No description available.

This thesis presents an active clamp forward converter for use in the Energy Harvesting From Exercise Machines project. Ideally, this converter will find use as the centerpiece in a process that links elliptical trainers to the California grid. This active clamp forward converter boasts a 14V-60V input voltage range and 150W power rating, which closely match the output voltage and power levels from the elliptical trainer. The isolated topology outputs 51V, higher than previous, non-isolated attempts, which allows the elliptical trainers to interact with a central grid-tied inverter instead of many small ones. The final converter operated at greater than 86% efficiency over most of the elliptical trainer’s input range, and produced very little noise, making it a solid choice for this implementation.

This thesis entails the design and fabrication of a smartphone charger that is powered by a bicycle dynamo hub. In addition to the design and validation of the charger prototype, this thesis involves the testing and characterization of the dynamo hub power source, the design and construction of specialized test equipment, and the design and prototyping of a handlebar-mounted case for the smartphone and charging electronics. With the intention of making the device a commercial product, price, aesthetics, and marketability are of importance to the design. An appropriate description of the charger circuit is a microcontroller-based energy management system, tailored to meet strict power demands of current smartphones. The system incorporates a switched-mode power supply, lithium polymer battery, microcontroller, and specialized protection circuitry. Prototype testing confirms that the circuit meets the charging requirements of the smartphone at bicycle speeds ranging from 7 miles per hour to as high as 55 miles per hour.

Energy Harvesting, also known as power harvesting or ambient power, is the process of obtaining small amounts of power from secondary sources, such as vibrations, light, temperature variations and even radio-frequency emissions. These systems have been uncommon in personal and wearable electronics in the past, however they are slowly gaining traction. With the increasing sophistication of prosthetic limbs and implants, devices that in some cases require a consistent and reliable power source, the potential field of application for energy harvesting grows wider. This thesis project evaluates whether energy harvesting methods could be implemented in future prosthetic limb designs without significantly affecting weight, user comfort, complexity of design etc., and whether the gains of such an implementation would be worth the effort and cost put into it. For reference the project used the RHEO KNEE® by Össur Hf., a microcontroller controlled prosthetic knee, as a device that such a system could be integrated with. Energy harvesting is still an emerging field and is a long time away from being a viable primary power source for most electronic devices. However, it still might have potential as a supplementary source for extending charge cycles or making smaller (and therefore more lightweight) power cells viable. This master’s thesis project was broad in scope and included 3D-design; mechanical, electrical and embedded software design; and setting up a miniature kinetic power generator as well as a photovoltaic harvesting system. No amputees were available for testing the designs so the system was tested with a 3D-printed model that was moved by hand to simulate the generation process. Due to some incorrect inital assumptions, the final electronic design was not optimal for this kind of system. However, a kinetic generator that harvested power from a modeled heel striking the ground 50 times a minute produced about 23mW of power. 