2,020 research outputs found
RF Energy Harvesting Techniques for Battery-less Wireless Sensing, Industry 4.0 and Internet of Things: A Review
As the Internet of Things (IoT) continues to expand, the demand for the use of energy-efficient circuits and battery-less devices has grown rapidly. Battery-less operation, zero maintenance and sustainability are the desired features of IoT devices in fifth generation (5G) networks and green Industry 4.0 wireless systems. The integration of energy harvesting systems, IoT devices and 5G networks has the potential impact to digitalize and revolutionize various industries such as Industry 4.0, agriculture, food, and healthcare, by enabling real-time data collection and analysis, mitigating maintenance costs, and improving efficiency. Energy harvesting plays a crucial role in envisioning a low-carbon Net Zero future and holds significant political importance. This survey aims at providing a comprehensive review on various energy harvesting techniques including radio frequency (RF), multi-source hybrid and energy harvesting using additive manufacturing technologies. However, special emphasis is given to RF-based energy harvesting methodologies tailored for battery-free wireless sensing, and powering autonomous low-power electronic circuits and IoT devices. The key design challenges and applications of energy harvesting techniques, as well as the future perspective of System on Chip (SoC) implementation, data digitization in Industry 4.0, next-generation IoT devices, and 5G communications are discussed
IoT Transmission Technologies for Distributed Measurement Systems in Critical Environments
Distributed measurement systems are spread in the most diverse application scenarios, and Internet of Things (IoT) transmission equipment is usually the enabling technologies for such measurement systems that need to feature wireless connectivity to ensure pervasiveness. Because wireless measurement systems have been deployed for the last years even in critical environments, assessing transmission technologies performances in such contexts is fundamental. Indeed, they are the most challenging ones for wireless data transmission due to their intrinsic attenuation capabilities.
Several scenarios in which measurement systems can be deployed are analysed. Firstly, marine contexts are treated by considering above-the-sea wireless links. Such setting can be experienced in whichever application requiring remote monitoring of facilities and assets that are offshore installed. Some instances are offshore sea farming plants, or remote video monitoring systems installed on seamark buoys. Secondly, wireless communications taking place from the underground to the aboveground are covered. This scenario is typical of precision agriculture applications, where the accurate measurement of underground physical parameters is needed to be remotely sent to optimise crops reducing the wastefulness of fundamental resources (e.g., irrigation water). Thirdly, wireless communications occurring from the underwater to the abovewater are addressed. Such situation is inevitable for all those infrastructures monitoring conservation status of underwater species like algae, seaweeds and reef. Then, wireless links happening traversing metal surfaces and structures are tackled. Such context is commonly encountered in asset tracking and monitoring (e.g., containers), or in smart metering applications (e.g., utility meters). Lastly, sundry harsh environments that are typical of industrial monitoring (e.g., vibrating machineries, harsh temperature and humidity rooms, corrosive atmospheres) are tested to validate pervasive measurement infrastructures even in such contexts that are usually experienced in Industrial Internet of Things (IIoT) applications. The performances of wireless measurement systems in such scenarios are tested by sorting out ad-hoc measurement campaigns. Finally, IoT measurement infrastructures respectively deployed in above-the-sea and underground-to-aboveground settings are described to provide real applications in which such facilities can be effectively installed. Nonetheless, the aforementioned application scenarios are only some amid their sundry variety. Indeed, nowadays distributed pervasive measurement systems have to be thought in a broad way, resulting in countless instances: predictive maintenance, smart healthcare, smart cities, industrial monitoring, or smart agriculture, etc.
This Thesis aims at showing distributed measurement systems in critical environments to set up pervasive monitoring infrastructures that are enabled by IoT transmission technologies. At first, they are presented, and then the harsh environments are introduced, along with the relative theoretical analysis modelling path loss in such conditions. It must be underlined that this Thesis aims neither at finding better path loss models with respect to the existing ones, nor at improving them. Indeed, path loss models are exploited as they are, in order to derive estimates of losses to understand the effectiveness of the deployed infrastructure. In fact, some transmission tests in those contexts are described, along with providing examples of these types of applications in the field, showing the measurement infrastructures and the relative critical environments serving as deployment sites. The scientific relevance of this Thesis is evident since, at the moment, the literature lacks a comparative study like this, showing both transmission performances in critical environments, and the deployment of real IoT distributed wireless measurement systems in such contexts
Study for the scientific development of the Sardinia Radio Telescope/SDSA configured for solar observations and radio-science aimed at Space Weather and Fundamental Physics applications
The Sun produces radiation across virtually the entire electromagnetic spectrum, each frequency range helps to better understand a different aspect of our star. In the radio domain, it is an interesting celestial object to study for the richness of physical phenomena that involve not only the astrophysical area of interest, but also plasma, nuclear and fundamental physics. However, even after decades of studies, our star still presents lots of mysteries.
