In this study, the optical simulation software Light Tools was executed to reduce the LED amount used by improving the performance of light guide plate of backlight module with LED illuminator. The improvement of the design including: 1.replacing the V-cut microstructures on the lower layer of the light guide plate by the micro-semispherical lens structures;2.replacing the diffusion film by the micro-semispherical lens structures on the upper layer of the light guide plate ; 3.adding the lateral microstructure on the light guide plate to reduce the dark-area phenomenon. The sizes of upper/lower microstructures, their spacings and the amount of LED were selected as the parameters and applying L18 orthogonal array to process the simulations firstly. Then integrating different kind of lateral microstructures to find the best uniformity, and obtain a set of parameters that could improve the performance of backlight module and then the amount of LED can be reduced. The results show that the uniformity of backlight module is over 88% without diffusion film which have overcome the requirement of 85% in traditional design with 2 diffusion films. This improvement not only reduces the cost from diffusion film, also removes the dark-area phenomenon. Additionally, the amount of LED is reduced to 45 from 48 that retrench about 7% of power. Energy and cost are saved simultaneously.

Aluminium titanium oxynitrides were studied as candidate materials for high temperature absorbers in solar selective coatings due to their excellent stability and their tuneable optical behaviour. A set of individual AlyTi1-y(OxN1-x) layers with different oxygen content was prepared by cathodic vacuum arc (CVA) deposition. The composition, morphology, phase structure and microstructure of the films were characterized by elastic recoil detection (ERD), scanning and transmission electron microscopy and X-ray diffraction. An fcc phase structure is found in a broad compositional range of AlyTi1-y(OxN1-x). Simultaneously, sample microstructure and morphology undergo systematic changes from a columnar growth to the development of a heterogeneous structure with spherical nanoparticle inclusions when the oxygen concentration is increased. The optical properties were determined by spectroscopic ellipsometry and UV–Vis–NIR and FTIR spectrophotometry. A comprehensive analysis of the film properties allowed an accurate modelling of the optical constants of the AlyTi1-y(OxN1-x) in the whole wavelength range of solar interest (from 190 nm to 25 µm). It points to a transition from metallic to dielectric behaviour with increasing oxygen content. Consequently, it is demonstrated that the optical properties of these AlyTi1-y(OxN1-x) deposited films can be controlled in a wide range from metallic to dielectric character by adjusting the oxygen concentration, opening a huge range of possibilities for the design of solar selective coatings (SSC) based on this material. Complete SSC, including a TiN layer as IR reflector, were designed by applying optical simulations, obtaining excellent optical selective properties of α=94.0% and εRT = 4.8%.

abstract: Solar energy has become one of the most popular renewable energy in human’s life because of its abundance and environment friendliness. To achieve high solar energy conversion efficiency, it usually requires surfaces to absorb selectivity within one spectral range of interest and reflect strongly over the rest of the spectrum. An economic method is always desired to fabricate spectrally selective surfaces with improved energy conversion efficiency. Colloidal lithography is a recently emerged way of nanofabrication, which has advantages of low-cost and easy operation. In this thesis, aluminum metasurface structures are proposed based on colloidal lithography method. High Frequency Structure Simulator is used to numerically study optical properties and design the aluminum metasurfaces with selective absorption. Simulation results show that proposed aluminum metasurface structure on aluminum oxide thin film and aluminum substrate has a major reflectance dip, whose wavelength is tunable within the near-infrared and visible spectrum with metasurface size. As the metasurface is opaque due to aluminum film, it indicates strong wavelength-selective optical absorption, which is due to the magnetic resonance between the top metasurface and bottom Al film within the aluminum oxide layer. The proposed sample is fabricated based on colloidal lithography method. Monolayer polystyrene particles of 500 nm are successfully prepared and transferred onto silicon substrate. Scanning electron microscope is used to check the surface topography. Aluminum thin film with 20-nm or 50-nm thickness is then deposited on the sample. After monolayer particles are removed, optical properties of samples are measured by micro-scale optical reflectance and transmittance microscope. Measured and simulated reflectance of these samples do not have frequency selective properties and is not sensitive to defects. The next step is to fabricate the Al metasurface on Al_2 O_3 and Al films to experimentally demonstrate the selective absorption predicted from the numerical simulation. / Dissertation/Thesis / Masters Thesis Mechanical Engineering 2019

