<p dir="ltr">Transitioning to a carbon-neutral future will require a broad portfolio of green energy generation and storage solutions. With the abundant availability of solar radiation across the Earth’s surface, energy generation from photovoltaics (PVs) will be an important part of this green energy portfolio. While silicon-based solar cells currently dominate the PV market, temperatures exceeding 1000 °C are needed for purification of silicon, and batch processing of silicon wafers limits how rapidly Si-based PV can be deployed. Furthermore, silicon’s indirect band gap necessitates absorber layers to exceed 100 µm thick, limiting its applications to rigid substrates.</p><p dir="ltr">Solution processed thin-film solar cells may allow for the realization of continuous, high-throughput manufacturing of PV modules. Thin-film absorber materials have direct band gaps, allowing them to absorb light more efficiently, and thus, they can be as thin as a few hundred nanometers and can be deposited on flexible substrates. Solution deposition of these absorber materials utilizing molecular precursor-based inks could be done in a roll-to-roll format, drastically increasing the throughput of PV manufacturing, and reducing installation costs. In this dissertation, solution processed synthesis and the characterization of two emerging direct band gap absorber materials consisting of earth abundant elements is discussed: the enargite phase of Cu₃AsS₄ and the distorted perovskite phase of BaZrS₃.</p><p dir="ltr">The enargite phase of Cu₃AsS₄ (ENG) is an emerging PV material with a 1.42 eV band gap, making it an ideal single-junction absorber material for photovoltaic applications. Unfortunately, ENG-based PV devices have historically been shown to have low power conversion efficiencies, potentially due to defects in the material. A combined computational and experimental study was completed where DFT-based calculations from collaborators were used inform synthesis strategies to improve the defect properties of ENG utilizing new synthesis techniques, including silver alloying, to reduce the density of harmful defects.</p><p dir="ltr">Chalcogenide perovskites are viewed as a stable alternative to halide perovskites, with BaZrS₃ being the most widely studied. With a band gap of 1.8 eV, BaZrS₃ could be an excellent wide-bandgap partner for a silicon-based tandem solar cell.Historically, sputtering, and solid-state approaches have been used to synthesize chalcogenide perovskites, but these methods require synthesis temperatures exceeding 800 °C, making them incompatible with the glass substrates and rear-contact layers required to create a PV device. In this dissertation, these high synthesis temperatures are bypassed through the development of a solution-processed deposition technique.A unique chemistry was developed to create fully soluble molecular precursor inks consisting of alkaline earth metal dithiocarboxylates and transition metal dithiocarbamates for direct-to-substrate synthesis of BaZrS₃ and BaHfS₃ at temperatures below 600 °C.</p><p dir="ltr">However, many challenges must be overcome before chalcogenide perovskites can be used for the creation of photovoltaic devices including oxide and Ruddlesden-Popper secondary phases, isolated grain growth, and deep level defects. Nevertheless, the development of a moderate temperature solution-based synthesis route makes chalcogenide perovskite research accessible to labs which do not have high temperature furnaces or sputtering equipment, further increasing research interest in this quickly developing absorber material.</p>

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Wave energy has the potential to provide an energy resource in this challenging energyenvironment. Wave energy converters are devices used to extract this energy and convertit into electricity. Wave Carpet is an example of such a novel wave energy converters andin its final form, it consists of a submerged membrane which covers an arbitrarily largearea above the sea floor. Incident waves create a pressure difference between the upper andlower surfaces, which triggers an up-and-down movement. The power take-off attached tothe surfaces serve to restrict this movement and thereby extract hydraulic power which isconverted to electricity.The Wave Carpet, is a type of wave energy converter that is beingdeveloped at University of California Berkeley′s Theoretical and Applied Fluid DynamicsLaboratory (TAFLab).The thesis aims at modeling and designing the different