My PhD aims to investigate the Sun environment and its emission mechanism in the radio domain to better understand some of the complex solar phenomena, their connections and find applications in the Space Weather and Fundamental Physics fields. This work is possible thanks to new challenging development of the radio telescopes managed by the Italian National Institute of Astrophysics (INAF) and the Italian Space Agency (ASI) in a joint collaboration. SRT is an ideal instrument for this Thesis project thanks to its double configuration: Sardinia Deep Space Antenna (SDSA)/radio astronomy for radio science experiments and solar imaging. The SDSA is in the implementation phase.
We are inquiring the most stringent observation scientific requirements that would be necessary to prepare the antenna to perform interplanetary spacecraft tracking in radio-science configuration. The radio-astronomy configuration is already operative and has permitted us to monitor the Sun for the last few years in K-band (18-26 GHz). Moreover, the Medicina radio telescope is fully equipped to perform solar observation and has contributed considerably to the solar imaging studies.
Starting 2018, we obtained more than 300 maps of the entire solar disk in the K-band, filling the observational gap in the field of solar imaging at these frequencies. I performed a new calibration procedure adopting the Supernova Remnant Cas A as a flux reference, which provided typical errors <3% for the estimation of the quiet-Sun level components. My work includes a study on the active regions brightness and spectral characterization. The interpretation of the observed emission as thermal bremsstrahlung components combined with gyro-magnetic variable emission paves the way for the use of our system for long-term monitoring of the Sun. We are also starting to explore possible interesting connections between macro-features in our data and explosive Space Weather Phenomena
Resolving particle acceleration and transport in the jets of the microquasar SS 433 with H.E.S.S. and HAWC
The microquasar SS 433 offers a unique laboratory to study the physics of mildly relativistic jets and the associated non-thermal processes. It hosts a compact binary system, from which a pair of counter-propagating jets is observed to emanate. The jets are resolved by observations out to distances of approximately 0.1 pc from the central source, but further out, they remain dark until they abruptly reappear at around 25 pc as bright X-ray sources. These outer jets were recently reported to be sources of TeV gamma-rays by the High Altitude Water Cherenkov (HAWC) observatory. This thesis presents a complete picture of the TeV emission from the jets of SS 433 including new data from the High Energy Stereoscopic System (H.E.S.S.) and the HAWC observatory.
To fully exploit the capabilities of the H.E.S.S. observations, a new approach to background rejection is presented. It is based on the detection of Cherenkov light from muons by large Imaging Atmospheric Cherenkov Telescopes (IACTs), such as the telescope located at the center of the H.E.S.S. array. The application of this technique leads to a factor four reduction in background above several tens of TeV in the
H.E.S.S. stereoscopic analysis.
This thesis presents the detection of the SS 433 outer jets for the first time with an IACT array using H.E.S.S.. The superior angular and energy resolution of H.E.S.S. compared to HAWC allow for a detailed study of the emission from the jets, including a measurement of the physical extension of the emission and of the spectra out to tens of TeV. These observations also reveal the presence of striking energy-
dependent morphology, ruling out a hadronic origin for the bulk of the gamma-ray emission. Photons above 10 TeV are observed only close to the base of the outer jets, implying efficient particle acceleration to very-high energies at that location. Evidence suggests that the acceleration is due to a shock, thus providing a clue to the long-standing question of the reappearance of the jets.
The observed energy-dependent morphology is modeled as a consequence of the particle cooling times and the advection flow of the jet, which constrains the jet dynamics and, in particular, results in an estimate of the velocity of the outer jets at their base. This solves several issues concerning the non-thermal processes occurring in the jets and their dynamics, but also opens up new questions that highlight our incomplete understanding of the SS 433 system.