53cm2 of photovoltaic panels produced 42μW of power in an ambient light setting. For comparison, a low-power microcontroller needed about 119μW of power on average to do some simple processing and send Bluetooth transmissions once every two seconds. / Energiinsamling (e. Energy Harvesting), är processen för att erhålla små mängder kraft från sekundära källor, såsom vibrationer, ljus, temperaturvariationer och utstrålning i radiofrekvens. Dessa system har varit ovanliga i hemelektronik och bärbar teknik, men de vinner sakta dragkraft. Med den ökande förfining av proteser och implantat, som i vissa fall kräver en jämn och pålitlig strömkälla, växer det potentiella användningsområdet för energiinsamling. Detta examensarbete utvärderar huruvida energiinsamlingsmetoder skulle kunna implementeras i framtida proteskonstruktioner utan att nämnvärt påverka vikt, användarkomfort, komplexitet i design etc., och om vinsterna med en sådan implementering skulle vara värd ansträngningen och kostnaden. Som exempel använde detta projekt en datoriserad knäprotes av Össur HF, RHEO KNEE®, som exempel på ett system som energiinsamling skulle kunna integreras med. Energiinsamling är fortfarande ett växande forskningsområde och är långt ifrån att en strömkälla för det mesta elektronik.. Det kan ändå ha potential som en kompletterande strömkälla som kan förlänga laddningscykler eller göra mindre (och därför lättare) batterier möjliga. Detta examensarbete var brett i omfattning och inkluderade 3D-design; mekanisk-, elektrisk- och mjukvara-design; och inrättning av en kinetisk kraftgenerator i miniatyr samt ett ljusdrivet energiinsamlingssystem. Inga amputerade var tillgängliga för att testa designen, därför så testades systemet med en 3D-printad modell som rördes för hand för att simulera strömförsörjelseprocessen. På grund av några felaktiga initiala antaganden var den slutliga elektroniska designen inte optimal för denna typ av system. Ändå lyckades en kinetisk generator som använde energiinsamlingsprinciper producera cirka 23mW ström genom en simulerad häl som träffade marken cirka 50 gånger i minuten. 53cm2 solcellspaneler producerade 42μW energi i en ljussatt miljö. Som jämförelse behövde en strömsnål styrkrets i genomsnitt cirka 119μW effekt för att genomföra enkla programprocesser och skicka Bluetooth-överföringar en gång varannan sekund. / Hliðarorkuöflun (e. energy harvesting), sem einnig bætti kalla umhverfisöflun, er ferlið við að fá lítið magn af orku frá óbeinum aflgjafa, svo sem frá hristingi, ljósi, hitabreytingum og jafnvel útvarpsbylgjum. Þessi kerfi hafa verið sjaldgæf í raftækjum hingað til, þó þau eru hægt og rólega að fá hlutdeild. Með nýrri og fágaðri gervilimum og ígræðslum, tæki sem í sumum tilvikum þurfa samfellda og áreiðanlega orkjugjafa, víkkar mögulegt notkunarsvið hliðarorkuöflunar. Þetta lokaverkefni metur hvort aðferðir við hliðarorkuöflun gætu verið notaðar í hönnun gervilima framtíðarinnar án þess að hafa neikvæð áhrif á þyngd, þægilegheit, flóknun hönnunar o.þ.h., og hvort hagur sé í samræmi við framlag og kostnað. Þetta verkefni notar RHEO KNEE® frá Össuri Hf. sem viðmið, sem er gervihné stjórnað af örtölvu. Viðmiðinu er ætlað að sýna notagildi kerfisins. Hliðarorkuöflun er ennþá svið í þróun og er nokkuð í að það geti orðið frumorkugjafi fyrir flest raftæki. Hins vegar þá gæti það enn átt möguleika á að vera aukaorkugjafi til að auka tímalengd hverrar hleðslu eða gera minni og léttari rafhlöður raunhæfari. Þetta meistaraverkefni var viðamikið að því leiti að það fól í sér þrívíddarhönnun; vél-, raf- og hugbúnaðarhönnun; og uppsetningu á hreyfirafal ásamt ljósorkuöflunarkerfi. Engir einstaklingar sem misst hafa fót voru til staðar til að prófa hannanir þessa verkefnis. Þ.a.l. voru þær prófaðar með þrívíddarprentuðum líkönum sem hreyfð voru með handafli til að líkja eftir orkuframleiðsluferlinu. Vegna rangrar upprunalegrar forsendu þá var endanleg rafhönnunin ekki ákjósanleg fyrir slíkt kerfi. Hreyfirafall tengdur við gervihæl sem sló jörðu 50 sinnum á mínútu framleiddi þó 23mW af orku. 53cm2 af ljósorkueiningum framleiddu 42μW af afli í meðal herbergisbirtu. Til samanburðar þá eyðir skilvirk örtölva u.þ.b. 119μW af afli í einfaldri tölvuvinnslu ásamt því að senda Bluetooth sendingu á tveggja sekúnda fresti.