The durability of two solar-selective aluminium titanium oxynitride multilayer coatings was studied under conditions simulating realistic operation of central receiver power plants. The coatings were deposited by cathodic vacuum arc applying an optimized design concept for complete solar-selective coating (SSC) stacks. Compositional, structural and optical characterization of initial and final stacks was performed by scanning electron microscopy, elastic recoil detection, UV-Vis-NIR-IR spectrophotometry and X-Ray diffraction. The design concept of the solar selective coatings was validated by an excellent agreement between simulated and initial experimental stacking order, composition and optical properties. Both SSC stacks were stable in single stage tests of 12 hours at 650°C. At 800°C, they underwent a structural transformation by full oxidation and they lost their solar selectivity. During cyclic durability tests, multilayer 1, comprised of TiN, Al0.64Ti0.36N and an Al1.37Ti0.54O top layer, fulfilled the performance criterion (PC) ≤ 5% for 300 symmetric, 3 hours long cycles at 600°C in air. Multilayer 2, which was constituted of four AlyTi1-y(OxN1-x) layers, met the performance criterion for 250 cycles (750 hours), but was more sensitive to these harsh conditions. With regard to the degradation mechanisms, the coarser microstructure of multilayer 1 is more resistant against oxidation than multilayer 2 with its graded oxygen content. These results confirm that the designed SSCs based on AlyTi1-y(OxN1-x) materials withstand breakdown at 600ºC in air. Therefore, they can be an exciting candidate material for concentrated solar power applications at high temperature.

No description available.

abstract: Current organic light emitting diodes (OLEDs) suffer from the low light extraction efficiency. In this thesis, novel OLED structures including photonic crystal, Fabry-Perot resonance cavity and hyperbolic metamaterials were numerically simulated and theoretically investigated. Finite-difference time-domain (FDTD) method was employed to numerically simulate the light extraction efficiency of various 3D OLED structures. With photonic crystal structures, a maximum of 30% extraction efficiency is achieved. A higher external quantum efficiency of 35% is derived after applying Fabry-Perot resonance cavity into OLEDs. Furthermore, different factors such as material properties, layer thicknesses and dipole polarizations and locations have been studied. Moreover, an upper limit for the light extraction efficiency of 80% is reached theoretically with perfect reflector and single dipole polarization and location. To elucidate the physical mechanism, transfer matrix method is introduced to calculate the spectral-hemispherical reflectance of the multilayer OLED structures. In addition, an attempt of using hyperbolic metamaterial in OLED has been made and resulted in 27% external quantum efficiency, due to the similar mechanism of wave interference as Fabry-Perot structure. The simulation and optimization methods and findings would facilitate the design of next generation, high-efficiency OLED devices. / Dissertation/Thesis / Masters Thesis Mechanical Engineering 2016

Dans le cadre de cette thèse, nous présentons un aperçu général des surfaces du silicium micro et nano structurées, appelées silicium noir (BSi), et obtenues par la gravure ionique réactive cryogénique (cryo-DRIE). Ces surfaces auto-générées peuvent être fabriquées dans un procédé en une seule étape fournissant de grandes surfaces à faible réflectivité sur une large gamme de longueurs d'onde et d'angles d'incidence. Nous examinons plusieurs aspects des surfaces du BSi, incluant les méthodes de fabrication, les applications, les méthodes de caractérisation de sa topographie, les techniques de modélisation pour les simulations optiques, et les mécanismes de croissance. Nous développons ensuite trois principales contributions que cette thèse apporte à l'état de l'art : une meilleure compréhension de la topographie du BSi, la modélisation de son comportement optique et un aperçu de ses mécanismes de formation. Nous développons une nouvelle technique de caractérisation topographique du BSi, utilisant un faisceau ionique localisé dans le plan de l'échantillon pour réaliser une nanotomographie qui reproduit les détails de structure avec une précision inférieure au micron. Nous présentons ensuite différentes méthodes de modélisation de cellules unitaires du BSi basées soit sur la topographie de la surface réelle obtenue, ou sur des formes géométriques équivalentes qui sont statistiquement représentatives de la topographie du BSi. Nous sommes capables d'obtenir une excellente concordance entre les simulations et les données expérimentales. Nous présentons également un modèle capable de simuler toute l'évolution de la surface du BSi allant d'un substrat plat jusqu'à sa topographie entièrement développée, en concordance avec des données obtenues expérimentalement. On produit un diagramme de phase qui saisit les combinaisons de paramètres responsables de la formation du BSi. Nous sommes en mesure de reproduire dans notre modèle, un certain nombre d'effets subtils qui mènent à la densification du motif observé, responsable de la formation du BSi pendant cryo-DRIE / In this thesis, we present a general overview of silicon micro and nanostructured surfaces, known as black silicon (BSi), fabricated with cryogenic deep reactive ion etching (cryo-DRIE). These self-generated surfaces can be fabricated in a single step procedure and provide large surfaces with reduced reflectance over a broad range of wavelengths and angles of incidence. We review several aspects of BSi surfaces, such as its fabrication methods, applications, topography characterization methods, modelling techniques for optical simulations, and growth mechanisms. We then develop three main contributions that this thesis brings to the state of the art: a better understanding of BSi topography, modelling of its optical behaviour and insights into its formation mechanism. We develop a novel BSi topographical characterisation technique which is based on in-plane focused ion beam nanotomography and can reproduce sample details with submicron accuracy. We then present different methods of modelling BSi unit cells, based either on real surface topography obtained using the aforementioned technique, or on equivalent geometric shapes that are statistically representative for BSi topography. We are capable to obtain excellent matching between simulations and experimental data. Finally, we present an experimentally-backed phenomenological model that is capable of simulating the entire evolution of a surface from a planar substrate to fully developed BSi topography. We produce a phase diagram which captures the parameter combinations responsible for BSi formation. We also observe experimentally, and are able to reproduce within our model, a number of subtle effects that lead to the observed pattern densification that is responsible for BSi formation during cryo-DRIE