A joint analysis of the H.E.S.S. and HAWC data would provide insights on the system across the entire range of TeV energies. To make this possible, a tool capable of reading and analyzing the data from both instruments is required. This thesis presents the extension and validation of an existing data format and analysis tool shared among IACTs to the data from particle detector arrays such as the HAWC observatory. This framework is then used to revisit the HAWC observations of the SS 433 region with the inclusion of additional data taken since the first detection was reported. The existence of this framework enables for the first time the joint analysis of the H.E.S.S. and HAWC data, the preliminary results of which are presente
RF Wireless Power and Data Transfer : Experiment-driven Analysis and Waveform Design
The brisk deployment of the fifth generation (5G) mobile technology across the globe has accelerated the adoption of Internet of Things (IoT) networks. While 5G provides the necessary bandwidth and latency to connect the trillions of IoT sensors to the internet, the challenge of powering such a multitude of sensors with a replenishable energy source remains. Far-field radio frequency (RF) wireless power transfer (WPT) is a promising technology to address this issue. Conventionally, the RF WPT concepts have been deemed inadequate to deliver wireless power due to the undeniably huge over-the-air propagation losses. Nonetheless, the radical decline in the energy requirement of simple sensing and computing devices over the last few decades has rekindled the interest in RF WPT as a feasible solution for wireless power delivery to IoT sensors.
The primary goal in any RF WPT system is to maximize the harvested direct current (DC) power from the minuscule incident RF power. As a result, optimizing the receiver power efficiency is pivotal for an RF WPT system. On similar lines, it is essential to minimize the power losses at the transmitter in order to achieve a sustainable and economically viable RF WPT system. In this regard, this thesis explores the system-level study of an RF WPT system using a digital radio transmitter for applications where alternative analog transmit circuits are impractical. A prototype test-bed comprising low-cost software-defined radio (SDR) transmitter and an off-the-shelf RF energy-harvesting (EH) receiver is developed to experimentally analyze the impact of clipping and nonlinear amplification at the digital radio transmitter on digital baseband waveform. The use of an SDR allows leveraging the test-bed for the research on RF simultaneous wireless information and power transfer (SWIPT); the true potential of this technology can be realized by utilizing the RF spectrum to transport data and power together. The experimental results indicate that a digital radio severely distorts high peak-to-average power ratio (PAPR) signals, thereby reducing their average output power and rendering them futile for RF WPT.
On similar lines, another test-bed is developed to assess the impact of different waveforms, input impedance mismatch, incident RF power, and load on the receiver power efficiency of an RF WPT system. The experimental results provide the foundation and notion to develop a novel mathematical model for an RF EH receiver. The parametric model relates the harvested DC power to the power distribution of the envelope signal of the incident waveform, which is characterized by the amplitude, phase and frequency of the baseband waveform. The novel receiver model is independent of the receiver circuit’s matching network, rectifier configuration, number of diodes, load as well as input frequency. The efficacy of the model in accurately predicting the output DC power for any given power-level distribution is verified experimentally.
Since the novel receiver model associates the output DC power to the parameters of the incident waveform, it is further leveraged to design optimal transmit wave-forms for RF WPT and SWIPT. The optimization problem reveals that a constant envelope signal with varying duty cycle is optimal for maximizing the harvested DC power. Consequently, a pulsed RF waveform is optimal for RF WPT, whereas a continuous phase modulated pulsed RF signal is suitable for RF SWIPT. The superior WPT performance of pulsed RF waveforms over multisine signals is demonstrated experimentally. Similarly, the pulsed phase-shift keying (PSK) signals exhibit superior receiver power efficiency than other communication signals. Nonetheless, varying the duty-cycle of pulsed PSK waveform leads to an efficiency—throughput trade-off in RF SWIPT.