A typical model for real-time status update systems consists of a transmitter node that generates real-time status updates about some physical process(es) of interest and sends them through a communication network to a destination node. Such a model can be used to analyze the performance of a plethora of emerging Internet of Things (IoT)-enabled real-time applications including healthcare, factory automation, autonomous vehicles, and smart homes, to name a few. The performance of these applications highly depends upon the freshness of the information status at the destination node about its monitored physical process(es). Because of that, the main design objective of such real-time status update systems is to ensure timely delivery of status updates from the transmitter node to the destination node. To measure the freshness of information at the destination node, the Age of Information (AoI) has been introduced as a performance metric that accounts for the generation time of each status update (which was ignored by conventional performance metrics, specifically throughput and delay). Since then, there have been two main research directions in the AoI research area. The first direction aimed to analyze/characterize AoI in different queueing-theoretic models/disciplines, and the second direction was focused on the optimization of AoI in different communication systems that deal with time-sensitive information. However, the prior queueing-theoretic analyses of AoI have mostly been limited to the characterization of the average AoI and the prior studies developing AoI/age-aware scheduling/transmission policies have mostly ignored the energy constraints at the transmitter node(s). Motivated by these limitations, this dissertation develops new queueing-theoretic methods that allow the characterization of the distribution of AoI in several classes of status updating systems as well as novel AoI-aware scheduling policies accounting for the energy constraints at the transmitter nodes (for several settings of communication networks) in the process of decision-making using tools from optimization theory and reinforcement learning. The first part of this dissertation develops a stochastic hybrid system (SHS)-based general framework to facilitate the analysis of characterizing the distribution of AoI in several classes of real-time status updating systems. First, we study a general setting of status updating systems, where a set of source nodes provide status updates about some physical process(es) to a set of monitors. For this setting, the continuous state of the system is formed by the AoI/age processes at different monitors, the discrete state of the system is modeled using a finite-state continuous-time Markov chain, and the coupled evolution of the continuous and discrete states of the system is described by a piecewise linear SHS with linear reset maps. Using the notion of tensors, we derive a system of linear equations for the characterization of the joint moment generating function (MGF) of an arbitrary set of age processes in the network. Afterwards, we study a general setting of gossip networks in which a source node forwards its measurements (in the form of status updates) about some observed physical process to a set of monitoring nodes according to independent Poisson processes. Furthermore, each monitoring node sends status updates about its information status (about the process observed by the source) to the other monitoring nodes according to independent Poisson processes. For this setup, we develop SHS-based methods that allow the characterization of higher-order marginal/joint moments of the age processes in the network. Finally, our SHS-based framework is applied to derive the stationary marginal and joint MGFs for several queueing disciplines and gossip network topologies, using which we derive closed-form expressions for marginal/joint high-order statistics of age processes, such as the variance of each age process and the correlation coefficients between all possible pairwise combinations of age processes. In the second part of this dissertation, our analysis is focused on understanding the distributional properties of AoI in status updating systems powered by energy harvesting (EH). In particular, we consider a multi-source status updating system in which an EH-powered transmitter node has multiple sources generating status updates about several physical processes. The status updates are then sent to a destination node where the freshness of each status update is measured in terms of AoI. The status updates of each source and harvested energy packets are assumed to arrive at the transmitter according to independent Poisson processes, and the service time of each status update is assumed to be exponentially distributed. For this setup, we derive closed-form expressions of MGF of AoI under several queueing disciplines at the transmitter, including non-preemptive and source-agnostic/source-aware preemptive in service strategies. The generality of our analysis is demonstrated by recovering several existing results as special cases. A key insight from our characterization of the distributional properties of AoI is that it is crucial to incorporate the higher moments of AoI in the implementation/optimization of status updating systems rather than just relying on its average (as has been mostly done in the existing literature on AoI). In the third and final part of this dissertation, we employ AoI as a performance metric for several settings of communication networks, and develop novel AoI-aware scheduling policies using tools from optimization theory and reinforcement learning. First, we investigate the role of an unmanned aerial vehicle (UAV) as a mobile relay to minimize the average peak AoI for a source-destination pair. For this setup, we formulate an optimization problem to jointly optimize the UAV's flight trajectory as well as energy and service time allocations for packet transmissions. This optimization problem is subject to the UAV's mobility constraints and the total available energy constraints at the source node and UAV. In order to solve this non-convex problem, we propose an efficient iterative algorithm and establish its convergence analytically. A key insight obtained from our results is that the optimal design of the UAV's flight trajectory achieves significant performance gains especially when the available energy at the source node and UAV is limited and/or when the size of the update packet is large. Afterwards, we study a generic system setup for an IoT network in which radio frequency (RF)-powered IoT devices are sensing different physical processes and need to transmit their sensed data to a destination node. For this generic system setup, we develop a novel reinforcement learning-based framework that characterizes the optimal sampling policy for IoT devices with the objective of