SNO Based Optimization for Shaped Beam Reflectarray Antennas

The design of a shaped beam reflectarray is a challenging issues. The problem can be hardly addressed by deterministic techniques or standard optimization due to the elevated number of design variables and its non-convex nature while can be much easily solved adopting Evolutionary Optimization Algorithms. In particular, in this paper a recently introduced evolutionary approach, named Social Network Optimization (SNO) has been applied to the design of a reduced size shaped beam reflectarray: the obtained numerical results are promising and prove the effectiveness of the adopted method

Design of wave-optical structured substrates for ultra-thin perovskite solar cells

grant agreement No 763989 UID/CTM/50025/2019 PTDC/NAN-OPT/28430/2017 PD/BD/143031/2018 SFRH/BD/148078/2019Photonic micro/nano-structures in the wave-optics regime have shown to be a promising strategy for effective broadband light capture in ultra-thin devices, opening a window of opportunity for cheap, efficient, lightweight and flexible photovoltaics (PV). Here we design, from an optical standpoint, a novel industrially-attractive concept where light trapping is obtained by conformably depositing the solar cell materials onto previously-patterned photonic substrates. This solution is applied and optimized for perovskite solar cells (PSCs) with distinct thicknesses of the perovskite absorber - the conventional (500 nm) and ultra-thin (300 nm) in view of enhanced flexibility - yielding photocurrent improvements up to 22.8% in superstrate cell configuration and 24.4% in substrate-type configuration; thereby coming relatively close to the fundamental Lambertian limits. Furthermore, these structures also show an omni-direction optical response for incidence angles up to 70° for all cases, therefore demonstrating the viability of this light trapping method for implementation in flexible PV devices operating under bending. The photonic-enhanced ultra-thin solar cells designed here ultimately support the reduction of material usage in PSC technology, which is especially beneficial to mitigate lead usage, without impacting the device's performance.preprintpublishe

Nanophotonic design and nanomaterial assembly for next-generation optoelectronics

Nanomaterials are widely deployed in many optoelectronic technologies, with applications in solar energy harvesting, light emission, bio-sensing, computing and communications. The unique advantages of colloidal nanomaterials include size-tunable optical properties and room-temperature solution-processability, which translates to low-cost materials growth and fabrication processes associated with nanomaterials-based technology. Moreover, their lightweight and thin-film nature enables optoelectronic devices made from nanomaterials to be flexibly coated on almost any surface, which is ideal for applications such as wearable electronics and building-integrated photovoltaics. This thesis focuses on combining optical modeling, nanomaterials synthesis, nanofabrication, and advanced optical and electrical characterization techniques to develop nanomaterial-based next-generation optoelectronic devices. The first section of this thesis focuses on applying nanophotonics design principles to optically engineer solar cell and photodetector device structures for specific applications. One of our studies demonstrated a high-performing visible-blind ultraviolet (UV) thin film photodetector by introducing nanoheterojunctions for enhanced absorption and carrier injection. In another study, we used optical simulations and an effective medium model to investigate and predict light-trapping enhancements by embedding plasmonic nano-inclusions in the absorbing layer of solution-processed solar cells. We also combined thin-film interference engineering and multi-objective optimization algorithms to control the color and transparency of colloidal quantum dot (CQD) solar cells for applications in building-integrated photovoltaics and multi-junction photovoltaics. In the final study of this section, we proposed and investigated engineering photonic bands in strongly absorbing materials to tune the spectral selectivity of optoelectronic films. We then focus on developing lead sulfide CQD-based light emitting diodes (QLEDs) and solar cells with novel functionality. We developed a room-temperature-processed silver-nanowire-based transparent electrode for flexible optoelectronics. With carefully-tuned nanomaterials synthesis conditions, we fabricated PbS QLEDs with near-infrared emission that can be easily detected by inexpensive silicon-based photodetectors, paving the way for our proposed flexible transparent light emitting membrane technology, which has many target applications including in next-generation virtual reality googles and motion-capture suits for the film industry. We also built a semi-automated spray-casting system to demonstrate an all-solution-processed CQD solar cell, as a scalable and portable method for manufacturing CQD solar cells, expanding the application areas of this technology

Engineering Tunable Colloidal Nanostructures for Light Energy Harvesting

Colloidal nanomaterials, such as semiconductor quantum dots and plasmonic metal nanoparticles, are of interest for various optoelectronic applications due to their size-tunable optical properties, unique electronic structures, and low-cost fabrication techniques. As the physical footprint of emerging optoelectronic device components continues to shrink, colloidal nanomaterials have the potential to enable advances in fields such as low-power computing, renewable energy generation and storage, and biosensing and medicine, due to their small size, earth-abundance, and novel functionality. This thesis focuses on engineering these nanostructures for energy harvesting technologies, such as solar cells, photodetectors and photocatalysts. This is achieved by combining modeling, nanofabrication, and advanced optical and electrical characterization techniques. The study is implemented in three sections. The first involves engineering these nanostructures for solution processed solar cells. Using optimization algorithms combined with thin film interference modeling, we developed a method for producing arbitrary spectral profiles in solar cells structures for potential applications in building- and window-integrated power generation. Similarly, by using photonic band engineering in strongly absorbing materials, we developed and analyzed a new strategy for tuning the spectral selectivity of optoelectronic films. Additionally we critically evaluate the prospects for plasmonic enhancements in solution-processed thin-film solar cells by developing an intuitive effective medium model for embedded plasmonic nanostructures in photovoltaic thin films. The next section involves investigating these nanostructures for photon detection applications. One study involves using a one-step solution-based growth technique to grow antimony selenide nanowires. This enables the growth of high-quality antimony selenide nanostructures from a molecular ink directly on flexible substrates for high-performance near-infrared photodetectors thus providing a route for low-cost, flexible, and broadband photon detection. The other study demonstrates high responsivity visible blind photodetectors based on nanoheterojunction films, thus representing a viable path for building UV cost-effective optoelectronic devices Finally, the last section includes designing, developing and characterizing new plasmonic-catalytic systems based on earth-abundant and cost-effective nanomaterials such as aluminum. We present the first photophysical characterization of plasmonic aluminum nanoparticles, and identify tuning strategies such as surface modifications for various niche applications. These three sections culminate in creating a sustainable route to building both an energy-efficient and scalable-materials platform for the next generation of nanotechnology-based optoelectronic devices for energy applications