Finally, the SDR test-bed is used to evaluate the overall end-to-end power efficiency of different digital baseband waveforms through wireless measurements. The results indicate a 4-PSK modulated signal to be suitable for RF WPT considering the overall power efficiency of the system. The corresponding transmitter, channel and receiver power efficiencies are evaluated as well. The results demonstrate the transmitter power efficiency to be lower than the receiver power efficiency
Lanthanide-doped upconversion nanoparticles (UCNPs) for biomedical applications
This thesis examines the need for new antibacterial materials to treat small colony variants
(SCVs) of Staphylococcus (S.) aureus bacteria and their parental strains. While ZnO-based
nanoparticles (NPs) activated by ultraviolet (UV) and short wavelength visible light have been
researched for their antibacterial properties, the potential benefits of incorporating UCNPs to
allow activation by near-infrared (NIR) light have been overlooked. This study aims to fill this
research gap by comprehensively investigating the synthesis and performance of ZnO-coated
lanthanide-doped upconversion nanoparticle (UCNP) composites activated by NIR light
against S. aureus SCVs and parental strains.
Furthermore, this research addresses the limited understanding of the potential risks associated
with UV emission from UCNPs used as fluorescent probes in super-resolution microscopy
(SRM). Despite extensive research on the usage of UCNPs as fluorescent probes for SRMs,
the potential cytotoxic effects of UV emission from UCNPs have not been thoroughly studied.
To advance cellular imaging techniques and ensure cellular viability, a comprehensive
investigation of UV emission from UCNPs is necessary. This thesis aims to identify and
quantify UV emission by UCNPs used in SRM and develop strategies to minimise UV
emission and mitigate potential cytotoxic effects.
These two main aims are addressed in three results chapters. The first aim, the focus of chapters
2 and 3, focuses on the synthesis UCNP@ZnO composites that can be activated by NIR light
for antimicrobial photodynamic therapy (aPDT) applications against S. aureus SCVs and
parental strains. Chapter 2 reports the synthesis and performance of these composites, showing
these materials to be effective antibacterial therapies against S. aureus SCVs, while chapter 3
improves upon the performance of these composites by careful tuning of the UCNP core and
provides enhancements to the ZnO shell composition to improve reactive oxygen species
generation and add a second mode of action in the form of silver nanoparticles. The second
aim of this research is covered in chapter 4, which reports an investigation into the UV emission
from UCNPs used as fluorescent probes in SRM. The work posits the need to understand the
UV emission properties of these UCNPs as knowledge of these and the potential for cytotoxic
effects are crucial for optimizing cellular imaging experiments and ensuring accurate and
reliable results. Chapter 4 identifies design features and compositions that can limit UV
emission, thereby minimizing the risk of phototoxicity and advancing the field of cellular
imaging.
Overall, the findings from this research have the potential to contribute to the development of
safer and more effective targeted antibacterial therapies and enhance the understanding of UV
emissions in cellular imaging techniques.Thesis (Ph.D.) -- University of Adelaide, School of Chemical Engineering, 202
Pulsed Free Space Photonic Vector Network Analyzers
Terahertz (THz) radiation (0.1–10 THz) has demonstrated great significance in a wide range of interdisciplinary applications due to its unique properties such as the capacity to penetrate optically opaque materials without ionizing effect, superior spatial resolution as compared to the microwave domain for imaging or ability to identify a vast array of molecules using THz fingerprinting. Advancements in generation and detection techniques, as well as the necessities of application-driven research and industry, have created a substantial demand for THz-range
devices and components. However, progress in the development of THz components is hampered by a lack of efficient and affordable characterization systems, resulting in limited development in THz science and technology.
Vector Network Analyzers (VNAs) are highly sophisticated well-established characterization instruments in the microwave bands, which are now employed in the lower end of the THz spectrum (up to 1.5 THz) using frequency extender modules. These modules are extremely expensive, and due to the implementation of hollow metallic waveguides for their configuration, they are narrowband, requiring at least six modules to achieve a frequency coverage of 0.2–1.5 THz. Moreover, they are susceptible to problems like material losses, manufacturing and alignment tolerances etc., making them less than ideal for fast, broadband investigation.
