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Electrical transport in materials is typically diffusive, due to dominant momentum-relaxing scattering of carriers with the phonons or defects. In ultraclean material systems such as GaAs/AlGaAs or graphene/hBN heterostructures, momentum-relaxing can be suppressed, leading to the onset of non-diffusive transport regimes, where Ohm's law is no longer valid. Within these non-diffusive regimes, the hydrodynamic regime occurs when momentum-conserving electron-electron scattering length scale is smaller than the device length scale (usually at intermediate temperatures). On the other hand, weak electron-electron scattering (at low temperatures) results in ballistic transport, commonly understood using the familiar single-particle framework of injected carriers travelling in straight line trajectories with intermittent reflections off device boundaries. Both the ballistic and hydrodynamic regimes can exhibit a emph{negative} nonlocal resistance, and collective behaviour such as the formation of current vortices. In this work, we study nonlocal current-voltage characteristics in mesoscopic devices fabricated from a GaAs/AlGaAs heterostructure that hosts a two-dimensional electron system in a GaAs quantum well. First, we report a quadratic non-linearity in the nonlocal current-voltage characteristics that manifests in any device where a nonlocal voltage measurement is possible. Using measurements at low temperatures ($sim$ 4 K) across multiple devices and considering various contact configurations for each device, we show that the non-linearity is universal. We apply the non-linearity to rectification and frequency multiplication. We also report on a periodic peaks in the nonlocal voltage vs. magnetic field, in an enclosed mesoscopic geometry in which transverse magnetic focusing (TMF) is typically studied. These peaks occur at weak magnetic fields, are independent of the source-detector separation and are distinct from TMF. Our experimental findings are backed by an extensive set of simulations using in both the semiclassical as well as quantum-coherent transport models. Master of Science Current is made up of charged particles such as electrons moving through a material. Typically, current is proportional to the applied voltage and flows from higher to lower potential within the device with the potential decreasing monotonically as we move from the source contact to the drain contact irrespective of the path taken through the device. This is commonly known as Ohm's law, and is followed in most materials we come across. The motion of electrons carrying this current is akin to the motion of balls inside a pinball machine, their momentum randomized by intermittent collisions due to lattice vibrations, defects and impurities present in the material. In ultraclean two-dimensional materials at low-intermediate temperatures (where lattice vibration is weak), these collisions become sparse. Collisions of electrons with other electrons now become important. When electron-electron collisions are frequent, the electrons collectively behave like a fluid, giving rise to so called hydrodynamic transport. On the other hand, when electron-electron collisions are sparse as well, electrons move unhindered in ballistic straight line trajectories until they reflect off the device boundaries. This is known as ballistic transport. Under both these transport regimes, Ohm's law breaks down, leading to interesting physical phenomena such as the formation of current whirlpools. In this work, we study the voltage measured at a point in the device which is distinct from the point where current is injected or extracted. This is commonly known as the nonlocal voltage. We explore the relationship between the nonlocal voltage and the injected current and find it to be significantly different from predictions made by Ohm's law. We use this novel current-voltage relationship to build a rectifier and frequency multiplier - two devices commonly used in high-frequency detection, radar systems and telecommunications. We also report previously unseen periodic oscillations in the nonlocal voltage when the magnetic field perpendicular to the device is varied. Using high-resolution simulations, we show the these oscillations can not be explained by looking at individual electron paths, and arise due to contribution from all electrons that travel through the device.

Next-generation wireless networks must support a plethora of new applications ranging from the Internet of Things to virtual reality. Each one of these emerging applications have unique rate, reliability, and latency requirements that substantially differ from traditional services such as video streaming. Hence, there is a need for designing an efficient resource management framework that is taking into account different components that can affect the resource usage, including less obvious factors such as human behavior that contribute to the resource usage of the system. The use of machine learning for modeling mentioned components in a resource management system is a promising solution. This is because many hidden factors might contribute to the resource usage pattern of users or machine-type devices that can only be modeled using an end-to-end machine learning solution. Therefore, machine learning algorithms can be used either for modeling a complex factor such as the human brain's delay perception or for designing an end-to-end resource management system. The overarching goal of this dissertation is to develop and deploy machine learning frameworks that are suitable to model the various components of a wireless resource management system that must provide reliable and low latency service to the users. First, by explicitly modeling the limitations of the human brain, a concrete measure for the delay perception of human users in a wireless network is introduced. Then, a new probabilistic model for this delay perception is learned based on the brain features of a human user. Given the learned model for the delay perception of the human brain, a brain-aware resource management algorithm is proposed for allocating radio resources to human users while minimizing the transmit power and taking into account the reliability of both machine type devices and human users. Next, a novel experienced deep reinforcement learning (deep-RL) framework is proposed to provide model-free resource allocation for ultra reliable low latency communication (URLLC) in the downlink of a wireless network. The proposed, experienced deep-RL framework can guarantee high end-to-end reliability and low end-to-end latency, under explicit data rate constraints, for each wireless user without any models of or assumptions on the users' traffic. In particular, in order to enable the deep-RL framework to account for extreme network conditions and operate in highly reliable systems, a new approach based on generative adversarial networks (GANs) is proposed. After that, the problem of network slicing is studied in the context of a wireless system having a time-varying number of users that require two types of slices: reliable low latency (RLL) and self-managed (capacity limited) slices. To address this problem, a novel control framework for stochastic optimization is proposed based on the Lyapunov drift-plus-penalty method. This new framework enables the system to minimize power, maintain slice isolation, and provide reliable and low latency end-to-end communication for RLL slices. Then, a novel concept of three-dimensional (3D) cellular networks, that integrate drone base stations (drone-BS) and cellular-connected drone users (drone-UEs), is introduced. For this new 3D cellular architecture, a novel framework for network planning for drone-BSs as well as latency-minimal cell association for drone-UEs is proposed. For network planning, a tractable method for drone-BSs' deployment based on the notion of truncated octahedron shapes is proposed that ensures full coverage for a given space with minimum number of drone-BSs. In addition, to characterize frequency planning in such 3D wireless networks, an analytical expression for the feasible integer frequency reuse factors is derived. Subsequently, an optimal 3D cell association scheme is developed for which the drone-UEs' latency, considering transmission, computation, and backhaul delays, is minimized. Finally, the concept of super environments is introduced. After formulating this concept mathematically, it is shown that any two markov decision process (MDP) can be a member of a super environment if sufficient additional state space is added. Then the effect of this additional state space on model-free and model-based deep-RL algorithms is investigated. Next, the tradeoff caused by adding the extra state space on the speed of convergence and the optimality of the solution is discussed. In summary, this dissertation led to the development of machine learning algorithms for statistically modeling complex parts in the resource management system. Also, it developed a model-free controller that can control the resource management system reliably, with low latency, and optimally. Doctor of Philosophy Next-generation wireless networks must support a plethora of new applications ranging from the Internet of Things to virtual reality. Each one of these emerging applications have unique requirements that substantially differ from traditional services such as video streaming. Hence, there is a need for designing a new and efficient resource management framework that is taking into account different components that can affect the resource usage, including less obvious factors such as human behavior that contributes to the resource usage of the system. The use of machine learning for modeling mentioned components in a resource management system is a promising solution. This is because of the data-driven nature of machine learning algorithms that can help us to model many hidden factors that might contribute to the resource usage pattern of users or devices. These hidden factors can only be modeled using an end-to-end machine learning solution. By end-to-end, we mean the system only relies on its observation of the quality of service (QoS) for users. Therefore, machine learning algorithms can be used either for modeling a complex factor such as the human brain's delay perception or for designing an end-to-end resource management system. The overarching goal of this dissertation is to develop and deploy machine learning frameworks that are suitable to model the various components of a wireless resource management system that must provide reliable and low latency service to the users.

