Advanced parametrical modelling of 24 GHz radar sensor IC packaging components

This paper deals with the development of an advanced parametrical modelling concept for packaging components of a 24 GHz radar sensor IC used in automotive driver assistance systems. For fast and efficient design of packages for system-in-package modules (SiP), a simplified model for the description of parasitic electromagnetic effects within the package is desirable, as 3-D field computation becomes inefficient due to the high density of conductive elements of the various signal paths in the package. By using lumped element models for the characterization of the conductive components, a fast indication of the design's signal-quality can be gained, but so far does not offer enough flexibility to cover the whole range of geometric arrangements of signal paths in a contemporary package. This work pursues to meet the challenge of developing a flexible and fast package modelling concept by defining parametric lumped-element models for all basic signal path components, e.g. bond wires, vias, strip lines, bumps and balls. © Author(s) 2011. CC Attribution 3.0 License.

Specification of a smart meter/actuator description mechanism & development of a mobile application

Home Automation holds the potential of realizing cost savings for end users while reducing the carbon footprint of domestic energy consumption. Yet, adoption is still very low. High cost of vendor-supplied home automation systems is a major prohibiting factor. Open source systems such as FHEM, Domoticz, OpenHAB etc. are a cheaper alternative and can drive the adoption of home automation. Moreover, they have the advantage of not being limited to a single vendor or communication technology which gives end users flexibility in the choice of devices to include in their installation. However, interaction with devices having diverse communication technologies can be inconvenient for users thus limiting the utility they derive from it. For application developers, creating applications which interact with the several technologies in the home automation systems is not a consistent process. Hence, there is the need for a common description mechanism that makes interaction smooth for end users and which enables application developers to make home automation applications in a consistent and uniform way. This thesis proposes such a description mechanism within the context of an open source home automation system – FHEM, together with a system concept for its application. A mobile application was developed as a proof of concept of the proposed description mechanism and the results of the implementation are reflected upon.

MEMS SENSOR PLATFORMS FOR IN SITU CHARACTERIZATION OF LI-ION BATTERY ELECTRODES

Lithium-ion batteries provide high energy density while being compact and light-weight and are the most pervasive energy storage technology powering portable electronic devices such as smartphones, laptops, and tablet PCs. Considerable efforts have been made to develop new electrode materials with ever higher capacity, while being able to maintain long cycle life. A key challenge in those efforts has been characterizing and understanding these materials during battery operation. While it is generally accepted that the repeated strain/stress cycles play a role in long-term battery degradation, the detailed mechanisms creating these mechanical effects and the damage they create still remain unclear. Therefore, development of techniques which are capable of capturing in real time the microstructural changes and the associated stress during operation are crucial for unravelling lithium-ion battery degradation mechanisms and further improving lithium-ion battery performance. This dissertation presents the development of two microelectromechanical systems sensor platforms for in situ characterization of stress and microstructural changes in thin film lithium-ion battery electrodes, which can be leveraged as a characterization platform for advancing battery performance. First, a Fabry-Perot microelectromechanical systems sensor based in situ characterization platform is developed which allows simultaneous measurement of microstructural changes using Raman spectroscopy in parallel with qualitative stress changes via optical interferometry. Evolutions in the microstructure creating a Raman shift from 145 cm−1 to 154 cm−1 and stress in the various crystal phases in the LixV2O5 system are observed, including both reversible and irreversible phase transitions. Also, a unique way of controlling electrochemically-driven stress and stress gradient in lithium-ion battery electrodes is demonstrated using the Fabry-Perot microelectromechanical systems sensor integrated with an optical measurement setup. By stacking alternately stressed layers, the average stress in the stacked electrode is greatly reduced by 75% compared to an unmodified electrode. After 2,000 discharge-charge cycles, the stacked electrodes retain only 83% of their maximum capacity while unmodified electrodes retain 91%, illuminating the importance of the stress gradient within the electrode. Second, a buckled membrane microelectromechanical systems sensor is developed to enable in situ characterization of quantitative stress and microstructure evolutions in a V2O5 lithium-ion battery cathode by integrating atomic force microscopy and Raman spectroscopy. Using dual-mode measurements in the voltage range of the voltage range of 2.8V – 3.5V, both the induced stress (~ 40 MPa) and Raman intensity changes due to lithium cycling are observed. Upon lithium insertion, tensile stress in the V2O5 increases gradually until the α- to ε-phase and ε- to δ-phase transitions occur. The Raman intensity change at 148 cm−1 shows that the level of disorder increases during lithium insertion and progressively recovers the V2O5 lattice during lithium extraction. Results are in good agreement with the expected mechanical behavior and disorder change in V2O5, highlighting the potential of microelectromechanical systems as enabling tools for advanced scientific investigations. The work presented here will be eventually utilized for optimization of thin film battery electrode performance by achieving fundamental understanding of how stress and microstructural changes are correlated, which will also provide valuable insight into a battery performance degradation mechanism.