The main objective of this thesis is to design a robust but cost-effective characterization system based on a photonic method that can characterize THz components up to several THz in a single configuration. To achieve this, we design architectures for the Photonic Vector Network Analyzer (PVNA) concept, incorporating ErAs:In(Al)GaAs-based photoconductive sources and ErAs:InGaAs-based photoconductive receivers, driven with a femtosecond pulsed laser operating at 1550 nm. The broadband photonic devices replace narrowband electronic ones in order to record the Scattering (S)-parameters in a free space configuration. Corresponding calibration and data evaluation methods are also developed. Then the PVNAs are configured, and their capabilities are validated by characterizing various THz components, including a THz isolator, a
distributed Bragg Reflector, a Split-Ring Resonator array and a Crossed-Dipole Resonator (CDR) array, in terms of their S-parameters. The PVNAs are also implemented to determine the complex refractive index or dielectric permittivity and physical thickness of several materials in the THz range. Finally, we develop an ErAs:In(Al)GaAs-based THz transceiver and implement it in a PVNA configuration, resulting in a more compact setup that is useful for industrial applications. The feasibility of such systems is also verified by characterizing several THz components.
The configured systems achieve a bandwidth of more than 2.5 THz, exceeding the maximum attainable frequency of the commercial Electronic Vector Network Analyzer (EVNA) extender modules. For the 1.1-1.5 THz band, the dynamic range of 47-35 dB (Equivalent Noise Bandwidth (ENBW) = 9.196 Hz) achieved with the PVNA is comparable to the dynamic range of 45-25 dB (ENBW = 10 Hz) of the EVNA. Both amplitude and phase of the S-parameters, determined by the configured PVNAs, are compared with simulations or theoretical models and showed excellent agreement. The PVNA could discern multi-peak and narrow resonance characteristics despite its lower spectral resolution (∼3-7 GHz) compared to the EVNA. By accurately determining the S-parameters of multiple THz components, the transceiver-based PVNA also demonstrated its exceptional competence.
With huge bandwidth and simpler calibration techniques, the PVNA provides a potential solution to bridge the existing technological gap in THz-range characterization systems and offers a solid platform for THz component development, paving the way for more widespread application of THz technologies in research and industry
Beam scanning by liquid-crystal biasing in a modified SIW structure
A fixed-frequency beam-scanning 1D antenna based on Liquid Crystals (LCs) is designed for application in 2D scanning with lateral alignment. The 2D array environment imposes full decoupling of adjacent 1D antennas, which often conflicts with the LC requirement of DC biasing: the proposed design accommodates both. The LC medium is placed inside a Substrate Integrated Waveguide (SIW) modified to work as a Groove Gap Waveguide, with radiating slots etched on the upper broad wall, that radiates as a Leaky-Wave Antenna (LWA). This allows effective application of the DC bias voltage needed for tuning the LCs. At the same time, the RF field remains laterally confined, enabling the possibility to lay several antennas in parallel and achieve 2D beam scanning. The design is validated by simulation employing the actual properties of a commercial LC medium
Synthetic Aperture Radar (SAR) Meets Deep Learning
This reprint focuses on the application of the combination of synthetic aperture radars and depth learning technology. It aims to further promote the development of SAR image intelligent interpretation technology. A synthetic aperture radar (SAR) is an important active microwave imaging sensor, whose all-day and all-weather working capacity give it an important place in the remote sensing community. Since the United States launched the first SAR satellite, SAR has received much attention in the remote sensing community, e.g., in geological exploration, topographic mapping, disaster forecast, and traffic monitoring. It is valuable and meaningful, therefore, to study SAR-based remote sensing applications. In recent years, deep learning represented by convolution neural networks has promoted significant progress in the computer vision community, e.g., in face recognition, the driverless field and Internet of things (IoT). Deep learning can enable computational models with multiple processing layers to learn data representations with multiple-level abstractions. This can greatly improve the performance of various applications. This reprint provides a platform for researchers to handle the above significant challenges and present their innovative and cutting-edge research results when applying deep learning to SAR in various manuscript types, e.g., articles, letters, reviews and technical reports
Historical Burdens on Physics
When learning physics, one follows a track very similar to the historical path of the evolution of this science: one takes detours, overcomes superfluous obstacles and repeats mistakes, one learns inappropriate concepts and uses outdated methods. In the book, more than 200 articles present and analyze such obsolete concepts methods. All articles have the same structure: 1. subject, 2. deficiencies, 3. origin, 4. disposal. The articles had originally appeared as columns in various magazines. Accordingly, we had tried to write them in an easily understandable way
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