Next-generation cellular systems will rely on millimeter wave (mmWave) bands to meet the increasing demand for wireless connectivity from end user equipment. Given large available bandwidth and small-sized antenna elements, mmWave frequencies can support high communication rates and facilitate the use of multiple-input-multiple-output (MIMO) techniques to increase the wireless capacity. However, the small wavelength of mmWave yields severe path loss and high channel uncertainty. Meanwhile, using a large number of antenna elements requires a high energy consumption and heavy communication overhead for MIMO transmissions and channel measurement. To facilitate efficient mmWave communications, in this dissertation, the challenges of energy efficiency and communication overhead are addressed. First, the use of unmanned aerial vehicle (UAV), intelligent signal reflector, and device-to-device (D2D) communications are investigated to improve the reliability and energy efficiency of mmWave communications in face of blockage. Next, to reduce the communication overhead, new channel modeling and user localization approaches are developed to facilitate MIMO channel estimation by providing prior knowledge of mmWave links. Using advance mathematical tools from machine learning (ML), game theory, and communication theory, this dissertation develops a suite of novel frameworks using which mmWave communication networks can be reliably deployed and operated in wireless cellular systems, UAV networks, and wearable device networks. For UAV-based wireless communications, a learning framework is developed to predict the cellular data traffic during congestion events, and a new framework for the on-demand deployment of UAVs is proposed to offload the excessive traffic from the ground base stations (BSs) to the UAVs. The results show that the proposed approach enables a dynamical and optimal deployment of UAVs that alleviates the cellular traffic congestion. Subsequently, a novel energy-efficient framework is developed to reflect mmWave signals from a BS towards mobile users using a UAV-carried intelligent reflector (IR). To optimize the location and reflection coefficient of the UAV-carried IR, a deep reinforcement learning (RL) approach is proposed to maximize the downlink transmission capacity. The results show that the RL-based approach significantly improves the downlink line-of-sight probability and increases the achievable data rate. Moreover, the channel estimation challenge for MIMO communications is addressed using a distributional RL approach, while optimizing an IR-aided downlink multi-user communication. The results show that the proposed method captures the statistic feature of MIMO channels, and significantly increases the downlink sum-rate. Moreover, in order to capture the characteristics of air-to-ground channels, a data-driven approach is developed, based on a distributed framework of generative adversarial networks, so that each UAV collects and shares mmWave channel state information (CSI) for cooperative channel modeling. The results show that the proposed algorithm enables an accurate channel modeling for mmWave MIMO communications over a large temporal-spatial domain. Furthermore, the CSI pattern is analyzed via semi-supervised ML tools to localize the wireless devices in the mmWave networks. Finally, to support D2D communications, a novel framework for mmWave multi-hop transmissions is investigated to improve the performance of the high-rate low-latency transmissions between wearable devices. In a nutshell, this dissertation provides analytical foundations on the ML-based performance optimization of mmWave communication systems, and the anticipated results provide rigorous guidelines for effective deployment of mmWave frequency bands into next-generation wireless systems (e.g., 6G). Doctor of Philosophy Different kinds of new smart devices are invented and deployed every year. Emerging smart city applications, including autonomous vehicles, virtual reality, drones, and Internet-of-things, will require the wireless communication system to support more data transmissions and connectivity. However, existing wireless network (e.g., 5G and Wi-Fi) operates at congested microwave frequency bands and cannot satisfy needs of these applications due to limited resources. Therefore, a different, very high frequency band at the millimeter wave (mmWave) spectrum becomes an inevitable choice to manage the exponential growth in wireless traffic for next-generation communication systems. With abundant bandwidth resources, mmWave frequencies can provide the high transmission rate and support the wireless connectivity for the massive number of devices in a smart city. Despite the advantages of communications at the mmWave bands, it is necessary to address the challenges related to high-frequency transmissions, such as low energy efficiency and unpredictable link states. To this end, this dissertation develops a set of novel network frameworks to facilitate the service deployment, performance analysis, and network optimization for mmWave communications. In particular, the proposed frameworks and efficient algorithms are tailored to the characteristics of mmWave propagation and satisfy the communication requirements of emerging smart city applications. Using advanced mathematical tools from machine learning, game theory, and wireless communications, this dissertation provides a comprehensive understanding of the communication performance over mmWave frequencies in the cellular systems, wireless local area networks, and drone networks. The anticipated results will promote the deployment of mmWave frequencies in next-generation communication systems.

III-V compound Gallium Antimonide (GaSb), with a low bandgap of 0.72 eV at room temperature, is an attractive candidate for a variety of potential applications in optoelectronic devices. Ion implantation, among non-epitaxial methods, is a common and reliable doping technique to achieve local doping and obtain high-performance ohmic contacts in order to form a pn junction in such devices. An advantage of this technique over the diffusion method is the ability to perform a low-temperature process leading to accurate control of the dopant profile and avoiding Sb evaporation from GaSb surface occurring at 370 C. In this work, the effect of protons and sulfur ions as two implant species on the electrical behavior of MBE-grown undoped GaSb on semi-insulating (SI) GaAs was investigated via the Hall Effect. Protons and sulfur ions were implanted at room temperature (27 C) and 200 C, respectively, and rapid thermal annealing (RTA) was implemented at various temperatures and durations upon encapsulated GaSb. The damage induced by protons enhanced the hole density of GaSb up to around 10 times, whereas mobilities showed both increase and decrease compared to the un-implanted one, depending on the dose. While the activation of sulfur donors at an elevated temperature was anticipated after annealing sulfur implanted GaSb, instead it led to increase in p-type concentration, as the residual damage originated from sulfur implantation dominated substitutional doping. Furthermore, GaSb p/n photovoltaic devices were fabricated by applying sulfur implantation through silicon nitride layer at RT into an n-GaSb wafer (n-type base, p-type emitter). The device showed a rectifying current and photovoltaic characteristic. The J-V plot under AM1.5G illumination conditions, before and after an etch-back optimizing process, indicated lower short circuit current density J_sc, the same open circuit voltage V_oc, and higher fill factor FF, compared to the photovoltaic device with a p-type base. Also, both normalized series R_s and shunt R_p resistances in p/n diode indicated lower and higher values, respectively, as opposed to a GaSb p++/p diode, indicative of higher quality and lower manufacturing defects. Master of Science Generally, the photovoltaic effect is a process by which voltage or electric current is generated in a photovoltaic cell when exposed to light. A solar cell is a photovoltaic device, typically consisting a pn junction, that converts incident photon power into electrical power and delivered to a load to do electrical work for variety of applications. There are variety of methods to form a pn junction and fabricate such devices, among which ion implantation is a reliable doping technique. In this process, dopant ions are accelerated and smashed into a perfect semiconductor lattice, creating a cascade of damage that may displace a thousand atoms for each implanted ion and become activated after an annealing process. The ions themselves can act as either electron donors, make the semiconductor n-type, or electron acceptors, make it p-type. In this work, sulfur ions and protons, as two implant species, were implanted into separate Gallium Antimonide (GaSb) substrates and the effect of each on the electrical behavior of GaSb was investigated by Hall effect experiment. Both species raised hole carrier concentration. This behavior was not expected for sulfur ions as they would be assumed to act as electron donors after activation and convert the GaSb surface to an n-type semiconductor. It was identified that this behavior is due to the domination of created defects during implantation over the number of activated sulfur donors. The same characteristics were predicted and verified for proton implantation as well, the effect of which is just leaving damage in the lattice. Furthermore, to verify this method for converting n-type GaSb to p-type and fabricating a pn junction in GaSb for photovoltaic application, sulfur implantation into an n-type GaSb wafer was performed and optimized by removing the excess surface damage away from the device's metal contacts using wet etching. The device showed a diode-like rectifying current and photovoltaic characteristic. Some parameters such as short circuit current density J_sc, open circuit voltage V_oc, fill factor FF, and resistances (shunt and series) were measured and calculated using J-V plot under dark and illuminated conditions.