power conversion chainof the entire wave energy converter device. The process of energy conversion that yieldsthe required electrical energy for connecting a wave energy converter to an electricalnetwork is termed as the power conversion chain. A detailed electro-mechanical modelof the wave energy converter system connected to power grid is developed in theMatlab/SIMULINK environment and its corresponding generator and hydraulic controlstructure is implemented. The simulation response of the wave energy converter alongwith the power conversion chain is investigated. / Vågenergi har potential att bli en energiresurs i en utmanande energimiljö. Vågkraftverkär maskiner som används till att utvinna denna energi och omvandla den till elektricitet.Wave Carpet är ett exempel på ett vågkraftverk som i sitt slutglitiga stadie bestårav ett nedsänkt membran som täcker ett godtyckligt stort område ovanför sjöbotten.Inkommande vågor skapar en tryckskillnad mellan den övre och nedre ytan som gerupphov till en lodrätt rörelse. De mekaniska armarna kopplade till membranet bromsardenna rörelse och kan genom hydraulik omvandla bromsenergin till elektricitet. The WaveCarpet är en typ av vågkraftverk som utvecklas vid University of California Berkeley′sTheoretical and Applied Fluid Dynamics Laboratory (TAFLab).Uppsatsen syftar till att modellera och designa effektomvandlingskedjan i ett sådantvågkraftverk. Energiomvandlings processen som ger upphov till elektriciteten via ettvågkraftverk är benämnt som effektomvandlingskedjan. En detaljerad elektro-mekaniskmodell över ett vågkraftverksystem kopplat till ett elnät med motsvarande generator ochhydraliska regulatorer är utvecklad i Matlab/Simulink miljön. Simuleringsresultaten fråndet modellerade vågkraftverket undersöks tillsammans med effektomvandlingskedjan.

The size reduction of transistors has been the main reason for a successful development of semiconductor integrated circuits over the last decades. Because of the physically limited downscaling of transistors, alternative technologies namely the information processing and nonvolatile resistive switches (also termed memristors) have come into focus. Memristors reveal a fast switching speed, long retention time, and stable endurance. Nonvolatile analog bipolar resistive switching with a considerable large On/Off ratio is reported in BiFeO3 (BFO)-based resistive switches. So far resistive switches are mainly applied in memory applications or logic operations. Given the excellent properties of BFO based memristors, the further exploration of functionalities for memristive devices is required. A new approach for hardware based cryptographic system was developed within the framework of this dissertation. By studying the power conversion efficiencies on BFO memristor at various harmonics, it has been shown that two sets of clearly distinguishable power ratios are achievable when the BFO memristor is set into high or into low resistance state. Thus, a BFO-based binary encoding system can be established. As an example the unrecoverable seizure information from encoded medical data suggests the proper functioning of the proposed encryption system. Aside from cryptographic functionality, the single pairing spike timing dependent plasticity (STDP) in BFO-based artificial synapses is demonstrated, which can be considered as the cornerstone for energy-efficient and fast hardware-based neuromorphic networks. In comparison to the biological driven realistic way, only single one pairing of pre- and postsynaptic spikes is applied to the BFO-based artificial synapse instead of 60-80 pairings. Thus, the learning time constant of STDP function can be reduced from 25 ms to 125 us. / In den letzten Jahrzehnten war die Größenreduktion von Transistoren einer der Hauptgründe für die Leistungssteigerung von integrierten Halbleiterschaltungen. Aufgrund des physikalisch beschränkten Skalierungspotentials, werden alternative Technologien für Halbleiterschaltungen entwickelt. Dazu zählen neuartige Widerstandsschalter, sogenannte Memristoren, welche wegen ihrer schnellen Schaltgeschwindigkeit, langen Speicherzeit und stabilen Haltbarkeit in den Fokus der Forschung gerückt sind. Das nichtflüchtige analoge bipolare Schalten des Widerstandwertes mit einem On/Off Verhältnis größer als 100 wurde in BiFeO 3 (BFO)-basierten Widerstands-schaltern beobachtet. Bisher wurden Widerstandsschalter hauptsächlich als Speicher oder in rekonfigurierbaren Logikschaltungen verwendet. Aufgrund der ausgezeichneten Eigenschaften