Searches for Neutrinos from Supernovae Using Cherenkov In-Ice Detectors

Supernovae mark the violent death of massive stars. They are among the most energetic processes known to exist in the Universe. Neutrinos play crucial roles in supernova processes. Besides the low-energy neutrinos emitted during the core-collapse process of the supernova, there may be neutrinos of much higher energies that are generated after the core-collapse. In this work, a new detector embedded in Antarctic glacier ice is studied, with sensitivity to extra-galactic supernova low-energy neutrino bursts. It is demonstrated that the development of optical sensors with large effective area and low noise rate is a requirement. For the proposed detector, several extra-galactic supernova neutrino detections per year are feasible. In addition, a multi-messenger data analysis program is carried out, which registers high-energy neutrino bursts with the IceCube detector and triggers follow-up observations with optical telescopes. No significant excess of neutrino bursts is found. Therefore, upper limits on the jet supernova model are derived. For model values of the jet Lorentz factor Γjet = 10 and the jet kinetic energy Ejet = 3 × 1051 erg, only about 8% of all core-collapse supernovae hosting a jet are consistent with the data.Suche nach Supernova-Neutrinos mit Cherenkov-Detektoren in Eis Supernovae sind gewaltige Explosionen am Lebensende massereicher Sterne. Sie gehören zu den energiereichsten bekannten Prozessen im Universum. Neutrinos spielen entscheidende Rollen während und nach Supernova-Explosionen. Neben den niederenergetischen Neutrinos, die während des Kernkollapsprozesses der Supernova emittiert werden, könnten Neutrinos von sehr viel höherer Energie nach dem Kernkollaps enstehen. In dieser Arbeit wird ein neues Detektorkonzept untersucht, mit Sensitivität für extragalaktische niederenergetische Supernova-Neutrino-Blitze. Die Notwendigkeit der Entwicklung optischer Sensoren mit großer effektiver Fläche und niedriger Rauschrate wird aufgezeigt. Der untersuchte Detektor könnte mehrere extra-galaktische Supernova-Neutrino-Detektionen pro Jahr liefern. Weiter wird ein multi-messenger Datenanalyseprogramm durchgeführt, welches hochenergetische Neutrinoblitze mit dem IceCube-Detektor registriert und automatisch Nachfolgebeobachtungen mit optischen Teleskopen auslöst. Kein signifikanter Exzess von Neutrino-Blitzen wird gefunden. Entsprechend werden obere Grenzen auf das Jet-Supernova-Modell berechnet. Für die Modellparameter Lorentzfaktor Γjet = 10 und kinetische Energie des Jets Ejet = 3 × 1051 erg sind höchstens etwa 8% aller Kernkollaps-Supernovae als Träger eines solchen Jets mit den Daten verträglich

Recent Development of Hybrid Renewable Energy Systems

Abstract: The use of renewable energies continues to increase. However, the energy obtained from renewable resources is variable over time. The amount of energy produced from the renewable energy sources (RES) over time depends on the meteorological conditions of the region chosen, the season, the relief, etc. So, variable power and nonguaranteed energy produced by renewable sources implies intermittence of the grid. The key lies in supply sources integrated to a hybrid system (HS)

Technology 2001: The Second National Technology Transfer Conference and Exposition, volume 1

Papers from the technical sessions of the Technology 2001 Conference and Exposition are presented. The technical sessions featured discussions of advanced manufacturing, artificial intelligence, biotechnology, computer graphics and simulation, communications, data and information management, electronics, electro-optics, environmental technology, life sciences, materials science, medical advances, robotics, software engineering, and test and measurement

A cumulative index to a continuing bibliography on aeronautical engineering

This bibliography is a cumulative index to the abstracts contained in NASA-SP-7037(184) through NASA-SP-7037(195) of Aeronautical Engineering: A Continuing Bibliography. NASA SP-7037 and its supplements have been compiled through the cooperative efforts of the American Institute of Aeronautics and Astronautics (AIAA) and the National Aeronautics and Space Administration (NASA). This cumulative index includes subject, personal author, corporate source, foreign technology, contract, report number, and accession number indexes

Advanced Computational Methods for Oncological Image Analysis

[Cancer is the second most common cause of death worldwide and encompasses highly variable clinical and biological scenarios. Some of the current clinical challenges are (i) early diagnosis of the disease and (ii) precision medicine, which allows for treatments targeted to specific clinical cases. The ultimate goal is to optimize the clinical workflow by combining accurate diagnosis with the most suitable therapies. Toward this, large-scale machine learning research can define associations among clinical, imaging, and multi-omics studies, making it possible to provide reliable diagnostic and prognostic biomarkers for precision oncology. Such reliable computer-assisted methods (i.e., artificial intelligence) together with clinicians’ unique knowledge can be used to properly handle typical issues in evaluation/quantification procedures (i.e., operator dependence and time-consuming tasks). These technical advances can significantly improve result repeatability in disease diagnosis and guide toward appropriate cancer care. Indeed, the need to apply machine learning and computational intelligence techniques has steadily increased to effectively perform image processing operations—such as segmentation, co-registration, classification, and dimensionality reduction—and multi-omics data integration.