Low Mass Calibration Target for MM-Wave Remote Sensing Instruments

The reliability of millimeter and sub-millimeter wave radiometer measurements is dependent on the accuracy of the loads they employ as calibration targets. In the recent past on-board calibration loads have been developed for a variety of satellite remote sensing instruments. Unfortunately some of these have suffered from calibration inaccuracies which had poor thermal performance of the calibration target as the root cause. Stringent performance parameters of the calibration target such as low reflectivity, high temperature uniformity, low mass and low power consumption combined with low volumetric requirements remain a challenge for the space instrument developer. In this paper we present a novel multi-layer absorber concept for a calibration load which offers an excellent compromise between very good radiometric performance and temperature uniformity and the mass and volumetric constraints required by space-borne calibration targets.

The Face of Power

Objective: In humans and other animals, open, expansive postures (compared to contracted postures) are evolutionary developed expressions of power and have been shown to cause neuroendocrine and behavioral changes (Carney, Cuddy, & Yap, 2010). In the present study we aimed to investigate whether power postures have a bearing on the participant’s facial appearance and whether others are able to distinguish faces after “high power posing” from faces after “low power posing”. Methods: 16 models were photographed 4-5 minutes after having adopted high and low power postures. Two different high power and two different low power postures were held for 2 minutes each. Power-posing sessions were performed on two consecutive days. High and low power photographs of each model were paired and an independent sample of 100 participants were asked to pick the more dominant and the more likeable face of each pair. Results: Photographs that were taken after adopting high power postures were chosen significantly more often as being more dominant looking. There was no preference when asked to choose the more likeable photograph (chance level). A further independent sample rated each photograph for head tilt, making it unlikely that dominance ratings were caused merely by the posture of the head. Consistently, facial width-to-height ratio did not differ between faces after high and low power posing. Conclusions: Postures associated with high power affect facial appearance, leading to a more dominant looking face. This finding may have implications for everyday life, for instance when a dominant appearance is needed.

Impact of N2 plasma power and duration on AlGaN/GaN HEMT

urface treatments have been recently shown to play an active role in electrical characteristics in AlGaN/GaN HEMTs, in particular during the passivation processing [1-4]. However, the responsible mechanisms are partially unknown and further studies are demanding. The effects of power and time N2 plasma pre-treatment prior to SiN deposition using PE-CVD (plasma enhanced chemical vapour deposition) on GaN and AlGaN/GaN HEMT have been investigated. The low power (60 W) plasma pre-treatment was found to improve the electronic characteristics in GaN based HEMT devices, independently of the time duration up to 20 min. In contrast, high power (150 and 210 W) plasma pretreatment showed detrimental effects in the electronic properties (Fig. 1), increasing the sheet resistance of the 2DEG, decreasing the 2DEG charge density in AlGaN/GaN HEMTs, transconductance reduction and decreasing the fT and fmax values up to 40% respect to the case using 60 W N2 plasma power. Although AFM (atomic force microscopy) results showed AlGaN and GaN surface roughness is not strongly affected by the N2-plasma, KFM (Kelvin force microscopy) surface analysis shows significant changes in the surface potential, trending to increase its values as the plasma power is higher. The whole results point at energetic ions inducing polarization-charge changes that affect dramatically to the 2-DEG charge density and the final characteristics of the HEMT devices. Therefore, we conclude that AlGaN surface is strongly sensitive to N2 plasma power conditions, which turn to be a key factor to achieve a good surface preparation prior to SiN passivation.

Power management techniques in an FPGA-Based WSN node for high performance application

In this work, the power management techniques implemented in a high-performance node for Wireless Sensor Networks (WSN) based on a RAM-based FPGA are presented. This new node custom architecture is intended for high-end WSN applications that include complex sensor management like video cameras, high compute demanding tasks such as image encoding or robust encryption, and/or higher data bandwidth needs. In the case of these complex processing tasks, yet maintaining low power design requirements, it can be shown that the combination of different techniques such as extensive HW algorithm mapping, smart management of power islands to selectively switch on and off components, smart and low-energy partial reconfiguration, an adequate set of save energy modes and wake up options, all combined, may yield energy results that may compete and improve energy usage of typical low power microcontrollers used in many WSN node architectures. Actually, results show that higher complexity tasks are in favor of HW based platforms, while the flexibility achieved by dynamic and partial reconfiguration techniques could be comparable to SW based solutions.