The Internet of Things (IoT) is a promising networking technology that will interconnect a plethora of heterogeneous wireless devices. To support the connectivity across a massive-scale IoT, the scarce wireless communication resources must be appropriately allocated among the IoT devices, while considering the technical challenges that arise from the unique properties of the IoT, such as device heterogeneity, strict communication requirements, and limited device capabilities in terms of computation and memory. The primary goal of this dissertation is to develop novel resource management frameworks using which resource-constrained IoT devices can operate autonomously in a dynamic environment. First, a comprehensive overview on the use of various learning techniques for wireless resource management in an IoT is provided, and potential applications for each learning framework are proposed. Moreover, to capture the heterogeneity among IoT devices, a framework based on cognitive hierarchy theory is discussed, and its implementation with learning techniques of different complexities for IoT devices with varying capabilities is analyzed. Next, the problem of dynamic, distributed resource allocation in an IoT is studied when there are heterogeneous messages. Particularly, a novel finite memory multi-state sequential learning is proposed to enable diverse IoT devices to reallocate the limited communication resources in a self-organizing manner to satisfy the delay requirement of critical messages, while minimally affecting the delay-tolerant messages. The proposed learning framework is shown to be effective for the IoT devices with limited memory and observation capabilities to learn the number of critical messages. The results show that the performance of learning framework depends on memory size and observation capability of IoT devices and that the learning framework can realize low delay transmission in a massive IoT. Subsequently, the problem of one-to-one association between resource blocks and IoT devices is studied, when the IoT devices have partial information. The one-to-one association is formulated as Kolkata Paise Restaurant (KPR) game in which an IoT device tries to choose a resource block with highest gain, while avoiding duplicate selection. Moreover, a Nash equilibrium (NE) of IoT KPR game is shown to coincide with socially optimal solution. A proposed learning framework for IoT KPR game is shown to significantly increase the number of resource blocks used to successful transmit compared to a baseline. The KPR game is then extended to consider age of information (AoI), which is a metric to quantify the freshness of information in the perspective of destination. Moreover, to capture heterogeneity in an IoT, non-linear AoI is introduced. To minimize AoI, centralized and distributed approaches for the resource allocation are proposed to enable the sharing of limited communication resources, while delivering messages to the destination in a timely manner. Moreover, the proposed distributed resource allocation scheme is shown to converge to an NE and to significantly lower the average AoI compared to a baseline. Finally, the problem of dynamically partitioning the transmit power levels in non-orthogonal multiple access is studied when there are heterogeneous messages. In particular, an optimization problem is formulated to determine the number of power levels for different message types, and an estimation framework is proposed to enable the network base station to adjust power level partitioning to satisfy the performance requirements. The proposed framework is shown to effectively increase the transmission success probability compared to a baseline. Furthermore, an optimization problem is formulated to increase sum-rate and reliability by adjusting target received powers. Under different fading channels, the optimal target received powers are analyzed, and a tradeoff between reliability and sum-rate is shown. In conclusion, the theoretical and performance analysis of the frameworks proposed in this dissertation will prove essential for implementing an appropriate distributed resource allocation mechanisms for dynamic, heterogeneous IoT environments. Doctor of Philosophy The Internet of Things (IoT), which is a network of smart devices such as smart phones, wearable devices, smart appliances, and environment sensors, will transform many aspects of our society with numerous innovative IoT applications. Those IoT applications include interactive education, remote healthcare, smart grids, home automation, intelligent transportation, industrial monitoring, and smart agriculture. With the increasing complexity and scale of an IoT, it becomes more difficult to quickly manage the IoT devices through a cloud, and a centralized management approach may not be viable for certain IoT scenarios. Therefore, distributed solutions are needed for enabling IoT devices to fulfill their services and maintain seamless connectivity. Here, IoT device management refers to the fact that the system needs to decide which devices access the network and using which resources (e.g., frequencies). For distributed management of an IoT, the unique challenge is to allocate scarce communication resources to many IoT devices appropriately. With distributed resource management, diverse IoT devices can share the limited communication resources in a self-organizing manner. Distributed resource management overcomes the limitations of centralized resource management by satisfying strict service requirements in a massive, complex IoT. Despite the advantages and the opportunities of distributed resource management, it is necessary to address the challenges related to an IoT, such as analyzing intricate interaction of heterogeneous devices, designing viable frameworks for constrained devices, and quickly adapting to a dynamic IoT. Furthermore, distributed resource management must enable IoT devices to communicate with high reliability and low delay. In this regard, this dissertation investigates these critical IoT challenges and introduces novel distributed resource management frameworks for an IoT. In particular, the proposed frameworks are tailored to realistic IoT scenarios and consider different performance metrics. To this end, mathematical frameworks and effective algorithms are developed by significantly extending tools from wireless communication, game theory, and machine learning. The results show that the proposed distributed wireless resource management frameworks can optimize key performance metrics and meet strict communication requirements while coping with device heterogeneity, massive scale, dynamic environment, and scarce wireless resources in an IoT.

Gallium Nitride (GaN) technology is capable of very high power levels but suffers from high non-linearity. With the advent of 5G technologies, high linearity is in greater demand due to complex modulation schemes and crowded RF (Radio Frequency) spectrum. Because of the non-linearity issue, GaN power amplifiers have to be operated at back-off input power levels. Operating at back-off reduces the efficiency of the power amplifier along-with the output power. This research presents a technique to linearize GaN amplifiers. The linearity can be improved by splitting a large device into multiple smaller devices and biasing them individually. This leads to the cancellation of the IMD3 (Third-order Intermodulation Distortion) components at the output of the FETs and hence higher linearity performance. This technique has been demonstrated in Silicon technology but has not been previously implemented in GaN. This research work presents for the first time the implementation of this technique in GaN Technology. By the application of this technique, improvement in IMD3 of 4 dBc has been shown for a 0.8-1.0 GHz PA (Power Amplifier), and 9.5 dBm in OIP3 (Third-order Intercept Point) for an S-Band GaN LNA, with linearity FOM (IP3/DC power) reaching up to 20. Large-signal simulation and analysis have been done to demonstrate linearity improvement for two parallel and four parallel FETs. A simulation methodology has been discussed in detail using commercial CAD software. A power sampler element is used to compute the IMD3 currents coming out of various FETs due to various bias currents. Simulation results show by biasing one device in Class AB and others in deep Class AB, IMD3 components of parallel FETs can be made out of phase of each other, leading to cancellation and improvement in linearity. Improvement up to 20 dBc in IMD3 has been reported through large-signal simulation when four parallel FETs with optimum bias were used. This technique has also been demonstrated in simulation for an X-Band MMIC PA from 8-10 GHz in GaN technology. Improvements up to 25-30 dBc were shown using the technique of biasing one device with Class AB and other with deep class AB/class B. The proposed amplifier achieves broadband linearization over the entire frequency compared to state-of-the-art PA's. The linearization technique demonstrated is simple, straight forward, and low cost to implement. No additional circuitry is needed. This technique finds its application in high dynamic range RF amplifier circuits for communications and sensing applications. Doctor of Philosophy Power amplifiers (PAs) and Low Noise Amplifiers (LNAs) form the front end of the Radio Frequency (RF) transceiver systems. With the advent of complex modulation schemes, it is becoming imperative to improve their linearity. Through this dissertation, we propose a technique for improving the linearity of amplifier circuits used for communication systems. Meanwhile, Gallium Nitride (GaN) is becoming a technology of choice for high-power amplifier circuits due to its higher power handling capability and higher breakdown voltage compared with Gallium Arsenide (GaAs), Silicon Germanium (SiGe) and Complementary Metal-Oxide-Semiconductor (CMOS) technologies. A circuit design technique of using multiple parallel GaN FETs is presented. In this technique, the multiple parallel FETs have independently controllable gate voltages. Compared to a large single FET, using multiple FETs and biasing them individually helps to improve the linearity through the cancellation of nonlinear distortion components. Experimental results show the highest linearity improvement compared with the other state-of-the-art linearization schemes. The technique demonstrated is the first time implementation in GaN technology. The technique is a simple and cost-effective solution for improving the linearity of the amplifier circuits. Applications include base station amplifiers, mobile handsets, radars, satellite communication, etc.

