HDG methods and data-driven techniques for the van Roosbroeck model and its applications

Noninvasive estimation of doping inhomogeneities in semiconductors is relevant for many industrial applications. The goal is to estimate experimentally the unknown doping profile of a semiconductor by means of reproducible, indirect and non--destructive measurements. A number of technologies (such as LBIC, EBIC and LPS) have been developed which allow the indirect detection of doping variations via photovoltaic effects. The idea is to illuminate the sample at several positions while measuring the resulting voltage drop or current at the contacts. These technologies lead to inverse problems for which we still do not have a complete theoretical framework. In this thesis, we present three different data-driven approaches based on least squares, multilayer perceptrons, and residual neural networks. We compare the three strategies after having optimized the relevant hyperparameters and we measure the robustness of our approaches with respect to noise. The methods are trained on synthetic data sets (pairs of discrete doping profiles and corresponding photovoltage signals at different illumination positions) which are generated by a numerical solution of the forward problem using a physics-preserving finite volume method stabilized using the Scharfetter--Gummel scheme. In view of the need of generating larger datasets for trainings, we study the possibility to apply high-order Discontinuous Galerkin methods to the forward problem, preserving the stability properties of the Scharfetter--Gummel scheme. We prove that the Hybridizable Discontinuous Galerkin methods (HDG), a family of high-order DG methods, are equivalent to the Scharfetter--Gummel scheme on uniform unidimensional grids for a specific choice of the HDG stabilization parameter. This result is generalized to two and three dimensions using an approach based on weighted scalar products, and on local Slotboom changes of variables. We show that the proposed numerical scheme is well-posed, and numerically validate that it has the same properties of classical HDG methods, including optimal convergence and superconvergence of postprocessed solutions. For polynomial degree zero, dimension one, and vanishing HDG stabilization parameter, W-HDG coincides with the Scharfetter-Gummel stabilized finite volume scheme (i.e., it produces the same system matrix)

NASA Tech Briefs, January 1989

Topics include: Electronic Components & and Circuits. Electronic Systems, A Physical Sciences, Materials, Computer Programs, Mechanics, Machinery, Fabrication Technology, Mathematics and Information Sciences, and Life Sciences

The Fifth NASA Symposium on VLSI Design

The fifth annual NASA Symposium on VLSI Design had 13 sessions including Radiation Effects, Architectures, Mixed Signal, Design Techniques, Fault Testing, Synthesis, Signal Processing, and other Featured Presentations. The symposium provides insights into developments in VLSI and digital systems which can be used to increase data systems performance. The presentations share insights into next generation advances that will serve as a basis for future VLSI design

The Second Annual International Space University Alumni Conference

The papers presented at the conference reflect the multidisciplinary nature of the International Space University (ISU) and its alumni. The first papers presented hold special relevance to the design projects, and cover such topics as lunar-based astronomical instrumentation, solar lunar power generation, habitation on the moon, and the legal issues governing multinational astronauts conducting research in space. The next set of papers cover various technical issues such as project success assessment, satellite networks and space station dynamics, thus reflecting the diverse backgrounds of the ISU alumni

A Contribution Towards Intelligent Autonomous Sensors Based on Perovskite Solar Cells and Ta2O5/ZnO Thin Film Transistors

Many broad applications in the field of robotics, brain-machine interfaces, cognitive computing, image and speech processing and wearables require edge devices with very constrained power and hardware requirements that are challenging to realize. This is because these applications require sub-conscious awareness and require to be always “on”, especially when integrated with a sensor node that detects an event in the environment. Present day edge intelligent devices are typically based on hybrid CMOS-memristor arrays that have been so far designed for fast switching, typically in the range of nanoseconds, low energy consumption (typically in nano-Joules), high density and endurance (exceeding 1015 cycles). On the other hand, sensory-processing systems that have the same time constants and dynamics as their input signals, are best placed to learn or extract information from them. To meet this requirement, many applications are implemented using external “delay” in the memristor, in a process which enables each synapse to be modeled as a combination of a temporal delay and a spatial weight parameter. This thesis demonstrates a synaptic thin film transistor capable of inherent logic functions as well as compute-in-memory on similar time scales as biological events. Even beyond a conventional crossbar array architecture, we have relied on new concepts in reservoir computing to demonstrate a delay system reservoir with the highest learning efficiency of 95% reported to date, in comparison to equivalent two terminal memristors, using a single device for the task of image processing. The crux of our findings relied on enhancing our capability to model the unique physics of the device, in the scope of the current thesis, that is not amenable to conventional TCAD simulations. The model provides new insight into the redox characteristics of the gate current and paves way for assessment of device performance in compute-in-memory applications. The diffusion-based mechanism of the device, effectively enables time constants that have potential in applications such as gesture recognition and detection of cardiac arrythmia. The thesis also reports a new orientation of a solution processed perovskite solar cell with an efficiency of 14.9% that is easily integrable into an intelligent sensor node. We examine the influence of the growth orientation on film morphology and solar cell efficiency. Collectively, our work aids the development of more energy-efficient, powerful edge-computing sensor systems for upcoming applications of the IOT