minimizing the long-term weighted sum of average AoI values in the network. Our analytical results characterize the structural properties of the age-optimal policy, and demonstrate that it has a threshold-based structure with respect to the AoI values for different processes. They further demonstrate that the structures of the age-optimal and throughput-optimal policies are different. Finally, we analytically characterize the structural properties of the AoI-optimal joint sampling and updating policy for wireless powered communication networks while accounting for the costs of generating status updates in the process of decision-making. Our results demonstrate that the AoI-optimal joint sampling and updating policy has a threshold-based structure with respect to different system state variables. / Doctor of Philosophy / A typical model for real-time status update systems consists of a transmitter node that generates real-time status updates about some physical process(es) of interest and sends them through a communication network to a destination node. Such a model can be used to analyze the performance of a plethora of emerging Internet of Things (IoT)-enabled real-time applications including healthcare, factory automation, autonomous vehicles, and smart homes, to name a few. The performance of these applications highly depends upon the freshness of the information status at the destination node about its monitored physical process(es). Because of that, the main design objective of such real-time status update systems is to ensure timely delivery of status updates from the transmitter node to the destination node. To measure the freshness of information at the destination node, the Age of Information (AoI) has been introduced as a performance metric that accounts for the generation time of each status update (which was ignored by conventional performance metrics, specifically throughput and delay). Since then, there have been two main research directions in the AoI research area. The first direction aimed to analyze/characterize AoI in different queueing-theoretic models/disciplines, and the second direction was focused on the optimization of AoI in different communication systems that deal with time-sensitive information. However, the prior queueing-theoretic analyses of AoI have mostly been limited to the characterization of the average AoI and the prior studies developing AoI/age-aware scheduling/transmission policies have mostly ignored the energy constraints at the transmitter node(s). Motivated by these limitations, this dissertation first develops new queueing-theoretic methods that allow the characterization of the distribution of AoI in several classes of status updating systems. Afterwards, using tools from optimization theory and reinforcement learning, novel AoI-aware scheduling policies are developed while accounting for the energy constraints at the transmitter nodes for several settings of communication networks, including unmanned aerial vehicles (UAVs)-assisted and radio frequency (RF)-powered communication networks, in the process of decision-making. In the first part of this dissertation, a stochastic hybrid system (SHS)-based general framework is first developed to facilitate the analysis of characterizing the distribution of AoI in several classes of real-time status updating systems. Afterwards, this framework is applied to derive the stationary marginal and joint moment generating functions (MGFs) for several queueing disciplines and gossip network topologies, using which we derive closed-form expressions for marginal/joint high-order statistics of age processes, such as the variance of each age process and the correlation coefficients between all possible pairwise combinations of age processes. In the second part of this dissertation, our analysis is focused on understanding the distributional properties of AoI in status updating systems powered by energy harvesting (EH). In particular, we consider a multi-source status updating system in which an EH-powered transmitter node has multiple sources generating status updates about several physical processes. The status updates are then sent to a destination node where the freshness of each status update is measured in terms of AoI. For this setup, we derive closed-form expressions of MGF of AoI under several queueing disciplines at the transmitter. The generality of our analysis is demonstrated by recovering several existing results as special cases. A key insight from our characterization of the distributional properties of AoI is that it is crucial to incorporate the higher moments of AoI in the implementation/optimization of status updating systems rather than just relying on its average (as has been mostly done in the existing literature on AoI). In the third and final part of this dissertation, we employ AoI as a performance metric for several settings of communication networks, and develop novel AoI-aware scheduling policies using tools from optimization theory and reinforcement learning. First, we investigate the role of a UAV as a mobile relay to minimize the average peak AoI for a source-destination pair. For this setup, we formulate an optimization problem to jointly optimize the UAV's flight trajectory as well as energy and service time allocations for packet transmissions. This optimization problem is subject to the UAV's mobility constraints and the total available energy constraints at the source node and UAV. A key insight obtained from our results is that the optimal design of the UAV's flight trajectory achieves significant performance gains especially when the available energy at the source node and UAV is limited and/or when the size of the update packet is large. Afterwards, we study a generic system setup for an IoT network in which RF-powered IoT devices are sensing different physical processes and need to transmit their sensed data to a destination node. For this generic system setup, we develop a novel reinforcement learning-based framework that characterizes the optimal sampling policy for IoT devices with the objective of minimizing the long-term weighted sum of average AoI values in the network. Our analytical results characterize the structural properties of the age-optimal policy, and demonstrate that it has a threshold-based structure with respect to the AoI values for different processes. They further demonstrate that the structures of the age-optimal and throughput-optimal policies are different. Finally, we analytically characterize the structural properties of the AoI-optimal joint sampling and updating policy for wireless powered communication networks while accounting for the costs of generating status updates in the process of decision-making. Our results demonstrate that the AoI-optimal joint sampling and updating policy has a threshold-based structure with respect to different system state variables.