von BFO-basierten Memristoren, ist die Untersuchung weiterer neuer Funktionalitäten vielversprechend. Als neuer Ansatz für ein Hardware-basiertes Kryptosystem wird in der vorliegenden Arbeit die Ausnutzung des Leistungsübertragungskoeffizienten in BFO Memristoren vorgeschlagen. Mit Hilfe der unterschiedlichen Oberschwingungen, welche von einem BFO Memristor im ON und OFF Zustand generiert werden, wurde ein Kryptosystem zum Kodieren binärer Daten entwickelt. Ein Test des Hardware-basierten Kryptosystems an Biodaten ergab, dass die kodierten Biodaten keine vorhersagbare Korrelation mehr enthielten. In der vorliegenden Arbeit wurden darüberhinaus BFO-basierte künstliche Synapsen mit einer Aktionspotentials-Intervall abhängigen Plastizität (STDP) für Einzelpulse entwickelt. Diese Einzelpuls-STDP legt den Grundstein für energieffiziente und schnelle neuromorphe Netzwerke mit künstlichen Synapsen. Im Vergleich zu biologischen Synapsen mit einer 60-80-Puls-STDP und einem Lernfenster auf der ms-Zeitskale, konnte das Lernfenster von BFO-basierten künstlichen Synapsen von 25 ms auf 125 μs reduziert werden. Solch ein schnelles Lernen ermöglicht auch die extreme Reduzierung des Leistungsverbrauchs in neuromorphen Netzwerken.

Ultra low power wireless sensors and sensor systems are of increasing interest in a variety of applications ranging from structural health monitoring to industrial process control. Electrochemical batteries have thus far remained the primary energy sources for such systems despite the finite associated lifetimes imposed due to limitations associated with energy density. However, certain applications (such as implantable biomedical electronic devices and tire pressure sensors) require the operation of sensors and sensor systems over significant periods of time, where battery usage may be impractical and add cost due to the requirement for periodic re-charging and/or replacement. In order to address this challenge and extend the operational lifetime of wireless sensors, there has been an emerging research interest on harvesting ambient vibration energy. Vibration energy harvesting is a technology that generates electrical energy from ambient kinetic energy. Despite numerous research publications in this field over the past decade, low power density and variable ambient conditions remain as the key limitations of vibration energy harvesting. In terms of the piezoelectric transducers, the open-circuit voltage is usually low, which limits its power while extracted by a full-bridge rectifier. In terms of the interface circuits, most reported circuits are limited by the power efficiency, suitability to real-world vibration conditions and system volume due to large off-chip components required. The research reported in this thesis is focused on increasing power output of piezoelectric transducers and power extraction efficiency of interface circuits. There are five main chapters describing two new design topologies of piezoelectric transducers and three novel active interface circuits implemented with CMOS technology. In order to improve the power output of a piezoelectric transducer, a series connection configuration scheme is proposed, which splits the electrode of a harvester into multiple equal regions connected in series to inherently increase the open-circuit voltage generated by the harvester. This topology passively increases the rectified power while using a full-bridge rectifier. While most of piezoelectric transducers are designed with piezoelectric layers fully covered by electrodes, this thesis proposes a new electrode design topology, which maximizes the raw AC output power of a piezoelectric harvester by finding an optimal electrode coverage. In order to extract power from a piezoelectric harvester, three active interface circuits are proposed in this thesis. The first one improves the conventional SSHI (synchronized switch harvesting on inductor) by employing a startup circuitry to enable the system to start operating under much lower vibration excitation levels. The second one dynamically configures the connection of the two regions of a piezoelectric transducer to increase the operational range and output power under a variety of excitation levels. The third one is a novel SSH architecture which employs capacitors instead of inductors to perform synchronous voltage flip. This new architecture is named as SSHC (synchronized switch harvesting on capacitors) to distinguish from SSHI rectifiers and indicate its inductorless architecture.