<p>Imaging at range for the purposes of biometric, scientific, or militaristic applications often suffer due to degradations by the atmosphere. These degradations, due to the non-uniformity of the atmospheric medium, can be modeled as being caused by turbulence. Dating back to the days of Kolmogorov in the 1940’s, the field has had many successes in modeling and some in mitigating the effects of turbulence in images. Today, modern restoration methods are often in the form of learning-based solutions which require a large amount of training data. This places atmospheric turbulence mitigation at an interesting point in its history; simulators which accurately capture the effects of the atmosphere were developed without any consideration of deep learning methods and are often missing critical requirements for today’s solutions.</p><p><br></p><p>In this work, we describe a simulator which is not only fast and accurate but has the additional property of being end-to-end differentiable, allowing for end-to-end training with a reconstruction network. This simulation, which we refer to as Zernike-based simulation, performs at a similar level of accuracy as its purely optics-based simulation counterparts while being up to 1000x faster. To achieve this we combine theoretical developments, engineering efforts, and learning-based solutions. Our Zernike-based simulation not only aids in the application of modern solutions to this classical problem but also opens the field to new possibilities with what we refer to as computational image formation.chimi</p>

The proliferation of reusable space vehicles has fundamentally changed how we inject assets into orbit and beyond, increasing the reliability and frequency of launches. Leading to the rapid development and adoption of new technologies into the Aerospace sector, such as computer vision (CV), machine learning (ML), and distributed networking. All these technologies are necessary to enable genuinely autonomous decision-making for space-borne platforms as our spacecraft travel further into the solar system, and our missions sets become more ambitious, requiring true ``human out of the loop" solutions for a wide range of engineering and operational problem sets. Deployment of systems proficient at classifying, tracking, capturing, and ultimately manipulating orbital assets and components for maintenance and assembly in the persistent dynamic environment of space and on the surface of other celestial bodies, tasks commonly referred to as On-Orbit Servicing and In Space Assembly, have a unique automation potential. Given the inherent dangers of manned space flight/extravehicular activity (EVAs) methods currently employed to perform spacecraft construction and maintenance tasking, coupled with the current limitation of long-duration human flight outside of low earth orbit, space robotics armed with generalized sensing and control machine learning architectures is a tremendous enabling technology. However, the large amounts of sensor data required to adequately train neural networks for these space domain tasks are either limited or non-existent, requiring alternate means of data collection/generation. Additionally, the wide-scale tools and methodologies required for hardware in the loop simulation, testing, and validation of these new technologies outside of multimillion-dollar facilities are largely in their developmental stages. This dissertation proposes a novel approach for simulating space-based computer vision sensing and robotic control using both physical and virtual reality testing environments. This methodology is designed to both be affordable and expandable, enabling hardware in the loop simulation and validation of space systems at large scale across multiple institutions. While the focus of the specific computer vision models in this paper are narrowly focused on solving imagery problems found on orbit, this work can be expanded to solve any problem set that requires robust onboard computer vision, robotic manipulation, and free flight capabilities. / Doctor of Philosophy / The lack of real-world imagery of space assets and planetary surfaces required to train neural networks to autonomously identify, classify, and perform decision-making in these environments is either limited, none existent, or prohibitively expensive to obtain. Leveraging the power of the unreal engine, motion capture, and theatre projections technologies combined with robotics, computer vision, and machine learning to provide a means to recreate these worlds for the purpose of optical machine learning testing and validation for space and other celestial applications. This dissertation also incorporates domain randomization methods to increase neural network performance for the above mentioned applications.

This diploma thesis describes the design of the illumination system for a Coherence--Controlled Holographic Microscope (CCHM). The theoretical part mentions the history of microscopy, the principle of holography and individual types of interference microscopy. To get closer to the topic, individual light sources and an overview of current illumination systems are mentioned. The diploma thesis also describes the procedure of designing a fiber-optic illumination module for microscopy from optical design through design of construction to the last step, which is assembly and testing of the module.