Although wireless sensor networks have been successfully used for environmental monitoring, one of the major challenges that this technology has been facing is supplying continuous and reliable electrical power during long-term field deployment. Batteries require repetitive visits to the deployment site to replace them once discharged; admittedly, they can be recharged from solar panels, but this only works in open areas where solar radiation is unrestricted. This dissertation introduces a novel approach to design and implement a reliable efficient solar energy harvester to continuously, and autonomously, provide power to wireless sensor nodes for long-term applications. The system uses supercapacitors charged by a solar panel and is designed to reduce power consumption to very low levels. Field tests were conducted for more than a year of continuous operation and under a variety of conditions, including areas under dense foliage. The resulting long-term field data demonstrates the feasibility and sustainability of the harvester system for challenging applications. In addition, we analyzed solar radiation data and supercapacitor charging behavior and showed that the harvester system can operate battery free, running on the power provided by supercapacitors. A battery is included only for backup in case the supercapacitor storage fails. The proposed approach provides continuous power supply to the system thereby significantly minimizing data loss by power failure and the frequency of visits to the deployment sites.

The search for renewable energy resources and ways to harvest them has become a global mainstream topic among researchers nowadays, with solar cells and thermoelectric generators among the energy harvesting technologies currently being researched in vast. CZTS (Cu2ZnSnS4), a p-type semiconducting material initially researched to replace copper indium gallium selenide (CIGS) as the light absorbing layer in thin film solar cells, was studied in this doctoral work for alternative uses in energy harvesting. This work aims to systemically investigate the prospects of CZTS to be used as hole transport layers and thermoelectric generators. CZTS thin film was successfully fabricated using a versatile approach involving hot-injection synthesis of CZTS nanoparticles ink followed by spin coating and thermal treatment. Results obtained revealed the possibility to fine control CZTS thin film fabrication based on ink concentration and spin. Besides that, thermal treatment temperature was found to affect the film’s overall properties, where an increase in thermal treatment temperature improved the degree of crystallinity and electrical properties. In addition, a phase change going from less stable cubic and wurtzite structures to a more stable tetragonal structure was also observed. Furthermore, CZTS was found to be a good candidate to replace the commonly used organic hole transport layer in perovskite solar cells, with potentials in improving performance and stability. In addition, CZTS also possessed good transport properties to be a potential p-type material in a thermoelectric generator, with the preliminary performance of fabricated CZTS/AZO thermoelectric generator showing a maximum power output of ~350 nW at ~170 KΔT. These findings provide new perspectives for CZTS in energy harvesting applications, despite the struggle in its development as the absorber layer in thin film solar cells. Besides providing a deeper understanding of CZTS and its vast possibilities in energy harvesting applications, promising future research stemming from this work is also limitless, reinventing ways in material studies, in search of alternative applications which may be of benefit.

No description available.