Gallium antimonide (GaSb) is a promising low-bandgap binary substrate for the fabrication of various infrared-based optoelectronic devices, particularly thermophotovoltaics (TPV). In order to make GaSb-based technologies like TPV more widely available, non-epitaxial dop- ing methods for GaSb must be pursued. Ion implantation is relatively unexplored for GaSb, and can offer advantages over the more common method of zinc diffusion, including higher flexibility with regards to substrate type and control over the resulting doping profile. Pre- vious work has shown beryllium (Be+) implantation to be a suitable method for fabricating a diode in an n-type GaSb substrate, opening the possibility for other ions to be considered for implanting into both n-type and p-type substrates. This work identifies sulfur (S+) as another species to investigate for this purpose. To do so, material and electrical characterization was done on S+ and beryllium implanted GaSb films grown onto a semi-insulating gallium arsenide (GaAs) substrate. X-ray Diffraction spectroscopy (XRD) and Atomic Force Microscopy (AFM) indicate that the post-implant anneal of 600 for 10 s repaired the implant damage in the bulk material, but left behind a damaged surface layer composed of coalesced vacancies. While the beryllium implant resulted in moderate doping concentrations corresponding to an activation percentage near 15 %, Hall Effect data showed that implanting S+ ions induced a strongly p-type behavior, with hole concentrations above 1 × 19 cm^3 and sheet hole densities 3.5 times higher than the total implanted dose. This strong p-type behavior is attributed to the remaining lattice damage caused by the implant, which induces a large density of acceptor-like defect states near the valence band edge. This technique was used on an unintentionally-doped p-type GaSb substrate to create a + /p junction. The implant process succeeded in producing a potential barrier similar to that of a hole-majority camel diode with a thin delta-doped region suitable for collecting diffused carriers from the p-type substrate. A post-fabrication etching process had the effect of strongly increasing the short circuit current density to as high as 41.8 mA/cm^2 and the open circuit voltage as high as 0.21 V by simultaneously removing a high carrier recombination surface layer. This etching process resulted in a broadband spectral response, giving internal quantum efficiencies greater than 90 %. Doctor of Philosophy Thermophotovoltaics (TPV) is a technology that converts light and other forms of electromagnetic energy into electrical power, much like a typical solar panel. However, instead of sunlight, the energy source used in a TPV system is a terrestrial heat source at a temperature range of 1250–1750 ◦C, whose radiation is primarily infrared (IR). The IR-absorbing qualities and commercial availability of the compound semiconductor gallium antimonide (GaSb) have made it a key component in the development of absorber devices for TPV-related systems. GaSb-based devices have most often been fabricated using epitaxy, a method in which layer(s) of material are ‘grown’ in a layer-by-layer fashion atop a substrate GaSb wafer to induce an interface between negatively-charged (n-type) and positively-charged (p-type) regions. In order to improve upon the scalability of TPV production, device fabrication methods for GaSb that avoid the use of epitaxy are sought after as a lower-cost alternative. In this work, sulfur ion implantation is examined as one of these methods, in which elemental sulfur ions are injected at a high energy into a p-type GaSb substrate. The implanted ions then alter the charge characteristics at the surface of the material, producing an electric field from which a photovoltaic (PV) device can be fabricated. The results of this study showed that by implanting sulfur ions, an extremely p-type (p++) layer was formed at the surface of the GaSb substrate, which was attributed to residual damage induced by the implant process. The resulting interface between the p++ surface and the moderately p-type GaSb substrate was found to induce an electric field suitable for a PV device. Removing the excess surface damage away from the device’s metal contacts resulted in an improvement in the output electrical currents, with measured values being significantly higher than that of other devices made using more common non-epitaxial fabrication methods. The success of this work demonstrates the advantages of using a p-type GaSb substrate in place of an n-type substrate, and could help diversify the types of TPV-related devices that can be produced.

Enhancing performance of power electronics converters has always been an interesting topic in the power electronics community. Over the years, researchers and engineers are developing new high performance component, novel converter topologies, smart control methods and optimal design procedures to improve the efficiency, power density, reliability and reducing the cost. Besides pursuing high performance, researchers and engineers are striving to modularize the power electronics converters, which provides redundancy, flexibility and standardization to the end users. The trend of modularization has been seen in photovoltaic inverters, telecommunication power supplies, and recently, HVDC applications. A systematic optimal design approach for modular power converters is developed in this dissertation. The converters are developed for aerospace applications where there are stringent requirement on converter form factor, loss dissipation, thermal management and electromagnetic interference (EMI) performance. This work proposed an optimal design approach to maximize the nominal power of the power converters considering all the constraints, which fully reveals the power processing potential. Specifically, this work studied three-phase active front-end converter, three-phase isolated ac/dc converter and inverter. The key models (with special attention paid to semiconductor switching loss model), detailed design procedures and key design considerations are elaborated. With the proposed design framework, influence of key design variables, e.g. converter topology, switching frequency, etc. is thoroughly studied. Besides optimal design procedure, control issues in paralleling modular converters are discussed. A master-slave control architecture is used. The slave controllers not only follow the command broadcasted by the master controller, but also synchronize the high frequency clock to the master controller. The control architecture eliminates the communication between the slave controllers but keeps paralleled modules well synchronized, enabling a fully modularized design. Furthermore, the implementation issues of modularity are discussed. Although modularizing converters under form factor constraints adds flexibility to the system, it limits the design space by forbidding oversized components. This work studies the influence of the form factor by exploring the maximal nominal power of a double-sized converter module and comparing it with that of two paralleled modules. The tradeoff between modularity and performance is revealed by this study. Another implementation issue is related to EMI. Scaling up system capacity by paralleling converter modules induces EMI issues in both signal level and system level. This work investigates the mechanisms and provides solutions to the EMI problems. Ph. D. As penetration of power electronics technologies in electric power delivery keeps increasing, performance of power electronics converters becomes a key factor in energy delivery efficacy and sustainability. Enhancing performance of power electronics converters reduces footprint, energy waste and delivery cost, and ultimately, promoting a sustainable energy use. Over the years, researchers and engineers are developing new technologies, including high performance component, novel converter topologies, smart control methods and optimal design procedures to improve the efficiency, power density, reliability and reducing the cost of power electronics converters. Besides pursuing high performance, researchers and engineers are striving to modularize the power electronics converters, enabling power electronics converters to be used in a “plug-and-play” fashion. Modularization provides redundancy, flexibility and standardization to the end users. The trend of modularization has been seen in applications that process electric power from several Watts to Megawatts. This dissertation discusses the design framework for incorporating modularization into existing converter design procedure, synergically achieving performance optimization and modularity. A systematic optimal design approach for modular power converters is developed in this dissertation. The converters are developed for aerospace applications where there is stringent v requirement on converter dimensions, loss dissipation, and thermal management. Besides, to ensure stable operation of the onboard power system, filters comprising of inductors and capacitors are necessary to reduce the electromagnetic interference (EMI). Owning to the considerable weight and size of the inductors and capacitors, filter design is one of the key component in converter design. This work proposed an optimal design approach that synergically optimizes performance and promotes modularity while complying with the entire aerospace requirement. Specifically, this work studied three-phase active front-end converter, three-phase isolated ac/dc converter and three-phase inverter. The key models, detailed design procedures and key design considerations are elaborated. Experimental results validate the design framework and key models, and demonstrates cutting-edge converter performance. To enable a fully modularized design, control of modular converters, with focus on synchronizing the modular converters, is discussed. This work proposed a communication structure that minimizes communication resources and achieves seamless synchronization among multiple modular converters that operate in parallel. The communication scheme is demonstrated by experiments. Besides, the implementation issues of modularity are discussed. Although modularizing converters under form factor constraints adds flexibility to the system, it limits the design space by forbidding oversized components. This work studies the impact of modularity by comparing performance of a double-sized converter module with two paralleled modules. The tradeoff between modularity and performance is revealed by this study.

The use of aerial platforms such as unmanned aerial vehicles (UAVs), popularly known as drones, has emerged as a promising solution for providing reliable and cost-effective wireless communications. In particular, UAVs can be quickly and efficiently deployed to support cellular networks and enhance their quality-of-service (QoS) by establishing line-of-sight communication links. With their inherent attributes such as mobility, flexibility, and adaptive altitude, UAVs admit several key potential applications in wireless systems. Remarkably, despite these inherent advantages of UAVbased communications, little work has analyzed the performance tradeoffs associated with using UAVs as aerial wireless platforms. The key goal of this dissertation is to develop the analytical foundations for deployment, performance analysis, and optimization of UAV-enabled wireless networks. This dissertation makes a number of fundamental contributions to various areas of UAV communications that include: 1) Efficient deployment of UAVs, 2) Performance evaluation and optimization, and 3) Design of new flying, three-dimensional (3D) wireless systems. For deployment, using tools from optimization theory, holistic frameworks are developed for the optimal 3D placement of UAV base stations in uplink and downlink scenarios. The results show that the proposed deployment approaches significantly improve the downlink coverage for ground users, and enable ultra-reliable and energy-efficient uplink communications in Internet of Things (IoT) applications. For performance optimization, a novel framework is developed for maximizing the performance of a UAV-based wireless system, in terms of data service, under UAVs’ flight time constraints. To this end, using the mathematical framework of optimal transport theory, the optimal cell associations, that lead to a maximum data service to ground users within the limited UAVs’ hover duration, are analytically derived. The results shed light on the tradeoff between hover time and quality-of-service in UAV-based wireless networks. For performance evaluation, this dissertation provides a comprehensive analysis on the performance of a UAV-based communication system in coexistence with a terrestrial network. In particular, a tractable analytical framework is proposed for analyzing the coverage and rate performance of a network with a UAV base station and deviceto-device (D2D) users. The results reveal the fundamental tradeoffs in such a UAV-D2D network that allow adopting appropriate system design parameters. Then, this dissertation sheds light on the design of three new drone-enabled wireless systems. First, a novel framework for effective use of cache-enabled UAVs in wireless networks is developed. The results demonstrate how the users’ quality of experience substantially improves by exploiting UAVs’ mobility and user-centric information. Second, a new framework is proposed for deploying and operating a drone-based antenna array system that delivers wireless service to ground users within a minimum time. The results show significant enhancement in QoS, spectral and energy efficiency while levering the proposed drone antenna array system. Finally, to effectively incorporate various use cases of drones ranging from aerial users to base stations, the new concept of a fully-fledged 3D cellular network is introduced. For this new type of 3D wireless network, a unified framework for deployment, network planning, and performance optimization is developed that yields a maximum coverage and minimum latency in the network. In a nutshell, the analytical foundations and frameworks presented in this dissertation provide key guidelines for effective design and operation of UAV-based wireless communication systems. Ph. D.