Loss model for a high frequency and low load DC/DC synchronous buck converter

This work presents a behavioral-analytical hybrid loss model for a buck converter. The model has been designed for a wide operating frequency range up to 4MHz and a low power range (below 20W). It is focused on the switching losses obtained in the power MOSFETs. Main advantages of the model are the fast calculation time and a good accuracy. It has been validated by simulation and experimentally with one Ga, power transistor and two Si MOSFETs. Results show good agreement between measurements and the model.

Hybrid behavioral-analytical loss model for a high frequency and low load DC/DC buck converter

This work presents a behavioral-analytical hybrid loss model for a buck converter. The model has been designed for a wide operating frequency range up to 4MHz and a low power range (below 20W). It is focused on the switching losses obtained in the power MOSFETs. Main advantages of the model are the fast calculation time (below 8.5 seconds) and a good accuracy, which makes this model suitable for the optimization process of the losses in the design of a converter. It has been validated by simulation and experimentally with one GaN power transistor and three Si MOSFETs. Results show good agreement between measurements and the model

Impact of N2 plasma power discharge on AlGaN/GaN HEMT performance

The effects of power and time conditions of in situ N2 plasma treatment, prior to silicon nitride (SiN) passivation, were investigated on an AlGaN/GaN high-electron mobility transistor (HEMT). These studies reveal that N2 plasma power is a critical parameter to control the SiN/AlGaN interface quality, which directly affects the 2-D electron gas density. Significant enhancement in the HEMT characteristics was observed by using a low power N2 plasma pretreatment. In contrast, a marked gradual reduction in the maximum drain-source current density (IDS max) and maximum transconductance (gm max), as well as in fT and fmax, was observed as the N2 plasma power increases (up to 40% decrease for 210 W). Different mechanisms were proposed to be dominant as a function of the discharge power range. A good correlation was observed between the device electrical characteristics and the surface assessment by atomic force microscopy and Kelvin force microscopy techniques.

Power-Aware Multi-Objective Evolvable Hardware System on an FPGA

Dynamic and Partial Reconfiguration (DPR) allows a system to be able to modify certain parts of itself during run-time. This feature gives rise to the capability of evolution: changing parts of the configuration according to the online evaluation of performance or other parameters. The evolution is achieved through a bio-inspired model in which the features of the system are identified as genes. The objective of the evolution may not be a single one; in this work, power consumption is taken into consideration, together with the quality of filtering, as the measure of performance, of a noisy image. Pareto optimality is applied to the evolutionary process, in order to find a representative set of optimal solutions as for performance and power consumption. The main contributions of this paper are: implementing an evolvable system on a low-power Spartan-6 FPGA included in a Wireless Sensor Network node and, by enabling the availability of a real measure of power consumption at run-time, achieving the capability of multi-objective evolution, that yields different optimal configurations, among which the selected one will depend on the relative “weights” of performance and power consumption.

Monolithic master oscillator power amplifier at 1.58 µm for lidar measurements

Nowadays the interest in high power semiconductor devices is growing for applications such as telemetry, lidar system or free space communications. Indeed semiconductor devices can be an alternative to solid state lasers because they are more compact and less power consuming. These characteristics are very important for constrained and/or low power supply environment such as airplanes or satellites. Lots of work has been done in the 800-1200 nm range for integrated and free space Master Oscillator Power Amplifier (MOPA) [1]-[3]. At 1.5 ?m, the only commercially available MOPA is from QPC [4]: the fibred output power is about 700 mW and the optical linewidth is 500 kHz. In this paper, we first report on the simulations we have done to determine the appropriate vertical structure and architecture for a good MOPA at 1.58 ?m (section II). Then we describe the fabrication of the devices (section III). Finally we report on the optical and electrical measurements we have done for various devices (section IV).