Dedicated sensors are widely used throughout many industries to monitor everyday operations, maintain safety, and report performance characteristics. In order to adopt a more sustainable solution, much research is being applied to self-powered sensing, implementing solutions which harvest wasted ambient energy sources to power these dedicated sensors. The adoption of not only wireless sensor nodes, but also self-powered capabilities in the nuclear energy process is critical as it can address issues in the overall safety and longevity of nuclear power. The removal of wires for data and power transmission can greatly reduce the cost of both installation and upkeep of power plants, while self-powered capabilities can further reduce effort and money spent in replacing batteries, and importantly may enable sensors to work even in losses to power across the plant, increasing plant safety. This thesis outlines three harvesting opportunities in the nuclear energy process from: thermal, vibration, and radiation sources in the main structure of the power plant, and from thermal and radiation energy from spent fuel in dry cask storage. Thermal energy harvesters for the primary and secondary coolant loops are outlined, and experimental analysis done on their longevity in high-radiation environments is discussed. A vibrational energy harvester for large rotating plant machine vibration is designed, prototyped, and tested, and a model is produced to describe its motion and energy output. Finally, an introduction to the design of a gamma radiation and thermal energy harvester for spent nuclear fuel canisters is discussed, and further research steps are suggested. / Master of Science / In this work multiple energy harvesters are investigated aimed at collecting wasted ambient energy to locally power sensor nodes in nuclear power plants, and in spent nuclear fuel canisters. Locally self-powered, wireless sensors can increase safety and reliability throughout the nuclear process. To address this a thermal energy harvester is tested in a radiation rich environment, and its performance before and after irradiation is analyzed. A vibrational energy harvester designed for use on large rotating machinery is discussed, manufactured, and tested, and a mathematical model describing it is produced. Finally, an introduction to harvesting radiation and heat given off from spent nuclear fuel in dry cask canister storage is investigated. Power capabilities for each design are considered, and the impact of such energy harvesting for wireless sensor nodes on the longevity, safety, and reliability of nuclear power plants is discussed.

[pt] Heteroestruturas sensíveis à luz solar possuem grande potencial em diferentes aplicações direcionadas a um futuro limpo e sustentável, como a fotoprodução de hidrogênio (H2) e a remediação ambiental. No contexto da fotocatálise, o dióxido de titânio (TiO2) desempenha um papel crucial devido à sua ampla gama de aplicações, excelente estabilidade química, baixa toxicidade e custo relativamente baixo. No entanto, o TiO2 puro possui algumas desvantagens, como uma alta taxa de recombinação e baixa sensibilidade à luz solar, o que limita sua eficiência em aplicações fotocatalíticas. Portanto, o desenvolvimento contínuo de novos materiais com o objetivo de superar essas desvantagens é obrigatório. Entre as abordagens reportadas para superar as deficiências do TiO2 puro está a formação de heterojunções com outros semicondutores, melhorando a separação de cargas e, portanto, a eficiência fotocatalítica. Óxidos de níquel e óxidos de cobre são relatados como alternativas promissoras para a formação de heterojunções com TiO2, melhorando a transferência de carga e aumentando a absorção de luz no espectro visível do TiO2 puro. Esta tese apresenta diferentes estudos voltados para a síntese e caracterização de novos nanomateriais heteroestruturados eficientes para geração fotocatalítica de hidrogênio e degradação de poluentes perigosos. No primeiro estudo, foi relatada uma heterojunção p-n de NiO/TiO2 obtida via mecanoquímica, que apresentou uma taxa elevada de fotoprodução pelo sol de H2 em comparação com o TiO2 puro (8.85 mmol h-1 g-1 vs. 0.73 mmol h-1 g-1). Em todos os casos, a adição de NiO suportado em TiO2 reduziu a taxa de recombinação e aumentou a absorção de luz visível. Estudos de TEM, XPS e XAS demonstraram que uma dispersão homogênea e uma configuração de spin favorável dos pequenos aglomerados de NiO suportados em TiO2 foram responsáveis pela eficiência superior exibida pela amostra preparada via mecanoquímica, denominada NiO/P90- BM. Notavelmente, testes de ciclagem, de longo prazo e de envelhecimento mostraram que o fotocatalisador relatado é eficiente após vários ciclos, para uso prolongado e após longos períodos de armazenamento. Além disso, foram realizados estudos combinando EPR e a técnica de captura de spin para aprofundar na produção de superóxido e hidroxila pelas heterojunções de NiO/TiO2. Esses estudos forneceram insights sobre a aplicação potencial das heterojunções de NiO/TiO2 para a degradação fotocatalítica de poluentes gasosos e aquosos. Os resultados de EPR lançaram luz sobre a amostra de NiO/P90-BM