With the continued evolution of MEMS-based gas chromatography, the drive to develop new standalone systems with lower power consumptions and higher portability has increased. However, with improvements come tradeoffs, and trying to reduce the pressure drop requirements of previously reported semi-packed columns causes a significant sacrifice in separation efficiency. This thesis covers the techniques for evaluating the separation column in a gas chromatography system as well as the important parameters that have the most effect on a column’s efficiency. Ionic liquids are introduced as a stable and versatile stationary phase for micro separation columns. It then describes a MEMS-based separation column design utilizing density modulation of embedded micro-pillars which attempts to optimize the balance between separation efficiency and pressure drop. Master of Science Gas chromatography is a technique used by scientists to separate and identify chemical compounds present in a given test mixture. It is a versatile technique that can be used for qualitative and quantitative analysis of complex mixtures in a variety of applications. However, typical gas chromatography systems are confined to a lab because they are large and consume a lot of power. In order to overcome these problems, different research groups have focused their attention towards the development of portable MEMS-based gas chromatography systems. By miniaturizing the various components of a gas chromatography system, these two main issues can be alleviated. This thesis covers the strategies used to develop and evaluate the separation column of a gas chromatography system and introduce a new MEMS-based column design that will further reduce the power consumption.

The overall energy consumption of portable devices has been projected to triple over the next decade, growing to match the total power generated by the European Union and Canada by 2025. The rise of the internet-of-things (IoT) and ubiquitous and embedded computing has resulted in an exponential increase in such devices, wherein projections estimate that 50 billion smart devices will be connected and online by 2020. In order to alleviate the associated stresses placed on power generation and distribution networks, a holistic approach must be taken to conserve energy usage in electronic devices from the component to the circuit level. An effective approach to reduce power dissipation has been a continual reduction in operating voltage, thereby quadratically down-scaling active power dissipation. However, as state-of-the-art silicon (Si) complimentary metal-oxide-semiconductor (CMOS) field-effect transistors (FETs) enter sub-threshold operation in the ultra-low supply voltage regime, their drive current is noticeable degraded. Therefore, new energy-efficient MOSFETs and circuit architectures must be introduced. In this work, tunnel FETs (TFETs), which operate leveraging quantum mechanical tunneling, are investigated. A comprehensive investigation detailing electronic materials, to novel TFET device designs, to memory and logic digital circuits based upon those TFETs is provided in this work. Combined, these advances offer a computing platform that could save considerable energy and reduce power consumption in next-generation, ultra-low voltage applications. Ph. D.

The aggressive scaling of silicon (Si) based complementary metal-oxide-semiconductor (CMOS) transistor over the past 50 years has resulted in an exponential increase in device density, which consequentially has increased computation power rapidly. This has pronounced the necessity to scale the device's supply voltage (VDD) in to order to maintain low-power device operation. However, the scaling of VDD can degrade drive current significantly due to the low carrier mobility of Si. To overcome the key challenges of dimensional and voltage scaling required for low-power electronic operation without degradation of device characteristics, the adoption of alternate channel materials with low bandgap with superior transport properties will play a crucial role to improve the computation ability of the standard integrated circuit (IC). The requirement of high-mobility channel materials allows the industry to harness the potential of III-V semiconductors and germanium. However, the adoption of such high mobility materials as bulk substrates remains cost-prohibitive even today. Hence, another key challenge lies in the heterogeneous integration of epitaxial high-mobility channel materials on the established cost-effective Si platform. Furthermore, dimensional scaling of the device has led to a change in architecture from the conventional planar MOSFET to be modified to a 3-D Tri-gate architecture which provides fully depleted characteristics by increasing the inversion layer area and hence, providing superior electrostatic control of the device channel to address short channel effects such as subthreshold slope (SS) and drain induced barrier lowering (DIBL). The Tri-gate configuration provides a steeper SS effectively reducing leakage current (IOFF), thereby decreasing dynamic power consumption and increasing device performance. Recently, Tantalum silicate (TaSiOx) a high-k dielectric has been shown to exhibit superior interfacial quality on multiple III-V materials. However, there is still ambiguity as to the potential of short-channel devices incorporating alternate channel (III-V) materials which is the basis of this research, to demonstrate the feasibility of future high-mobility n-channel InGaAs material integration on Si for high- speed, low-power, high performance CMOS logic applications. Master of Science

The detection and measurement of gas properties has become essential to meet rigorous criteria of environmental unfriendly emissions and to increase the energy production efficiency. Although low cost devices such as pellistors, semiconductor gas sensors or electrochemical gas sensors can be used for these applications, they offer a very limited lifetime and suffer from cross-response and drift. On the contrary, gas sensors based on optical absorption offer fast response, zero drift, and high sensitivity with zero cross response to other gases. Hence, over the last forty years, diode laser spectroscopy (DLS) has become an established method for non-intrusive measurement of gas properties in scientific as well as industrial applications. Wavelength modulation spectroscopy (WMS) is derivative form of DLS that has been increasingly applied for making self-calibrated measurements in harsh environments due to its improved sensitivity and noise rejection capability compared to direct absorption detection. But, the complexity in signal processing and higher scope of error (when certain restrictions on operating conditions are not met), have inhibited the widespread use of the technique. This dissertation presents a simple and novel strategy for practical implementation of WMS with commercial diode lasers. It eliminates the need for pre-characterization of laser intensity parameters or making any design changes to the conventional WMS system. Consequently, sensitivity and signal strength remain the same as that obtained from traditional WMS setup at low modulation amplitude. Like previously proposed calibration-free approaches, this new method also yields absolute gas absorption line shape or absorbance function. Residual Amplitude Modulation (RAM) contributions present in the first and second harmonic signals of WMS are recovered by exploiting their even or odd symmetric nature. These isolated RAM signals are then used to estimate the absolute line shape function and thus removing the impact of optical intensity fluctuations on measurement. Uncertainties and noises associated with the estimated absolute line shape function, and the applicability of this new method for detecting several important gases in the near infrared region are also discussed. Absorbance measurements from 1% and 8% methane-air mixtures in 60 to 100 kPa pressure range are used to demonstrate simultaneous recovery of gas concentration and pressure. The system is also proved to be self-calibrated by measuring the gas absorbance for 1% methane-air mixture while optical transmission loss changes by 12 dB. In addition to this, a novel method for diode laser absorption spectroscopy has been proposed to accomplish spatially distributed monitoring of gases. Emission frequency chirp exhibited by semiconductor diode lasers operating in pulsed current mode, is exploited to capture full absorption response spectrum from a target gas. This new technique is referred to as frequency chirped diode laser spectroscopy (FC-DLS). By applying an injection current pulse of nanosecond duration to the diode laser, both spectroscopic properties of the gas and spatial location of sensing probe can be recovered following traditional Optical Time Domain Reflectometry (OTDR) approach. Based on FC-DLS principle, calibration-free measurement of gas absorbance is experimentally demonstrated for two separate sets of gas mixtures of approximately 5% to 20% methane-air and 0.5% to 20% acetylene-air. Finally, distributed gas monitoring is shown by measuring acetylene absorbance from two sensor probes connected in series along a single mode fiber. Optical pulse width being 10 nanosecond or smaller in the sensing optical fiber, a spatial resolution better than 1 meter has been realized by this technique. These demonstrations prove that accurate, non-intrusive, single point, and spatially distributed measurements can be made in harsh environments using the diode laser spectroscopy technology. Consequently, it opens the door to practical implementation of optical gas sensors in a variety of new environments that were previously too difficult. Ph. D.

