Modelling and characterization of Quantum Dots as QLED devices for automotive lighting systems

This work reports the design, manufacturing and numerical simulation approach of an electroluminescent quantum dot light emitting device (QLED) based on quantum dots as an active layer. In addition, the electrical I-V curve was measured, observing how the fabrication process and layer thickness have an influence in the shape of the plot. This experimental device enabled us to create a computational model for the QLED based on the Transfer Hamiltonian approach to calculate the current density J(mA/cm2), the band diagram of the system and the accumulated charge distribution. Thanks to the QLED simulator developed, it would be possible to model the device and anticipate the electrical performance in a theoretical design step before going to QLED manufacturing at the laboratory. Eventually, particular automotive lighting system demonstrators were designed to integrate the theoretical and experimental research carried out in an industrial automotive product.Tesis Univ. Granada

Polychromatic determination of spectral response of PV devices

This thesis introduces a novel spectral response (SR) measurement technique using polychromatic filters (filters with very broad spectral transmittances) to determine SR of large area PV devices. Conventionally, SR of a photovoltaic (PV) device is determined by illuminating the device under test (DUT) with a series of monochromatic beams at different wavelengths as described in the international standard IEC 60904-8, or beams of limited spectral content using narrow band pass filters or monochromator. One significant problem associated with the application of the narrow band pass filters for a large-area SR measurement is that low light intensity produced on the measurement plane particularly in certain wavelength ranges: the ultraviolet and infrared. This can produce weak signal responses from a tested PV device. In addition, the imperfection of the filter s mounting position can shift the peak wavelength of the filter s transmittance at angle of incidence greater than 10. This can cause stray light on the measurement plane. The proposed SR measurement method is called as the polychromatic SR fitting method or, in short, it is known as the polychromatic method . The advantage of this method is that higher beam intensity can be produced on the measurement plane as a result of large spectral transmittance of the polychromatic filters. This can improve the signal strength of a tested PV device. This new SR measurement method works by comparing the variations in the currents which are measured at different spectra to the currents which are calculated at the same spectral conditions using the SR model. Validations of this method for a large- and small-area SR determinations show that it is potentially feasible as a new technique for determining SR of a PV device with deviations within ±2% across the wavelength bands

Image based analysis of visibility in smoke laden environments

This study investigates visibility in a smoke laden environment. For many years, researchers and engineers in fire safety have criticized the inadequacy of existing theory in describing the effects such as colour, viewing angle, environmental lighting etc. on the visibility of an emergency sign. In the current study, the author has raised the fundamental question on the concept of visibility and how it should be measured in fire safety engineering and tried to address the problem by redefining visibility based on the perceived image of a target sign. New algorithms have been created during this study to utilise modern hardware and software technology in the simulation of human perceived image of object in both experiment and computer modelling. Unlike the traditional threshold of visual distance, visibility in the current study has been defined as a continuous function changing from clearly discemable to completely invisible. It allows the comparison of visibility under various conditions, not just limited to the threshold. Current experiment has revealed that different conditions may results in the same visual threshold but follow very different path on the way leading to the threshold. The new definition of visibility has made the quantification of visibility in the pre-threshold conditions possible. Such quantification can help to improve the performance of fire evacuation since most evacuees will experience the pre-threshold condition. With current measurement of visibility, all the influential factors such as colour, viewing angle etc. can be tested in experiment and simulated in numerical model. Based on the newly introduced definition of visibility, a set of experiments have been carried output in a purposed built smoke tunnel. Digital camera images of various illuminated signs were taken under different illumination, colour and smoke conditions. Using an algorithm developed by the author in this study, the digital camera images were converted into simulated human perceived images. The visibility of a target sign is measured against the quality of its image acquired. Conclusions have been drawn by comparing visibility under different conditions. One of them is that signs illuminated with red and green lights have the similar visibility that is far better than that with blue light. It is the first time this seemingly obvious conclusion has been quantified. In the simulation of visibility in participating media, the author has introduced an algorithm that combines irradiance catching in 3D space with Monte Carlo ray tracing. It can calculate the distribution of scattered radiation with good accuracy without the high cost typically related to zonal method and the limitations in discrete ordinate method. The algorithm has been combined with a two pass solution method to produce high resolution images without introducing excessive number of rays from the light source. The convergence of the iterative solution procedure implemented has been theoretically proven. The accuracy of the model is demonstrated by comparing with the analytical solution of a point radiant source in 3D space. Further validation of the simulation model has been carried out by comparing the model prediction with the data from the smoke tunnel experiments. The output of the simulation model has been presented in the form of an innovative floor map of visibility (FMV). It helps the fire safety designer to identify regions of poor visibility in a glance and will prove to be a very useful tool in performance based fire safety design