como a mais eficiente na fotogeração de ROS, revelando que a síntese mecanoquímica resultou em uma arquitetura mais eficiente para a geração de radicais superóxido e hidroxila. Finalmente, foi relatada uma rota simples de química branda para preparar uma heteroestrutura de nanocubos de óxido cúprico (Cu2O NCs) e TiO2, denominada Cu2O NCs/TiO2, como um adsorvente eficiente para a tetraciclina (TC), que é um antibiótico de amplo espectro. FTIR e TGA foram realizados antes e após o processo de adsorção para demonstrar a adsorção de TC pela heteroestrutura Cu2O NCs/TiO2. Além disso, foram realizados testes com irradiação de luz visível para distinguir entre os processos de remoção por adsorção e fotocatalítica. Além disso, foram realizadas medições de EPR usando captura de spin para investigar a fotoprodução de ROS. Curiosamente, não houve fotoprodução de ROS detectável pela heteroestrutura Cu2O NCs/TiO2, demonstrando que a remoção de TC é exclusivamente devido à adsorção. Estes resultados contribuem para esclarecer uma discrepância na literatura quanto à atividade fotocatalítica dos Cu2O NCs sob luz visível. Coletivamente, esta pesquisa avançou o entendimento dos mecanismos fotocatalíticos e relatou novos nanomateriais heteroestruturados, destacando seu potencial para aplicações sustentáveis em diversos contextos relacionados ao meio ambiente e transição energética. / [en] Solar light-responsive heterostructures hold great potential in different applications toward a clean and sustainable future, such as hydrogen (H2) photoproduction and environmental remediation. In the context of photocatalysis, titanium dioxide (TiO2) plays a crucial role due to its wide range of applications, excellent chemical stability, low toxicity, and relatively low cost. However, neat TiO2 has some shortfalls, such as a high recombination rate and low sensitivity to solar light, which limits its efficiency in photocatalytic applications in general. Therefore, the continuous development of new materials aimed at improving these limitations is mandatory. Among the approaches to overcome the neat TiO2 shortfalls is the formation of heterojunctions with suitable semiconductors, improving charge separation and, therefore, photocatalytic efficiency. Nickel oxides and copper oxides are reported as promising alternatives for forming heterojunctions with TiO2, enhancing the charge transfer and broadening the light absorption in the visible spectrum. This thesis presents different studies aimed at the synthesis and characterization of new efficient heterostructured nanomaterials for photocatalytic hydrogen generation and hazardous pollutants abatement. In the first study, a NiO/TiO2 p-n heterojunction obtained via mechanochemistry was reported, which exhibited an improved solar-driven H2 photoproduction rate compared to neat TiO2 (8.85 mmol h-1g-1vs. 0.73 mmol h-1g-1). In all cases, the addition of NiO supported on TiO2 reduced the recombination rate and enhanced the visible light absorption. TEM, XPS, and XAS studies demonstrated that a homogenous dispersion and a favorable spin configuration of NiO clusters supported on TiO2 were responsible for the superior efficiency exhibited by the sample prepared via mechanochemistry, labeled as NiO/P90-BM. Noticeably, cycling, long-term, and aging tests have shown that the reported photocatalyst is efficient after several cycles, prolonged use, and after long periods of storage. Furthermore, studies combining EPR and the spin trapping technique were carried out to delve into the production of superoxide and hydroxyl by NiO/TiO2 heterojunctions. These studies provided insights into the potential application of the NiO/TiO2 heterojunctions for the photocatalytic degradation of gaseous and aqueous pollutants. The EPR results shed light on the NiO/P90-BM sample as the most efficient in ROS photogeneration, revealing that mechanochemical synthesis resulted in a more efficient architecture for generating superoxide and hydroxyl radicals. Besides, a simple soft chemistry route was reported to prepare a heterostructure of cuprous oxide nanocubes (Cu2O NCs) and TiO2, labeled as Cu2O NCs/TiO2, as an efficient adsorbent for tetracycline (TC), which is a broad-spectrum antibiotic. FTIR and TGA were carried out before and after the adsorption process to demonstrate the adsorption of TC by the Cu2O NCs/TiO2 heterostructure. Additionally, tests with visible light irradiation were performed to distinguish between adsorption and photocatalytic removal processes. In addition, EPR measurements were also carried out using spin trapping to investigate the ROS photoproduction. Interestingly, there was no detectable ROS photoproduction by the Cu2O NCs/TiO2 heterostructure, demonstrating that TC removal is solely due to adsorption. These results contribute to clarifying a discrepancy in the literature regarding the photocatalytic activity of Cu2O NCs under visible light. Collectively, this research has advanced the understanding of photocatalytic mechanisms and reported new heterostructured nanomaterials, while highlighting their potential for sustainable applications in diverse environmental and energy transition related contexts.