Special oils for halal and safe cosmetics

Three types of non conventional oils were extracted, analyzed and tested for toxicity. Date palm kernel oil (DPKO), mango kernel oil (MKO) and Ramputan seed oil (RSO). Oil content for tow cultivars of dates Deglect Noor and Moshkan was 9.67% and 7.30%, respectively. The three varieties of mango were found to contain about 10% oil in average. The red yellow types of Ramputan were found to have 11 and 14% oil, respectively. The phenolic compounds in DPKO, MKO and RSO were 0.98, 0.88 and 0.78 mg/ml Gallic acid equivalent, respectively. Oils were analyzed for their fatty acid composition and they are rich in oleic acid C18:1 and showed the presence of (dodecanoic acid) lauric acid C12:0, which reported to appear some antimicrobial activities. All extracted oils, DPKO, MKO and RSO showed no toxic effect using prime shrimp bioassay. Since these oils are stable, melt at skin temperature, have good lubricity and are great source of essential fatty acids; they could be used as highly moisturizing, cleansing and nourishing oils because of high oleic acid content. They are ideal for use in such halal cosmetics such as Science, Engineering and Technology 75 skin care and massage, hair-care, soap and shampoo products

Rising stars in energy research: 2022

Recognising the future leaders of Energy Research is fundamental to safeguarding tomorrow's driving force in innovation. This collection will showcase the high-quality work of internationally recognized researchers in the early stages of their careers. We aim to highlight research by leading scientists of the future across the entire breadth of Energy Research, and present advances in theory, experiment and methodology with applications to compelling problems

Control of active cell balancing systems : innovation report

Lithium-ion battery packs are increasingly being used for high power and energy applications such as electric vehicles and grid storage. These battery packs consist of many individual cells connected in series and/or parallel. Manufacturing tolerances and varied operating conditions mean that each cell will be different one from another, being able to store different amounts of energy and deliver different amounts of power. This also means some cells will finish charging or discharging before others, resulting in unutilised energy in the remaining cells. Passive balancing systems are often used in multi-cell battery packs to ensure that all of the cells can be fully charged. However, this does not account for differences in cell capacity, meaning that not all cells will be fully discharged. Active balancing systems have been developed to transfer energy between the cells, in theory allowing for stronger cells to compensate for weaker ones. However, their perceived cost and complexity have prevented them from being widely adopted in commercial applications. In this work, an innovative control strategy was developed to determine how and when to energy balance a set of battery cells, with the aim of maximising battery pack energy utilisation. A model-based control system was designed, using state of charge to evaluate the level of energy imbalance between cells. Real-time implementation using second-hand electric vehicle cells and commercial balancing hardware demonstrated that the control strategy can decrease the amount of unused charge in the battery pack from 8% with passive balancing to 1% with active balancing, which has significant impact for battery pack energy throughput, physical size, mass, and long-term health

Photonic Technology for Precision Metrology

Photonics has had a decisive influence on recent scientific and technological achievements. It includes aspects of photon generation and photon–matter interaction. Although it finds many applications in the whole optical range of the wavelengths, most solutions operate in the visible and infrared range. Since the invention of the laser, a source of highly coherent optical radiation, optical measurements have become the perfect tool for highly precise and accurate measurements. Such measurements have the additional advantages of requiring no contact and a fast rate suitable for in-process metrology. However, their extreme precision is ultimately limited by, e.g., the noise of both lasers and photodetectors. The Special Issue of the Applied Science is devoted to the cutting-edge uses of optical sources, detectors, and optoelectronics systems in numerous fields of science and technology (e.g., industry, environment, healthcare, telecommunication, security, and space). The aim is to provide detail on state-of-the-art photonic technology for precision metrology and identify future developmental directions. This issue focuses on metrology principles and measurement instrumentation in optical technology to solve challenging engineering problems