Towards a real-time 3D object recognition pipeline on mobile GPGPU computing platforms using low-cost RGB-D sensors

In this project, we propose the implementation of a 3D object recognition system which will be optimized to operate under demanding time constraints. The system must be robust so that objects can be recognized properly in poor light conditions and cluttered scenes with significant levels of occlusion. An important requirement must be met: the system must exhibit a reasonable performance running on a low power consumption mobile GPU computing platform (NVIDIA Jetson TK1) so that it can be integrated in mobile robotics systems, ambient intelligence or ambient assisted living applications. The acquisition system is based on the use of color and depth (RGB-D) data streams provided by low-cost 3D sensors like Microsoft Kinect or PrimeSense Carmine. The range of algorithms and applications to be implemented and integrated will be quite broad, ranging from the acquisition, outlier removal or filtering of the input data and the segmentation or characterization of regions of interest in the scene to the very object recognition and pose estimation. Furthermore, in order to validate the proposed system, we will create a 3D object dataset. It will be composed by a set of 3D models, reconstructed from common household objects, as well as a handful of test scenes in which those objects appear. The scenes will be characterized by different levels of occlusion, diverse distances from the elements to the sensor and variations on the pose of the target objects. The creation of this dataset implies the additional development of 3D data acquisition and 3D object reconstruction applications. The resulting system has many possible applications, ranging from mobile robot navigation and semantic scene labeling to human-computer interaction (HCI) systems based on visual information.

Single Events in a COTS Soft-Error Free SRAM at Low Bias Voltage Induced by 15-MeV Neutrons

This paper presents an experimental study of the sensitivity to 15-MeV neutrons of Advanced Low Power SRAMs (A-LPSRAM) at low bias voltage little above the threshold value that allows the retention of data. This family of memories is characterized by a 3D structure to minimize the area penalty and to cope with latchups, as well as by the presence of integrated capacitors to hinder the occurrence of single event upsets. In low voltage static tests, classical single event upsets were a minor source of errors, but other unexpected phenomena such as clusters of bitflips and hard errors turned out to be the origin of hundreds of bitflips. Besides, errors were not observed in dynamic tests at nominal voltage. This behavior is clearly different than that of standard bulk CMOS SRAMs, where thousands of errors have been reported.

Survey on demand side sensitivity to power quality in Ireland

Power systems require a reliable supply and good power quality. The impact of power supply interruptions is well acknowledged and well quantified. However, a system may perform reliably without any interruptions but may have poor power quality. Although poor power quality has cost implications for all actors in the electrical power systems, only some users are aware of its impact. Power system operators are much attuned to the impact of low power quality on their equipment and have the appropriate monitoring systems in place. However, over recent years certain industries have come increasingly vulnerable to negative cost implications of poor power quality arising from changes in their load characteristics and load sensitivities, and therefore increasingly implement power quality monitoring and mitigation solutions. This paper reviews several historical studies which investigate the cost implications of poor power quality on industry. These surveys are largely focused on outages, whilst the impact of poor power quality such as harmonics, short interruptions, voltage dips and swells, and transients is less well studied and understood. This paper examines the difficulties in quantifying the costs of poor power quality, and uses the chi-squared method to determine the consequences for industry of power quality phenomenon using a case study of over 40 manufacturing and data centres in Ireland.

