<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>

Proceedings of the 18th IEEE Workshop on Nonlinear Dynamics of Electronic Systems, which took place in Dresden, Germany, 26 – 28 May 2010.

<p>Implantable wireless devices are used to treat a variety of diseases that are not able to be treated with pharmaceuticals or traditional surgery, These implantable devices have use in the treatment of neurological disorders like epilepsy, optical disorders such as glaucoma, or injury related issues such as targeted muscle reinnervation. These devices can rely upon harvesting power from an inductive wireless power source and batteries. Improvements to how well the devices utilize this power directly increase the efficacy of the device operation as well as the device's lifetime, reducing the need for future surgeries or implantations. </p> <p> I have designed an improvement to cavity resonator based wireless power by designing a dynamic impedance matching implantable power supply, capable of tracking with device motion throughout a changing magnetic field and tracking with changing powering frequencies. This cavity resonator based system presents further challenges practically in the turn-on cycle of the improved device. </p> <p> I further design a coil-to-coil based wireless power system, capable of dynamically impedance matching a high quality factor coil to optimize power transfer during steady state, while also reducing turn-on transient power required in dynamic systems by utilizing a second low quality factor coil. This second coil has a broadband response and is capable of turning on at lower powers than that of the high quality factor coil. The low quality factor coil powers the circuitry that dynamically matches the impedance of the high quality factor coil, allowing for low power turn on while maintaining high power transfer at all operating frequencies to the implantable device. </p> <p> Finally, an integrated circuit is designed, fabricated, and tested that is capable of smoothly providing regulated DC power to the implantable device by stepping up from wireless power to a reasonable voltage level or stepping down from a battery to a reasonable voltage level for the device. The chip is fabricated in 0.18um CMOS process and is capable of providing power to the "Bionode" implantable device. </p>

The field of coupled resonant systems is a rich research area with enumerable real-world applications, including the fields of neural computing and pattern recognition, energy harvesting, and even modeling the behavior of certain types of biological systems. This work is primarily focused on the study of the behaviors of two subsets of this field: large networks of globally coupled resonators (which, in this work, refers to passive, damped resonant elements which require external stimulus) and smaller networks of oscillators (referring to active devices capable of self-sustained motion), which are coupled through a network of light-sensitive resistive elements. In the case of the former, we begin by developing an analytical and experimental framework to examine the behaviors of this system under various conditions, such as different coupling modalities and element-level parametric mistunings. Once a proper understanding of the dynamics of these systems has been established, we go on to develop the system into a single-input, single-output, multi-analyte volatile organic compound sensor. For the study of oscillator networks, we begin by building a device which utilizes a network of Colpitts oscillators, coupled through a series of color-filtered CdSe photocells. We then establish that through the analysis of particular emergent behaviors (most notably, frequency locking within the network), this type of system may show promise as a threshold color sensor. By exploiting these behaviors, this type of system may find applications in neuromorphic computing (particularly in optical pattern recognition).

Proceedings of the 18th IEEE Workshop on Nonlinear Dynamics of Electronic Systems, which took place in Dresden, Germany, 26 – 28 May 2010.:Welcome Address ........................ Page I Table of Contents ........................ Page III Symposium Committees .............. Page IV Special Thanks ............................. Page V Conference program (incl. page numbers of papers) ................... Page VI Conference papers Invited talks ................................ Page 1 Regular Papers ........................... Page 14 Wednesday, May 26th, 2010 ......... Page 15 Thursday, May 27th, 2010 .......... Page 110 Friday, May 28th, 2010 ............... Page 210 Author index ............................... Page XIII

<p>  </p> <p>Many machine learning models exist for battery management systems to utilize. Few have been shown to work. This work focuses on gathering data from cycling battery packs and sending this data directly to machine learning models built off robust datasets for applying the resulting predicted values and outputs directly on top of real-time systems. A parasitic sensor network was created composed of a main microcontroller, a host CPU, and various sensors including resistance temperature detection devices (RTDs), a voltage measurement circuit, current measurement circuit, and an accelerometer/gyroscope. The resulting network was integrated parasitically with a 4-cell 18650 SONY VTC6 battery pack, then tested both on-ground and in-flight with a commercial quadcopter. Real-time data for the battery pack with four cells in series was gathered. This real-time data stream was then integrated with data-driven neural network algorithms trained on various 18650 datasets and a real physical model to finalize the “AI BMS”. Using the power of non-linear models to infer battery health impacts not normally considered in battery management systems, the “AI BMS” was able to use low-fidelity real-time data in conjunction with a powerful multi-faceted model to make predictive decisions about battery health characteristics on top of normal system operations.</p>