The size reduction of transistors has been the main reason for a successful development of semiconductor integrated circuits over the last decades. Because of the physically limited downscaling of transistors, alternative technologies namely the information processing and nonvolatile resistive switches (also termed memristors) have come into focus. Memristors reveal a fast switching speed, long retention time, and stable endurance. Nonvolatile analog bipolar resistive switching with a considerable large On/Off ratio is reported in BiFeO3 (BFO)-based resistive switches. So far resistive switches are mainly applied in memory applications or logic operations. Given the excellent properties of BFO based memristors, the further exploration of functionalities for memristive devices is required. A new approach for hardware based cryptographic system was developed within the framework of this dissertation. By studying the power conversion efficiencies on BFO memristor at various harmonics, it has been shown that two sets of clearly distinguishable power ratios are achievable when the BFO memristor is set into high or into low resistance state. Thus, a BFO-based binary encoding system can be established. As an example the unrecoverable seizure information from encoded medical data suggests the proper functioning of the proposed encryption system. Aside from cryptographic functionality, the single pairing spike timing dependent plasticity (STDP) in BFO-based artificial synapses is demonstrated, which can be considered as the cornerstone for energy-efficient and fast hardware-based neuromorphic networks. In comparison to the biological driven realistic way, only single one pairing of pre- and postsynaptic spikes is applied to the BFO-based artificial synapse instead of 60-80 pairings. Thus, the learning time constant of STDP function can be reduced from 25 ms to 125 us. / In den letzten Jahrzehnten war die Größenreduktion von Transistoren einer der Hauptgründe für die Leistungssteigerung von integrierten Halbleiterschaltungen. Aufgrund des physikalisch beschränkten Skalierungspotentials, werden alternative Technologien für Halbleiterschaltungen entwickelt. Dazu zählen neuartige Widerstandsschalter, sogenannte Memristoren, welche wegen ihrer schnellen Schaltgeschwindigkeit, langen Speicherzeit und stabilen Haltbarkeit in den Fokus der Forschung gerückt sind. Das nichtflüchtige analoge bipolare Schalten des Widerstandwertes mit einem On/Off Verhältnis größer als 100 wurde in BiFeO 3 (BFO)-basierten Widerstands-schaltern beobachtet. Bisher wurden Widerstandsschalter hauptsächlich als Speicher oder in rekonfigurierbaren Logikschaltungen verwendet. Aufgrund der ausgezeichneten Eigenschaften von BFO-basierten Memristoren, ist die Untersuchung weiterer neuer Funktionalitäten vielversprechend. Als neuer Ansatz für ein Hardware-basiertes Kryptosystem wird in der vorliegenden Arbeit die Ausnutzung des Leistungsübertragungskoeffizienten in BFO Memristoren vorgeschlagen. Mit Hilfe der unterschiedlichen Oberschwingungen, welche von einem BFO Memristor im ON und OFF Zustand generiert werden, wurde ein Kryptosystem zum Kodieren binärer Daten entwickelt. Ein Test des Hardware-basierten Kryptosystems an Biodaten ergab, dass die kodierten Biodaten keine vorhersagbare Korrelation mehr enthielten. In der vorliegenden Arbeit wurden darüberhinaus BFO-basierte künstliche Synapsen mit einer Aktionspotentials-Intervall abhängigen Plastizität (STDP) für Einzelpulse entwickelt. Diese Einzelpuls-STDP legt den Grundstein für energieffiziente und schnelle neuromorphe Netzwerke mit künstlichen Synapsen. Im Vergleich zu biologischen Synapsen mit einer 60-80-Puls-STDP und einem Lernfenster auf der ms-Zeitskale, konnte das Lernfenster von BFO-basierten künstlichen Synapsen von 25 ms auf 125 μs reduziert werden. Solch ein schnelles Lernen ermöglicht auch die extreme Reduzierung des Leistungsverbrauchs in neuromorphen Netzwerken.