Multi-sensor Cloud and Aerosol Retrieval Simulator and Its Applications

Executing a cloud or aerosol physical properties retrieval algorithm from controlled synthetic data is an important step in retrieval algorithm development. Synthetic data can help answer questions about the sensitivity and performance of the algorithm or aid in determining how an existing retrieval algorithm may perform with a planned sensor. Synthetic data can also help in solving issues that may have surfaced in the retrieval results. Synthetic data become very important when other validation methods, such as field campaigns,are of limited scope. These tend to be of relatively short duration and often are costly. Ground stations have limited spatial coverage whilesynthetic data can cover large spatial and temporal scales and a wide variety of conditions at a low cost. In this work I develop an advanced cloud and aerosol retrieval simulator for the MODIS instrument, also known as Multi-sensor Cloud and Aerosol Retrieval Simulator (MCARS). In a close collaboration with the modeling community I have seamlessly combined the GEOS-5 global climate model with the DISORT radiative transfer code, widely used by the remote sensing community, with the observations from the MODIS instrument to create the simulator. With the MCARS simulator it was then possible to solve the long standing issue with the MODIS aerosol optical depth retrievals that had a low bias for smoke aerosols. MODIS aerosol retrieval did not account for effects of humidity on smoke aerosols. The MCARS simulator also revealed an issue that has not been recognized previously, namely,the value of fine mode fraction could create a linear dependence between retrieved aerosol optical depth and land surface reflectance. MCARS provided the ability to examine aerosol retrievals against “ground truth” for hundreds of thousands of simultaneous samples for an area covered by only three AERONET ground stations. Findings from MCARS are already being used to improve the performance of operational MODIS aerosol properties retrieval algorithms. The modeling community will use the MCARS data to create new parameterizations for aerosol properties as a function of properties of the atmospheric column and gain the ability to correct any assimilated retrieval data that may display similar dependencies in comparisons with ground measurements.

Structural Data Acquisition Using Sensor Network

The development cost of any civil infrastructure is very high; during its life span, the civil structure undergoes a lot of physical loads and environmental effects which damage the structure. Failing to identify this damage at an early stage may result in severe property loss and may become a potential threat to people and the environment. Thus, there is a need to develop effective damage detection techniques to ensure the safety and integrity of the structure. One of the Structural Health Monitoring methods to evaluate a structure is by using statistical analysis. In this study, a civil structure measuring 8 feet in length, 3 feet in diameter, embedded with thermocouple sensors at 4 different levels is analyzed under controlled and variable conditions. With the help of statistical analysis, possible damage to the structure was analyzed. The analysis could detect the structural defects at various levels of the structure.

Radiação Solar: Estudo e criação de plataforma de apoio a conceção de um sensor de radiação solar

Este trabalho introduz a teoria da instrumentação virtual descrevendo os principais componentes desta. É detalhada a implementação de um instrumento virtual e uma base de dados associada que permitem obter uma estimativa de variáveis ambientais para qualquer ponto do globo e qualquer altura do ano. Este instrumento - Environment simulator – permite fornecer dados ambientais necessários a simulação da radiação solar. Para explicar a implementação da plataforma de apoio introduzem-se noções relativas à radiação solar, à relação entre o planeta Terra e o sol. É considerada a radiação solar espectral bem como os principais componentes óticos atmosféricos que com ela interagem. Apresentam-se formulações e aproximações dos coeficientes de extinção e dispersão na atmosfera que levam ao cálculo da radiação solar espectral direta, difusa e global. Por fim, validam-se os resultados através da comparação com valores registados durante a campanha de observações ALEX2014.

