP has proven difficult to study because it frequently occurs unobserved and cannot be predicted. What limited clinical data exists suggests that SUDEP occurs as a cardiorespiratory collapse immediately following a seizure. In this work, I explore how a group of autonomic reflexes termed collectively as “oxygen‐conserving reflexes (OCRs)” lead to sudden death when activated during seizures. I also demonstrate multiple physiological parallels between the OCR‐mediated deaths that I report and the clinical data on cases of human SUDEP. Additionally, I explore the neural pathway underlying OCRs, identify the carotid body as a potential target for intervention, and demonstrate the efficacy of electroceutical intervention in reducing the mortality risk of OCR activation during seizures. This work seeks to both offer a neural explanation for SUDEP as well as present a promising target and means for potential intervention.</p>