Developing high efficiency solar cells for lower manufacturing costs has been a key objective for photovoltaic researchers to drive down the levelized cost of energy for solar power. In this pursuit, III-V compound semiconductor based solar cells have steadily shown performance improvement at approximately 1% (absolute) increase per year, with a recent record efficiency of 46% under concentrator and 32% under AM0. However, the expensive cost has made it challenging for III-V solar cells to compete with the mainstream Silicon (Si) technology. Novel approaches to lower down the cost per watt for III-V solar cells will position them to be among the key contenders in the renewable energy sector. Integration of such high-efficiency III-V multijunction solar cells on significantly cheaper and large area Si substrate has the potential to address the future LCOE roadmaps by unifying the high-efficiency merits of III-V materials with low-cost and abundance of Si. However, the 4% lattice mismatch, thermal mismatch, polar on non-polar epitaxy makes the direct growth of GaAs on Si challenging, rendering the metamorphic cell sensitive to dislocations. The focus of this dissertation is to investigate heterogeneously integrated 1J GaAs solar cells on Si substrate using germanium (Ge) as an intermediate buffer layer that will address mitigation of defects and dislocations between GaAs active cell structure and Ge “virtual” substrate on Si. The all-epitaxial molecular beam epitaxy (MBE)-grown thin (

Over the past four decades, aggressive scaling of silicon (Si) based complementary metal-oxide-semiconductor (CMOS) transistors has resulted in an exponential increase in device density, and thus an exponential increase in computing power. Increasing transistor density also results in increasing total power consumption and thus, necessitates supply voltage scaling in order to maintain low-power device operation. However, with increased supply voltage scaling, transistor drive current is significantly degraded due to the low carrier mobility of Si. To overcome the key challenges of device and voltage scaling required for low-power electronic operation without the degradation of transistor drive current requires the adoption of narrow bandgap channel materials with superior transport properties. However, the use of such materials as bulk substrates remains cost-prohibitive. Thus, another key challenge lies in the heterogeneous integration of high-mobility channel materials on affordable, established Si platform. Germanium (Ge) is an attractive candidate for next-generation low-power devices owing to its high electron and high hole mobility. Recently, AlAs/GaAs epilayers were demonstrated as a potential buffer platform for next-generation Ge-based electronics integrated on Si substrate. This research systematically investigates the structural characteristics of the Ge epitaxial layer heterogeneously integrated on Si using a composite III-V AlAs/GaAs buffer and the electrical characteristics of MOS capacitors (MOS-C's) fabricated on the aforementioned stack. Further passivation techniques and interface engineering is then pursued on MOS-C's fabricated from (100) and (110) crystallographically oriented epitaxial Ge integrated on AlAs/GaAs material stacks, balancing out effective oxide thickness (EOT) and reduction of oxide and interfacial traps in order to ensure a pristine interfacial quality for high-performance electronic applications. Further, work function tuning is demonstrated for the first time on the different crystallographically oriented epitaxial Ge integrated on AlAs/GaAs material stacks using two different gate metals, demonstrating the tunability of threshold voltage, VTH, required for transistor applications. The research demonstrates the feasibility of future high-mobility channel material integration on Si via large bandgap buffer architectures for high-speed, low-power, high-performance CMOS logic applications. Master of Science

The continued scaling of feature size in silicon (Si)-based complimentary metal-oxide-semiconductor (CMOS) technology has led to a rapid increase in compute power. Resulting from increases in device densities and advances in materials and transistor design, integrated circuit (IC) performance has continued to improve while operational power (VDD) has been substantially reduced. However, as feature sizes approach the atomic length scale, fundamental limitations in switching characteristics (such as subthreshold slope, SS, and OFF-state power dissipation) pose key technical challenges moving forward. Novel material innovations and device architectures, such as group IV and III-V materials and tunnel field-effect transistors (TFETs), have been proposed as solutions for the beyond Si era. TFETs benefit from steep switching characteristics due to the band-to-band tunneling injection of carriers from source to channel. Moreover, the narrow bandgaps of III-V and germanium (Ge) make them attractive material choices for TFETs in order to improve ON-state current and reduce SS. Further, Ge grown on InₓGa₁₋ₓAs experiences epitaxy-induced strain (ε), further reducing the Ge bandgap and improving carrier mobility. Due to these reasons, the ε-Ge/InₓGa₁₋ₓAs system is a promising candidate for future TFET architectures. In addition, the ability to tune the bandgap of Ge via strain engineering makes ε-Ge/InₓGa₁₋ₓAs heterostructures attractive for nanoscale group IV-based photonics, thereby benefitting the monolithic integration of electronics and photonics on Si. This research systematically investigates the material, optical, and heterointerface properties of ε-Ge/InₓGa₁₋ₓAs heterostructures on GaAs and Si substrates. The effect of strain on the heterointerface band alignment is comprehensively studied, demonstrating the ability to modulate the effective tunneling barrier height (Ebeff) and thus the threshold voltage (VT), ON-state current, and SS in future ε-Ge/InₓGa₁₋ₓAs TFETs. Further, band structure engineering via strain modulation is shown to be an effective technique for tuning the emission properties of Ge. Moreover, the ability to heterogeneously integrate these structures on Si is demonstrated for the first time, indicating their viability for the development of next-generation high performance, low-power logic and photonic integrated circuits on Si. Master of Science

Instrument miniaturization is led by the desire to perform rapid diagnosis in remote areas with high throughput and low cost. In addition, miniaturized instruments hold the promise of consuming small sample volumes and are thus less prone to cross-contamination. Gas chromatography (GC) is the leading analytical instrument for the analysis of volatile organic compounds (VOCs). Due to its wide-ranging applications, it has received great attention both from industrial sectors and scientific communities. Recently, numerous research efforts have benefited from the advancements in micro-electromechanical system (MEMS) and nanotechnology based solutions to miniaturize the key components of GC instrument (pre-concentrator/injector, separation column, valves, pumps, and the detector). The purpose of this dissertation is to address the critical need of developing a micro GC system for various field- applications. The uniqueness of this work is to emphasize on the importance of integrating the basic components of μGC (including sampling/injection, separation and detection) on a single platform. This integration leads to overall improved performance as well as reducing the manufacturing cost of this technology. In this regard, the implementation of micro helium discharge photoionization detector (μDPID) in silicon-glass architecture served as a major accomplishment enabling its monolithic integration with the micro separation column (μSC). For the first time, the operation of a monolithic integrated module under temperature and flow programming conditions has been demonstrated to achieve rapid chromatographic analysis of a complex sample. Furthermore, an innovative sample injection mechanism has been incorporated in the integrated module to present the idea of a chip-scale μGC system. The possibility of using μGC technology in practical applications such as breath analysis and water monitoring is also demonstrated. Moreover, a nanotechnology based scheme for enhancing the adsorption capacity of the microfabricated pre-concentrator is also described. Ph. D.

Biaxial tensile strain has been shown to greatly enhance the optoelectronic properties of epitaxial germanium (Ge) layers. As a result, tensile-Ge (and#949t-Ge) layers grown on larger lattice constant InGaAs or GeSn have attracted great research interest. However, no previous studies have investigated the plastic relaxation occurring in these and#949t-Ge layers. Here, we experimentally demonstrate that plastic relaxation occurs in nearly all and#949t-Ge epitaxial layers that are of practical interest for optoelectronic applications, even when layers may still exhibit strain-enhanced characteristics. We show arrays of misfit dislocations (MDs), which are mostly disassociated, form at the and#949t-Ge/InGaAs interface for and#949t-Ge layers as thin as 15 nm with less than 1% total mismatch. Wedge geometry of plain view transmission electron microscopy (PV-TEM) foils is utilized to carry out a depth dependent investigation MD spacing for a range of and#949t-Ge/InGaAs heterostructures. MD spacing measured by PV-TEM is correlated to and#949t-Ge layer relaxation measured by high-resolution x-ray diffraction. We confirm very low relaxation (< 10% relaxed) in and#949t-Ge layers does not imply they have been coherently grown. We demonstrate plastic relaxation in the and#949t-Ge layer is acutely sensitive to grown-in threading dislocations (TDs) in the template material, and that reducing TD density is critical for maximizing strain retention. Given that and#949t-Ge layer thicknesses of 150+ nm with greater than 1% tensile strain are desired for optoelectronic devices, this work suggests that MDs may inevitably be present at and#949t-Ge/InGaAs heterointerfaces in practical devices, and that the effect of MDs on optoelectronic performance must be better understood. Master of Science