Development and experimental validation of a knock induced damage model and real-time implementation of model-based strategies to control knock intensity in boosted gasoline engines

This PhD thesis reports the main activities carried out during the 3 years long “Mechanics and advanced engineering sciences” course, at the Department of Industrial Engineering of the University of Bologna. The research project title is “Development and analysis of high efficiency combustion systems for internal combustion engines” and the main topic is knock, one of the main challenges for boosted gasoline engines. Through experimental campaigns, modelling activity and test bench validation, 4 different aspects have been addressed to tackle the issue. The main path goes towards the definition and calibration of a knock-induced damage model, to be implemented in the on-board control strategy, but also usable for the engine calibration and potentially during the engine design. Ionization current signal capabilities have been investigated to fully replace the pressure sensor, to develop a robust on-board close-loop combustion control strategy, both in knock-free and knock-limited conditions. Water injection is a powerful solution to mitigate knock intensity and exhaust temperature, improving fuel consumption; its capabilities have been modelled and validated at the test bench. Finally, an empiric model is proposed to predict the engine knock response, depending on several operating condition and control parameters, including injected water quantity.

Inertial and magnetic sensors for upper limb kinematics: modeling, calibration, sensor fusion and clinical applications

The primary aim of the research activity presented in this PhD thesis was the development of an innovative hardware and software solution for creating a unique tool for kinematics and electromyographic analysis of the human body in an ecological setting. For this purpose, innovative algorithms have been proposed regarding different aspects of inertial and magnetic data elaboration: magnetometer calibration and magnetic field mapping (Chapter 2), data calibration (Chapter 3) and sensor-fusion algorithm. Topics that may conflict with the confidentiality agreement between University of Bologna and NCS Lab will not be covered in this thesis. After developing and testing the wireless platform, research activities were focused on its clinical validation. The first clinical study aimed to evaluate the intra and interobserver reproducibility in order to evaluate three-dimensional humero-scapulo-thoracic kinematics in an outpatient setting (Chapter 4). A second study aimed to evaluate the effect of Latissimus Dorsi Tendon Transfer on shoulder kinematics and Latissimus Dorsi activation in humerus intra - extra rotations (Chapter 5). Results from both clinical studies have demonstrated the ability of the developed platform to enter into daily clinical practice, providing useful information for patients' rehabilitation.

Hybrid ground-aerial mesh networks for IoT monitoring applications: network design and software platform development

The Internet of Things (IoT) has grown rapidly in recent years, leading to an increased need for efficient and secure communication between connected devices. Wireless Sensor Networks (WSNs) are composed of small, low-power devices that are capable of sensing and exchanging data, and are often used in IoT applications. In addition, Mesh WSNs involve intermediate nodes forwarding data to ensure more robust communication. The integration of Unmanned Aerial Vehicles (UAVs) in Mesh WSNs has emerged as a promising solution for increasing the effectiveness of data collection, as UAVs can act as mobile relays, providing extended communication range and reducing energy consumption. However, the integration of UAVs and Mesh WSNs still poses new challenges, such as the design of efficient control and communication strategies. This thesis explores the networking capabilities of WSNs and investigates how the integration of UAVs can enhance their performance. The research focuses on three main objectives: (1) Ground Wireless Mesh Sensor Networks, (2) Aerial Wireless Mesh Sensor Networks, and (3) Ground/Aerial WMSN integration. For the first objective, we investigate the use of the Bluetooth Mesh standard for IoT monitoring in different environments. The second objective focuses on deploying aerial nodes to maximize data collection effectiveness and QoS of UAV-to-UAV links while maintaining the aerial mesh connectivity. The third objective investigates hybrid WMSN scenarios with air-to-ground communication links. One of the main contribution of the thesis consists in the design and implementation of a software framework called "Uhura", which enables the creation of Hybrid Wireless Mesh Sensor Networks and abstracts and handles multiple M2M communication stacks on both ground and aerial links. The operations of Uhura have been validated through simulations and small-scale testbeds involving ground and aerial devices.