LASER Tech Briefs, February 1995

Topics included in this issue of LASER Tech Briefs are: Electronic Components and Circuits. Electronic Systems, Physical Sciences, Materials, Mechanics, Fabrication, and Mathematics and Information Sciences, an

Image based analysis of visibility in smoke laden environments

This study investigates visibility in a smoke laden environment. For many years, researchers and engineers in fire safety have criticized the inadequacy of existing theory in describing the effects such as colour, viewing angle, environmental lighting etc. on the visibility of an emergency sign. In the current study, the author has raised the fundamental question on the concept of visibility and how it should be measured in fire safety engineering and tried to address the problem by redefining visibility based on the perceived image of a target sign. New algorithms have been created during this study to utilise modern hardware and software technology in the simulation of human perceived image of object in both experiment and computer modelling. Unlike the traditional threshold of visual distance, visibility in the current study has been defined as a continuous function changing from clearly discemable to completely invisible. It allows the comparison of visibility under various conditions, not just limited to the threshold. Current experiment has revealed that different conditions may results in the same visual threshold but follow very different path on the way leading to the threshold. The new definition of visibility has made the quantification of visibility in the pre-threshold conditions possible. Such quantification can help to improve the performance of fire evacuation since most evacuees will experience the pre-threshold condition. With current measurement of visibility, all the influential factors such as colour, viewing angle etc. can be tested in experiment and simulated in numerical model.Based on the newly introduced definition of visibility, a set of experiments have been carried output in a purposed built smoke tunnel. Digital camera images of various illuminated signs were taken under different illumination, colour and smoke conditions. Using an algorithm developed by the author in this study, the digital camera images were converted into simulated human perceived images. The visibility of a target sign is measured against the quality of its image acquired. Conclusions have been drawn by comparing visibility under different conditions. One of them is that signs illuminated with red and green lights have the similar visibility that is far better than that with blue light. It is the first time this seemingly obvious conclusion has been quantified.In the simulation of visibility in participating media, the author has introduced an algorithm that combines irradiance catching in 3D space with Monte Carlo ray tracing. It can calculate the distribution of scattered radiation with good accuracy without the high cost typically related to zonal method and the limitations in discrete ordinate method. The algorithm has been combined with a two pass solution method to produce high resolution images without introducing excessive number of rays from the light source. The convergence of the iterative solution procedure implemented has been theoretically proven. The accuracy of the model is demonstrated by comparing with the analytical solution of a point radiant source in 3D space. Further validation of the simulation model has been carried out by comparing the model prediction with the data from the smoke tunnel experiments.The output of the simulation model has been presented in the form of an innovative floor map of visibility (FMV). It helps the fire safety designer to identify regions of poor visibility in a glance and will prove to be a very useful tool in performance based fire safety design

Demystifying Event-based Sensor Biasing to Optimize Signal to Noise for Space Domain Awareness