Achieving high efficiency solar cells and concurrently driving down the cell cost has been among the key objectives for photovoltaic researchers to attain a lower levelized cost of energy (LCOE). While the performance of silicon (Si) based solar cells have almost saturated at an efficiency of ~25%, III-V compound semiconductor based solar cells have steadily shown performance improvement at approximately 1% (absolute) increase per year, with a recent record efficiency of 46%. However, the expensive cost has made it challenging for the high efficiency III-V solar cells to compete with the mainstream Si technology. Novel approaches to lower down the cost per watt for III-V solar cells will position them to be among the key contenders in the renewable energy sector. Integration of such high-efficiency III-V multijunction solar cells on significantly cheaper and large area Si substrate has the potential to address the future LCOE roadmaps by unifying the high-efficiency merits of III-V materials with low-cost and abundance of Si. However, the 4% lattice mismatch, thermal mismatch polar-on-nonpolar epitaxy makes the direct growth of GaAs on Si challenging, rendering the metamorphic cell sensitive to dislocations. The focus of this dissertation is to systematically investigate heterogeneously integrated III-V multijunction solar cells on Si substrate. Utilizing a combination of comprehensive solar cell modeling and experimental techniques, we seek to better understand the material properties and correlate them to improve the device performance, with simulation providing a very valuable feedback loop. Key technical design considerations and optimal performance projections are discussed for integrating metamorphic III-V multijunction solar cells on Si substrates for 1-sun and concentrated photovoltaics. Key factors limiting the “GaAs-on-Si” cell performance are identified, and novel approaches focused on minimizing threading dislocation density are discussed. Finally, we discuss a novel epitaxial growth path utilizing high-quality and thin epitaxial Ge layers directly grown on Si substrate to create virtual “Ge-on-Si” substrate for III-V-on-Si multijunction photovoltaics. With the plummeting price of Si solar cells accompanied with the tremendous headroom available for improving the III-V solar cell efficiencies, the future prospects for successful integration of III-V solar cell technology with Si substrate looks very promising to unlock an era of next generation of high-efficiency and low-cost photovoltaics. Ph. D.

Advances in micro-electro-mechanical-systems (MEMS) along with nanotechnology based methods have enabled the miniaturization of analytical chemistry instrumentation. The broader aim is to provide a portable, low-cost, and low-power platform for the real-time detection and identification of organic compounds in a wide variety of applications. A benchtop gas chromatography (GC) system is considered a gold standard for chemical analysis by analytical chemists. Similarly, miniaturization of key GC components (preconcentrator, separation column, detector, and pumps) using micro- and nanotechnology based techniques is an on-going research field. This dissertation specifically deals with the design, fabrication, coating, and chromatographic testing of microfabricated separation columns for GC. This work can be broadly categorized into three research areas: design and development of new column designs, introduction of new stationary phases and the development of novel fabrication methodologies for integrating functionalized thin-film into microchannels for chromatographic separations. As a part of this research, two high performance new micro column designs namely width-modulated and high-density semi-packed columns are introduced for the first time. Similarly, two new types of functionalized stationary phases are also demonstrated i.e. a highly stable and homogenous silica nanoparticles coating deposited using a layer-by-layer self-assembly scheme and a highly conformal functionalized thin aluminum oxide film deposited using atomic layer deposition. Moreover, novel thin-film patterning methods using different microfabrication technologies are also demonstrated for high-aspect ratio multicapillary and semi-packed columns. Ph. D.

Reducing supply voltage is a promising way to address the power dissipation in nano-electronic circuits. However, the fundamental lower limit of subthreshold slope (SS) within metal-oxide-semiconductor field-effect transistors (MOSFETs) is a major obstacle to further scaling the operation voltage without degrading ON/OFF-ratio in today's integrated circuits. Tunnel field-effect transistors (TFETs) benefit from steep switching characteristics due to the quantum-mechanical tunneling injection of carriers from source to channel, rather than by conventional thermionic emission in MOSFETs. TFETs based on group III-V compound semiconductor and Ge heterostructures further improve the ON-state current and reduce SS due to the low bandgap energies and smaller carrier tunneling mass. The mixed arsenide/antimonide (As/Sb) InxGa1-xAs/GaAsySb1-y and Ge/InxGa1-xAs heterostructures allow a wide range of bandgap energies and various band alignments depending on the alloy compositions in the source and channel materials. Band alignments at source/channel heterointerface can be well modulated by carefully controlling the compositions of the InxGa1-xAs or GaAsySb1-y. In particular, this research systematically investigate the development and optimization of low-power TFETs using mixed As/Sb and Ge/InxGa1-xAs based heterostructures including: basic working principles, design considerations, material growth, interface engineering, material characterization, band alignment determination, device fabrication, device performance investigation, and high-temperature reliability. A comprehensive study of TFETs using mixed As/Sb and Ge/InxGa1-xAs based heterostructures shows superior structural properties and distinguished device performances, both of which indicate the mixed As/Sb and Ge/InxGa1-xAs based TFET as a promising option for high performance, low standby power and energy efficient logic circuit application. Ph. D.

This research presents design techniques for a linear power amplifier with high efficiency in wireless handsets. The power amplifier operates with high efficiency at the saturated output power, maintains high linearity with enhanced efficiency at back-off power levels, and covers a broadband frequency response. The amplifier is thus able to operate in multiple modes (2G/2.5G/3G/4G). The design techniques provide contributions to current research in handset power amplifiers, especially to the converged power amplifier architecture, to reduce the number of power amplifiers within the handset while covering all standards and frequency bands around the globe. Three main areas of interest in power amplifier design are investigated: high power efficiency; high linearity; and broadband frequency response. Multiple techniques for improving the efficiency are investigated with the focus on maintaining linear operation. The research applies a new technique to the handset industry, class-J, to improve the power efficiency while avoiding the practical issues that hinder the typical techniques (class-AB and class-F). Class-J has been implemented using GaN FET in high power applications. To our knowledge, this work provides the first implementation of class-J using GaAs HBT in a handset power amplifier. The research investigates the linearity, and the nature and causes of nonlinearities. Multiple concepts for improving the linearity are presented, such as avoiding odd-degree harmonics, and linearizing the relationship between the output current and the input voltage of the amplifier at the fundamental frequency. The concept of bias depression in HBT transistors is introduced with a bias circuit that reduces the bias-offset effect to improve linearity at high output power. A design methodology is presented for broadband matching networks, including the component loss. The methodology offers a quick and accurate estimation of component values, giving more degrees of freedom to meet the design specifications. It enables a trade-off among high out-of-band attenuation, number/size of components, and power loss within the network. Although the main focus is handset power amplifiers, most of the developed techniques can be applied to a wide range of power amplifiers. Ph. D.

Energy distribution in a conventional magnetic component is generally not at a designer's disposal. In a conventional toroidal inductor, the energy density is inversely proportional to the square of the radius. Thus, a designer would be unable to prescribe uniform field distribution to fully utilize the inductor volume for storing magnetic energy. To address this problem a new inductor design, called a "constant-flux" inductor, is introduced in this thesis. This new inductor has the core and windings configured to distribute the magnetic flux and energy relatively uniformly throughout the core volume to achieve power density higher than that of a conventional toroidal inductor. The core of this new inductor design is made of concentric cells of magnetic material, and the windings are wound in the gaps between the cells. This structure is designed to avoid crowding of the flux, thus ensuring lower core energy losses. In addition, the windings are patterned for shorter length and larger area of cross-section to facilitate lower winding energy losses. Based on this approach, a set of new, constant flux inductor/transformer designs has been developed. This design set is based on specific input parameters are presented in this thesis. These parameters include the required inductance, peak and rms current, frequency of operation, permissible dc resistance, material properties of the core such as relative permeability, maximum permissible magnetic flux density for the allowed core loss, and Steinmetz parameters to compute the core loss. For each constant flux inductor/transformer design, the winding loss and core loss of the magnetic components are computed. In addition, the quality factor is used as the deciding criterion for selection of an optimized inductor/transformer design. The first design presented in this thesis shows that for the same maximum magnetic field intensity, height, total stored energy, and material, the footprint area of the new five-cell constant-flux inductor is 1.65 times less than that of an equivalent conventional toroidal inductor. The winding loss for the new inductor is at least 10% smaller, and core loss is at least 1% smaller than that in conventional inductors. For higher energy densities and taller inductors, an optimal field ratio of the dimensions of each cell (α = Rimin/Rimax) and a larger number of cells is desired. However, there is a practical difficulty in realizing this structure with a larger number of cells and higher field ratio α. To address this problem, an inductor design is presented that has a footprint area of a three-cell constant-flux inductor (α = 0.6) that is 1.48 times smaller in comparison to an equivalent conventional toroidal inductor. For the same maximum magnetic flux density, height, material, and winding loss, the energy stored in this new three-cell constant-flux inductor (α = 0.6) is four times larger than that of an equivalent conventional toroidal inductor. Finally, new designs for application-specific toroidal inductors are presented in this thesis. First, a constant-flux inductor is designed for high-current, high-power applications. An equivalent constant-flux inductor to a commercially available inductor (E70340-010) was designed. The height of this equivalent inductor is 20% less than the commercial product with the same inductance and dc resistance. Second, a constant-flux inductor design of inductance 1.2 µH was fabricated using Micrometal-8 for the core and flat wire of 0.97 mm x 0.25 mm for the conductor. The core material of this inductor has relative permeability < 28 and maximum allowed flux density of 3600 Gauss. The dc resistance of this new, constant flux inductor was measured to be 14.4 mΩ. Master of Science