Development of textile wearable chemical sensors

In this elaborate, a textile-based Organic Electrochemical Transistor (OECT) was first developed for the determination of uric acid in wound exudate based on the conductive polymer poly(3,4-ethylenedioxythiophene):polystyrene sulfonate (PEDOT:PSS), which was then coupled to an electrochemically gated textile transistor consisting of a composite of iridium oxide particles and PEDOT:PSS for pH monitoring in wound exudate. In that way a sensor for multiparameter monitoring of wound health status was assembled, including the ability to differentiate between a wet-dry status of the smart bandage by implementing impedance measurements exploiting the OECT architecture. Afterwards, for both wound management as well as generic health status tracking applications, a glass-based calcium sensor was developed employing polymeric ion-selective membranes on a novel architecture inspired by the Wrighton OECT configuration, which was later converted to a Proof-of-Concept textile prototype for wearable applications. Lastly, in collaboration with the King Abdullah University of Science and Technology (KAUST, Thuwal, Saudi Arabia) under the supervision of Prof. Sahika Inal, different types of ion-selective thiophene-based monomers were used to develop ion-selective conductive polymers to detect sodium ion by different methods, involving standard potentiometry and OECT-based approaches. The textile OECTs for uric acid detection performances were optimized by investigating the geometry effect on the instrumental response and the properties of the different textile materials involved in their production, with a special focus on the final application that implies the operativity in flow conditions to simulate the wound environment. The same testing route was followed for the multiparameter sensor and the calcium sensor prototype, with a particular care towards the ion-selective membrane composition and electrode conditioning protocol optimization. The sodium-selective polymer electrosynthesis was optimized in non-aqueous environments and was characterized by means of potentiostatic and potentiodynamic techniques coupled with Quartz Crystal Microbalance and spectrophotometric measurements.

Development and testing of methodologies for the control and diagnosis of innovative combustion systems

In pursuit of aligning with the European Union's ambitious target of achieving a carbon-neutral economy by 2050, researchers, vehicle manufacturers, and original equipment manufacturers have been at the forefront of exploring cutting-edge technologies for internal combustion engines. The introduction of these technologies has significantly increased the effort required to calibrate the models implemented in the engine control units. Consequently the development of tools that reduce costs and the time required during the experimental phases, has become imperative. Additionally, to comply with ever-stricter limits on 〖"CO" 〗_"2" emissions, it is crucial to develop advanced control systems that enhance traditional engine management systems in order to reduce fuel consumption. Furthermore, the introduction of new homologation cycles, such as the real driving emissions cycle, compels manufacturers to bridge the gap between engine operation in laboratory tests and real-world conditions. Within this context, this thesis showcases the performance and cost benefits achievable through the implementation of an auto-adaptive closed-loop control system, leveraging in-cylinder pressure sensors in a heavy-duty diesel engine designed for mining applications. Additionally, the thesis explores the promising prospect of real-time self-adaptive machine learning models, particularly neural networks, to develop an automatic system, using in-cylinder pressure sensors for the precise calibration of the target combustion phase and optimal spark advance in a spark-ignition engines. To facilitate the application of these combustion process feedback-based algorithms in production applications, the thesis discusses the results obtained from the development of a cost-effective sensor for indirect cylinder pressure measurement. Finally, to ensure the quality control of the proposed affordable sensor, the thesis provides a comprehensive account of the design and validation process for a piezoelectric washer test system.