Average-case analysis of power consumption in embedded systems

Power efficiency is one of the most important constraints in the design of embedded systems since such systems are generally driven by batteries with limited energy budget or restricted power supply. In every embedded system, there are one or more processor cores to run the software and interact with the other hardware components of the system. The power consumption of the processor core(s) has an important impact on the total power dissipated in the system. Hence, the processor power optimization is crucial in satisfying the power consumption constraints, and developing low-power embedded systems. A key aspect of research in processor power optimization and management is “power estimation”. Having a fast and accurate method for processor power estimation at design time helps the designer to explore a large space of design possibilities, to make the optimal choices for developing a power efficient processor. Likewise, understanding the processor power dissipation behaviour of a specific software/application is the key for choosing appropriate algorithms in order to write power efficient software. Simulation-based methods for measuring the processor power achieve very high accuracy, but are available only late in the design process, and are often quite slow. Therefore, the need has arisen for faster, higher-level power prediction methods that allow the system designer to explore many alternatives for developing powerefficient hardware and software. The aim of this thesis is to present fast and high-level power models for the prediction of processor power consumption. Power predictability in this work is achieved in two ways: first, using a design method to develop power predictable circuits; second, analysing the power of the functions in the code which repeat during execution, then building the power model based on average number of repetitions. In the first case, a design method called Asynchronous Charge Sharing Logic (ACSL) is used to implement the Arithmetic Logic Unit (ALU) for the 8051 microcontroller. The ACSL circuits are power predictable due to the independency of their power consumption to the input data. Based on this property, a fast prediction method is presented to estimate the power of ALU by analysing the software program, and extracting the number of ALU-related instructions. This method achieves less than 1% error in power estimation and more than 100 times speedup in comparison to conventional simulation-based methods. In the second case, an average-case processor energy model is developed for the Insertion sort algorithm based on the number of comparisons that take place in the execution of the algorithm. The average number of comparisons is calculated using a high level methodology called MOdular Quantitative Analysis (MOQA). The parameters of the energy model are measured for the LEON3 processor core, but the model is general and can be used for any processor. The model has been validated through the power measurement experiments, and offers high accuracy and orders of magnitude speedup over the simulation-based method.

I) Improving low photocurrent of pseudorotaxane based solar cell II) Synthesis and characterization of new Fe(0) cyclopentadienone complexes

Next to conventional solar panels that harvest direct sunlight, p-type dye-sensitized solar cells (DSSCs) have been developed, which are able to harvest diffuse sunlight. Due to unwanted charge recombination events p-type DSSCs exhibit low power conversion efficiencies (PCEs). Previous research has shown that dye-redox mediator (RM) interactions can prevent these recombination events, resulting in higher PCEs. It is unknown how the nature of dye-RM interactions affects the PCEs of pseudorotaxane-based solar cells. In this research this correlation is investigated by comparing one macrocycle, the 3-NDI, in combination with the three dyes that contains a recognition sites. 2D-DOSY-NMR experiments have been conducted to evaluate the diffusion constants (LogD) of the three couple. The research project has been stopped due to the coronavirus pandemic. The continuation of this thesis would have been to synthesize a dye on the basis of the data obtained from the diffusion tests and attempt the construction of a solar cell to then evaluate its effectiveness. During my training period I synthetized new Fe(0) cyclopentadienone compounds bearing a N-Heterocyclic Carbene ligand. The aim of the thesis was to achieve water solubility by modifications of the cyclopentadienone ligand. These new complexes have been modified using a sulfonation reaction, replacing an hydroxyl with a sulfate group, on the alkyl backbone of the cyclopentadienone ligand. All the complexes were characterized with IR, ESI-MS and NMR spectroscopy, and a new Fe(0) cyclopentadienone complex, involved as an intermediate, was obtained as a single crystal and was characterized also with X-Ray spectroscopy.

Optimization and development of low environmental impact propulsion systems

The aim of the Ph.D. research project was to explore Dual Fuel combustion and hybridization. Natural gas-diesel Dual Fuel combustion was experimentally investigated on a 4-Stroke, 2.8 L, turbocharged, light-duty Diesel engine, considering four operating points in the range between low to medium-high loads at 3000 rpm. Then, a numerical analysis was carried out using a customized version of the KIVA-3V code, in order to optimize the diesel injection strategy of the highest investigated load. A second KIVA-3V model was used to analyse the interchangeability between natural gas and biogas on an intermediate operating point. Since natural gas-diesel Dual Fuel combustion suffers from poor combustion efficiency at low loads, the effects of hydrogen enriched natural gas on Dual Fuel combustion were investigated using a validated Ansys Forte model, followed by an optimization of the diesel injection strategy and a sensitivity analysis to the swirl ratio, on the lowest investigated load. Since one of the main issues of Low Temperature Combustion engines is the low power density, 2-Stroke engines, thanks to the double frequency compared to 4-Stroke engines, may be more suitable to operate in Dual Fuel mode. Therefore, the application of gasoline-diesel Dual Fuel combustion to a modern 2-Stroke Diesel engine was analysed, starting from the investigation of gasoline injection and mixture formation. As far as hybridization is concerned, a MATLAB-Simulink model was built to compare a conventional (combustion) and a parallel-hybrid powertrain applied to a Formula SAE race car.