The focus of this research is the isolation of waterborne pathogens which are one of the grand challenges to human health, costing the lives of about 2.5 million people worldwide each year. The aim was to develop new microfluidic techniques for selectively concentrating and detecting waterborne pathogens. Detection of microbes in water can greatly help reduce deaths; however, analytical instruments cannot readily detect them due to the extreme dilution of these microbes, and hence, require significant sample concentration. Current methods are expensive and either require days to process or are not sufficiently robust for water monitoring. Microfluidic chips based on insulator-based dielectrophoresis (iDEP) provide a promising solution to these problems and have been previously used to selectively concentrate biological particle such as bacteria. The microfluidic devices in this work were created with a 3D mircofabrication technique, which we also developed as part of this project. The core process of the technique is the etching of 3D structures in silicon with a single plasma etch utilizing an effect known as reactive ion etch lag (RIE lag). Using this unique process, 3D devices are fabricated in both silicon and the polymer polydimenthylsiloxane (PDMS). Using both numerical modeling and experimental results, we show how these 3D structures enhance the performance of the dielectrophoretic devices. The main findings indicate that 3D structures can help reduce Joule heating in the devices and lower the applied voltage necessary to operate the devices. Additionally, within this work, we develop a new dielectrophoresis technique called off-chip passivated-electrode, insulator-based dielectrophoresis microchip (O"DEP). This technique combines the sensitivity of electrode-based dielectrophoresis (eDEP) with the high-throughput and inexpensive device characteristics of insulator-based dielectrophoresis. The result is a cartridge based system which is accessible, economical, high-performance, and high-throughput technologies allowing timely detection of pathogenic bacteria. Ph. D.

Emerging memory technologies are being intensively investigated for extending Moore\'s law in the next decade. The conductive bridge random access memory (CBRAM) is one of the most promising candidates. CBRAM shows unique nanoionics-based filamentary switching mechanism. Compared to flash memory, the advantages of CBRAM include excellent scalability, low power consumption, high OFF-/ON-state resistance ratio, good endurance, and long retention. Besides the nonvolatile memory applications, resistive switching devices implement the function of memristor which is the fourth basic electrical component. This research presents the characterization and modeling of Cu/TaOx/Pt resistive switching devices. Both Cu and oxygen vacancy nanofilaments can conduct current according to the polarity of bias voltage. The volatile resistive switching phenomenon has been observed on Cu/TaOx/delta-Cu/Pt devices and explained by a flux balancing model. The resistive devices are also connected in series and in anti-parallel manner. These circuit elements are tested for chaotic neural circuit. The quantum conduction has been observed in the I-V characteristics of devices, evidencing the metallic contact between the nanofilament and electrodes. The model of filament radial growth has been developed to explain the transient I-V relation and multilevel switching in the metallic contact regime. The electroforming/SET and RESET processes have been simulated according to the mechanism of conductive filament formation and rupture and validated by experimental results. The Joule and Thomson heating effects have also been investigated for the RESET processes. Ph. D.

This thesis investigates the impact of doping on the optical and structural characteristics of cerium oxide (ceria) nanoparticles synthesized using chemical precipitation. The dopants selected are samarium and neodymium, which have positive association energy with oxygen vacancies in the ceria host, and negative association lanthanides, holmium and erbium, as well as two metal dopants, aluminum and iron. Characteristics measured are absorption and fluorescence spectra and the diameter and lattice parameter of ceria. Analysis of the characteristics indicates qualitatively that the dopant controls the O-vacancy concentration and the ratio of the two cerium ionization states: Ce+3 and Ce+4. A novel conclusion is proposed that the negative association lanthanide dopants can act as O-vacancies scavengers in ceria while the O-vacancy concentration increases in ceria doped with positive association lanthanide elements. Doped ceria nanoparticles are evaluated in two applications: dissolved oxygen (DO) sensing and up-conversion. In the first application, ceria doped with either Sm or Nd and ceria doped with aluminum have a strong correlation between the fluorescence quenching with the DO concentration in the aqueous solution in which the ceria nanoparticles are suspended. Stern-Volmer constants (KSV) of doped ceria are found to strongly depend upon the O-vacancy concentration and are larger than some of the fluorescent molecular probes currently used to measure DO. The KSV measured between 25-50oC is found to be significantly less temperature dependent as compared to the constants of commercially-available DO molecular probes. In the second application, up-conversion, ceria nanoparticles doped with erbium and an additional lanthanide, either Sm or Nd, are exposed to IR radiation at 780 nm. Visible emission is only observed after the nanoparticles are calcinated at high temperature, greatly diminishing the concentration of O-vacancies. It is concluded that O-vacancies do not play a dominant role in up-conversion, unlike that drawn for down-conversion, where the fluorescence intensity is strongly correlated with the O-vacancy concentration. Correlations between annealing temperatures, dopant, and dopant concentrations with the power dependence of up-conversion on the pump and the origin of the intensities of the visible emission are presented. These studies show the promise of doped ceria nanoparticles. Ph. D.

There is an increased interest in the Conductive Bridge Random Access Memory (CBRAM) and Resistive Random Access Memory (RRAM) because of their excellent scaling potential, low power consumption, high switching speed, good retention and endurance properties. Although, various mechanisms have been proposed to explain the switching behavior in CBRAM devices, i.e. metal ion migration and subsequent formation and rupture of conductive filament, formation of conductive path via oxygen ion transport etc, there are still many aspects of these mechanisms that are little understood or are being disputed. This work probes the details of the switching mechanisms on a new level and asks questions like: 1) How is the formation of nanofilament affected by various degrees of Cu diffusion stopping power of the inert electrode? To answer this question, resistive switches with very thin Cu layers covering the Pt electrode were fabricated and analyzed. 2) How does a limited source of active ions impact the formation and rupture of nanofilaments? To answer this question, new samples with limited Cu supply were fabricated and analyzed. 3) What is the mechanism of nanofilament formation in Pt/TaOx/Pt resistive switches where the active copper electrode is removed and replaced by inert Pt electrode. 4) What are the most suitable conditions (material structure of the device and operation conditions) to set and reset multi nanofilaments? This work summarizes the current status of analysis of the data obtained while attempting to explain interesting phenomena like volatile switching and multiple filament formation experienced by modifying the switch structures. Master of Science

With looming energy crisis across the globe, achieving high efficiency and low cost solar cells have long been the key objective for photovoltaic researchers. III-V compound semiconductor based multijunction solar cells have been the dominant choice for space power due to their superior performance compared to any other existing solar cell technologies. In spite of unmatched performance of III-V solar cells, Si cells have dominated the terrestrial market due to their lower cost. Most of the current III-V solar cells are grown on Ge or GaAs substrates, which are not only smaller in diameter, but are also more expensive than Si substrate. Direct integration of high efficiency III-V solar cells on larger diameter, cheaper and readily available Si substrate is highly desirable for increased density, low-cost and lightweight photovoltaics. However, the polar-on-nonpolar epitaxy, the thermal mismatch and the 4% lattice mismatch makes the direct growth of GaAs on Si challenging, rendering the metamorphic cell sensitive to dislocations. The focus of this work is to investigate and correlate the impact of threading dislocation density on the performance of lattice-mismatched single-junction (1J) GaAs and dual-junction (2J) InGaP/GaAs solar cells on Si substrate. Utilizing our calibrated dislocation-assisted modeling process, we present the design methodology to optimize the structure of 2J InGaP/GaAs solar cell on Si substrate. Our modeling results suggest an optimistic future for integrating III-V solar cell technology on Si substrate and will be useful for future design and prediction of metamorphic III-V solar cell performance on Si substrate. Master of Science