Development of wearable electrochemical sensors for the determination of biological analytes

Wearable biosensors are attracting interest due to their potential to provide continuous, real-time physiological information via dynamic, non-invasive measurements of biochemical markers in biofluids, such as interstitial fluid (ISF). One notable example of their applications is for glycemic monitoring in diabetic patients, which is typically carried out either by direct measurement of blood glucose via finger pricking or by wearable sensors that can continuously monitor glucose in ISF by sampling it from below the skin with a microneedle. In this context, the development of a new and minimally invasive multisensing tattoo-based platform for the monitoring of glucose and other analytes in ISF extracted through reverse iontophoresis in proposed by the GLUCOMFORT project. This elaborate describes the in-vitro development of flexible electrochemical sensors based on inkjet-printed PEDOT:PSS and metal inks that are capable of determining glucose and chloride at biologically relevant concentrations, making them good candidates for application in the GLUCOMFORT platform. In order to make PEDOT:PSS sensitive to glucose at micromolar concentrations, a biocompatible functionalization based on immobilized glucose oxidase and electrodeposited platinum was developed. This functionalization was successfully applied to bulk and flexible amperometric devices, the design of which was also optimized. Using the same strategy, flexible organic electrochemical transistors (OECTs) for glucose sensing were also made and successfully tested. For the sensing of chloride ions, an organic charge-modulated field-effect transistor (OCMFET) featuring a silver/silver chloride modified floating gate electrode was developed and tested.

Ihwg-μnir: A Miniaturised Near-infrared Gas Sensor Based On Substrate-integrated Hollow Waveguides Coupled To A Micro-nir-spectrophotometer.

A miniaturised gas analyser is described and evaluated based on the use of a substrate-integrated hollow waveguide (iHWG) coupled to a microsized near-infrared spectrophotometer comprising a linear variable filter and an array of InGaAs detectors. This gas sensing system was applied to analyse surrogate samples of natural fuel gas containing methane, ethane, propane and butane, quantified by using multivariate regression models based on partial least square (PLS) algorithms and Savitzky-Golay 1(st) derivative data preprocessing. The external validation of the obtained models reveals root mean square errors of prediction of 0.37, 0.36, 0.67 and 0.37% (v/v), for methane, ethane, propane and butane, respectively. The developed sensing system provides particularly rapid response times upon composition changes of the gaseous sample (approximately 2 s) due the minute volume of the iHWG-based measurement cell. The sensing system developed in this study is fully portable with a hand-held sized analyser footprint, and thus ideally suited for field analysis. Last but not least, the obtained results corroborate the potential of NIR-iHWG analysers for monitoring the quality of natural gas and petrochemical gaseous products.

[the Use Of Fish On Buccal Smear To Investigate Mosaicism With A 45,x Cell Line: Study On Healthy Men And Patients With Disorders Of Sex Development].

To verify whether fluorescence in situ hybridization (FISH) of cells from the buccal epithelium could be employed to detect cryptomosaicism with a 45,X lineage in 46,XY patients. Samples of nineteen 46,XY healthy young men and five patients with disorders of sex development (DSD), four 45,X/46,XY and one 46,XY were used. FISH analysis with X and Y specific probes on interphase nuclei from blood lymphocytes and buccal epithelium were analyzed to investigate the proportion of nuclei containing only the signal of the X chromosome. The frequency of nuclei containing only the X signal in the two tissues of healthy men did not differ (p = 0.69). In all patients with DSD this frequency was significantly higher, and there was no difference between the two tissues (p = 0.38), either. Investigation of mosaicism with a 45,X cell line in patients with 46,XY DSD or sterility can be done by FISH directly using cells from the buccal epithelium.

The Influence Of The Environment On The Development Of Thyroid Tumors: A New Appraisal.

Most epidemiological studies concerning differentiated thyroid cancers (DTC) indicate an increasing incidence over the last two decades. This increase might be partially explained by the better access to health services worldwide, but clinicopathological analyses do not fully support this hypothesis, indicating that there are carcinogenetic factors behind this noticeable increasing incidence. Although we have undoubtedly understood the biology and molecular pathways underlying thyroid carcinogenesis in a better way, we have made very little progresses in identifying a risk profile for DTC, and our knowledge of risk factors is very similar to what we knew 30-40 years ago. In addition to ionizing radiation exposure, the most documented and established risk factor for DTC, we also investigated the role of other factors, including eating habits, tobacco smoking, living in a volcanic area, xenobiotics, and viruses, which could be involved in thyroid carcinogenesis, thus, contributing to the increase in DTC incidence rates observed.