<p>With the advent of increasingly complex radio systems at higher frequencies and the slowing of traditional CMOS process scaling with power concerns, there has been an increased focus on integration, architectural, and material innovations as a continued path forward in MEMS and logic. This work presents the first comprehensive experimental study of resonant body transistors in a commercial 14nm FinFET process, demonstrating differential radio frequency transduction as a function of transistor biasing through electrostatic, piezoresistive, and threshold voltage modulation. The impact of device design changes on unreleased resonator performance are further explored, highlighting the importance of phononic confinement in achieving an f*Q product of 8.2*10¹¹ at 11.73 GHz. Also shown are initial efforts towards the understanding of coupled oscillator architectures and a perovskite nickelate material system. Finally, development of resonators based on two-dimensional materials, whose scale is particularly attractive for high-frequency nano-mechanical resonators and acoustic devices, is discussed. Experiments towards dry transfer of tellurene flakes using geometries printed via two photon polymerization are presented along with optimization of a fabrication process for gated RF devices, presenting new opportunities for high-frequency electro-mechanical interactions in this topological material. </p>

<p dir="ltr">Interconnects pose severe performance bottlenecks in advanced technology nodes due to multiple scaling challenges. To understand such problems and explore potential solutions, it is important to develop advanced models. This is particularly relevant for modern interconnects (especially vias) with complex structures with non- trivial current paths. In this dissertation, we develop a comprehensive physics-based interconnect models to capture surface and grain boundary scattering. We further analyze the circuit implications of 2D transition metal dichalcogenide (TMD)-augmented interconnects, which show potential in mitigating some of the scalability concerns of state-of-the-art interconnects. First, we propose a 2D spatially resolved model for surface scattering in rectangular interconnects based on the Fuchs-Sondheimer (FS) theory. The proposed spatially resolved FS (SRFS) model offers both spatial dependence and explicit relation of conductivity to physical parameters. We also couple the SRFS model with grain boundary scattering based on the Mayadas−Shatzkes (MS) theory. The SRFS-MS model is exact for diffusive surface scattering and offers a good approximation for elastic surface scattering. Furthermore, we develop a circuit-compatible version of the SRFS-MS model and show a close match with the physical SRFS-MS model (error < 0.7%). Moreover, we integrate temperature dependency, confirming that surface scattering has a negligible temperature-dependence. Second, we analyze the circuit implications of 2D TMD augmented interconnects and show the effective clock frequency of an AES circuit is boosted by 2%-32%. We also establish that the vertical resistivity of the TMD material must be below 22 kΩ-nm to obtain performance benefits over state-of-the-art interconnects in the worst-case process-temperature corner.</p>

For ultra-high speed communication systems at high center frequencies above 100 GHz, we propose a disruptive change in system architecture to address major issues regarding amplifier chains with a large number of amplifier stages. They cause a high noise figure and high power consumption when operating close to the frequency limits of the underlying semiconductor technologies. Instead of scaling a classic homodyne transceiver system, we employ repeated amplification in single-stage amplifiers through positive feedback as well as synthesizer-free self-mixing demodulation at the receiver to simplify the system architecture notably. Since the amplitude and phase information for the emerging oscillation is defined by the input signal and the oscillator is only turned on for a very short time, it can be left unstabilized and thus come without a PLL. As soon as gain is no longer the most prominent issue, relaxed requirements for all the other major components allow reconsidering their implementation concepts to achieve further improvements compared to classic systems. This paper provides the first comprehensive overview of all major design aspects that need to be addressed upon realizing a SPARS-based transceiver. At system level, we show how to achieve high data rates and a noise performance comparable to classic systems, backed by scaled demonstrator experiments. Regarding the transmitter, design considerations for efficient quadrature modulation are discussed. For the frontend components that replace PA and LNA amplifier chains, implementation techniques for regenerative sampling circuits based on super-regenerative oscillators are presented. Finally, an analog-to-digital converter with outstanding performance and complete interfaces both to the analog baseband as well as to the digital side completes the set of building blocks for efficient ultra-high speed communication.

<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>