Neuromorphic dynamic vision sensors (DVS), often called event-based sensors (EBS), are a novel class of cameras that have recently shown potential to make a significant impact in the SDA community. Their biologically-inspired design simultaneously achieves high temporal resolution, wide dynamic range, low power consumption and sparse data output, making them an ideal fit for space applications. Although initial results for SDA are promising, they typically exhibit elevated noise rates in dim conditions and have thus far failed to outperform conventional cameras in terms of limiting visual magnitude and sensitivity with high telescope scan rates. A hurdle for widespread adoption is a lack of general guidance regarding optimal camera biases (settings) for SDA. Prior studies either serve as proof of concept or focus on algorithm development; however, to date, none have provided detailed guidance on biasing EBS to optimize signal to noise ratio (SNR) for SDA tasks. The goal of this paper is to narrow the knowledge gap between EBS pixel biasing and resulting performance to optimize their capabilities for SDA. To accomplish this, we adopt a bottom-up approach, revisiting the pixel architecture to consider physics-based performance limitations. In an EBS, each pixel responds autonomously, generating "events" in response to local brightness changes within its field of view (FOV), and outputs a sparse representation of the visual scene where each event is encoded by a pixel address (x,y), a microsecond resolution timestamp (t), and a single bit polarity value (p) indicating either an increase or decrease in brightness by a defined threshold. In most camera models, behavior is fine-tuned by adjusting roughly a half-dozen biases, including threshold levels (sensitivity), bandwidth (speed of the front-end photoreceptor), and refractory period (dead-time between events in a given pixel). These parameters make EBS cameras adaptable for varied applications, but many degrees of freedom presents a challenge for optimization. Researchers unfamiliar with the technology can be overwhelmed by the myriad of biasing options and must either rely on a prescribed set of biases or manually adjust them to achieve desired performance; the latter is not typically recommended for non-experts due to 2nd-order effects such as excessive noise rates. Manufacturer default biases are considered optimized for a broad range of applications, but recent studies have demonstrated non-conventional bias techniques can significantly reduce background noise in dim conditions while still retaining signal, suggesting that SDA capabilities could be improved by a more sophisticated biasing strategy. By conducting a detailed study of how sensitivity, response speed, and noise rates scale with varied bias configurations, we aim to approach an optimal SNR bias configuration and demonstrate the maximal capabilities of current generation COTS EBS cameras for SDA. To systematically analyze and benchmark performance against a calibrated and repeatable stimulus, we developed a custom SDA test-bench to simulate stars/satellites as sub-pixel point source targets of variable speed and brightness. The set-up includes an integrating light box to provide a calibrated flat-field illumination source, a custom 170 mm radius anodized aluminum disk with precision drilled holes of diameters ranging from 100 to 250 microns, and a digitally programmable motor capable of precise speed control from ~0.1 to 800 RPM. The disk is backlit by the flat-field illumination source and connected to the motor shaft, and a 7 x 10 cm region is viewed through a Fujinon 1:1.8/7-70mm CS mount lens at a distance of 50 cm. The FOV and zoom are chosen such that the dimension of the largest holes is still sub-pixel in diameter when in focus. Even with the ability to rapidly collect measurements with this setup, the overall parameter space is still too large to fully explore without any a-priori knowledge about how the sensor responds to signal and noise, and how this depends on biases. As a result, we consider fundamental pixel behaviors to devise an efficient test strategy. We first consider strategies to limit noise rates, as these can overwhelm sensor readout when the background is dark. In prior work, this was presumably accomplished by either reducing the bandwidth biases or increasing threshold biases, but these approaches inherently limit signal. Instead of this naive approach, we draw inspiration from two recent studies: the first demonstrated an optimal balance between two bandwidth related biases accessible in some camera prototypes, and the second relies on a key observation about the statistical distribution of noise events to devise two additional biasing techniques to enhance SNR by allowing either lower thresholds or broader bandwidth settings. Using these techniques as a starting point, we examine the performance the DAVIS346 EBS. We first report baseline performance using manufacturer default biases. To quantify performance, we measure sensitivity (dimmest point source detected) and bandwidth (fastest point source detected). Next, we tune bias settings with specific detection goals (i.e. maximum velocity and/or minimum brightness) and analyze the results. Finally, we apply newly developed low-noise bias techniques and attempt to identify general principles that can be applied universally to any EBS camera to improve performance in SDA tasks. This paper provides a baseline for understanding EBS performance characteristics and will significantly lower the entry barrier for new researchers in the field of event-based SDA. More importantly, it adds insight for optimizing EBS behavior for SDA tasks and demonstrates the absolute performance limits of current generation cameras for detecting calibrated point source targets against a dark background. Finally, this study will enable follow-on work including the development of customized denoising, detection, and tracking algorithms that consider signal response and noise statistics as a function of the selected camera and bias configuration