Optical Microring Resonators based on ion-implanted LiNbO3 ridge waveguides

The growing interest for Integrated Optics for sensing, telecommunications and even electronics is driving research to find solutions to the new challenges issued by a more and more fast, connected and smart world. This thesis deals with the design, the fabrication and the characterisation of the first prototypes of Microring Resonators realised using ion implanted Lithium Niobate (LiNbO3) ridge waveguides. Optical Resonator is one among the most important devices for all tasks described above. LiNbO3 is the substrate commonly used to fabricate optical modulators thanks to its electro-optic characteristics. Since it is produced in high quantity, good quality and large wafers its price is low compared to other electro-optic substrate. We propose to use ion implantation as fabrication technology because in the other way standard optical waveguides realised in LiNbO3 by Proton Exchange (PE) or metal diffusion do not allow small bending radii, which are necessary to keep the circuit footprint small. We will show in fact that this approach allows to fabricate waveguides on Lithium Niobate that are better than PE or metal diffused waveguides as it allows smaller size devices and tailoring of the refractive index profile controlling the implantation parameters. Moreover, we will show that the ridge technology based on enhanced etching rate via ion implantation produces a waveguide with roughness lower than a dry etched one. Finally it has been assessed a complete technological process for fabrication of Microring Resonator devices in Lithium Niobate by ion implantation and the first prototypes have been produced.

A simple voltage/mass index increases the suspicion of amyloidotic cardiomyopathy: an electrocardiographic and echocardiographic study of 767 patients with increased left ventricular wall thickness due to different causes

Background-Amyloidotic cardiomyopathy (AC) can mimic true left ventricular hypertrophy (LVH), including hypertrophic cardiomyopathy (HCM) and hypertensive heart disease (HHD). We assessed the diagnostic value of combined electrocardiographic/echocardiographic indexes to identify AC among patients with increased echocardiographic LV wall thickness due to either different etiologies of amyloidosis or HCM or HHD. Method-First, we studied 469 consecutive patients: 262 with biopsy/genetically proven AC (with either AL or transthyretin (TTR)-related amyloidosis); 106 with HCM; 101 with HHD. We compared the diagnostic performance of: low QRS voltage, symmetric LVH, low QRS voltage plus interventricular septal thickness >1.98 cm, Sokolow index divided by the cross-sectional area of LV wall, Sokolow index divided by body surface area indexed LV mass (LVMI), Sokolow index divided by LV wall thickness, Sokolow index divided by (LV wall/height^2.7); peripheral QRS score divided by LVMI, Peripheral QRS score divided by LV wall thickness, Peripheral QRS score divided by LV wall thickness indexed to height^2.7, total QRS score divided by LVMI, total QRS score divided by LV wall thickness; total QRS score divided by (LV wall/height^2.7). We tested each criterion, separately in males and females, in the following settings: AC vs. HCM+HHD; AC vs. HCM; AL vs. HCM+HHD; AL vs. HCM; TTR vs. HCM+HHD; TTR vs. HCM. Results-Low QRS voltage showed high specificity but low sensitivity for the identification of AC. All the combined indexes had a higher diagnostic accuracy, being total QRS score divided by LV wall thickness or by LVMI associated with the best performances and the largest areas under the ROC curve. These results were validated in 298 consecutive patients with AC, HCM or HHD. Conclusions-In patients with increased LV wall thickness, a combined ECG/ echocardiogram analysis provides accurate indexes to non-invasively identify AC. Total QRS score divided by LVMI or LV wall thickness offers the best diagnostic performance.

Urban air quality: new high-resolution modeling approaches and forecasting tools for citizens

Air pollution is one of the greatest health risks in the world. At the same time, the strong correlation with climate change, as well as with Urban Heat Island and Heat Waves, make more intense the effects of all these phenomena. A good air quality and high levels of thermal comfort are the big goals to be reached in urban areas in coming years. Air quality forecast help decision makers to improve air quality and public health strategies, mitigating the occurrence of acute air pollution episodes. Air quality forecasting approaches combine an ensemble of models to provide forecasts from global to regional air pollution and downscaling for selected countries and regions. The development of models dedicated to urban air quality issues requires a good set of data regarding the urban morphology and building material characteristics. Only few examples of air quality forecast system at urban scale exist in the literature and often they are limited to selected cities. This thesis develops by setting up a methodology for the development of a forecasting tool. The forecasting tool can be adapted to all cities and uses a new parametrization for vegetated areas. The parametrization method, based on aerodynamic parameters, produce the urban spatially varying roughness. At the core of the forecasting tool there is a dispersion model (urban scale) used in forecasting mode, and the meteorological and background concentration forecasts provided by two regional numerical weather forecasting models. The tool produces the 1-day spatial forecast of NO2, PM10, O3 concentration, the air temperature, the air humidity and BLQ-Air index values. The tool is automatized to run every day, the maps produced are displayed on the e-Globus platform, updated every day. The results obtained indicate that the forecasting output were in good agreement with the observed measurements.

Wireless Power Link Design for Both High-Power Inductive Coupling and Smart Metasurfaces Exploitation

As future technologies are going to be autonomous under the umbrella of the Internet of things (IoT) we can expect WPT to be the solution for intelligent devices. WPT has many industrial and medical applications both in the near-field and far-field domains. Considering the impact of WPT, this thesis is an attempt to design and realize both near-field and far-field WPT solutions for different application scenarios. A 27 MHz high frequency inductive wireless power link has been designed together with the Class-E switching inverter to compensate for the efficiency loss because of the varying weak coupling between transmitter and receiver because of their mutual misalignment. Then a system of three coils was introduced for SWIPT. The outer coil for WPT and the inner two coils were designed to fulfil the purpose of communication and testing, operating at frequencies different from the WPT coil. In addition to that, a trapping filter technique has also been adopted to ensure the EM isolation of the coils. Moreover, a split ring resonator-based dual polarization converter has been designed with good efficiency over a wide frequency range. The gap or cuts have been introduced in the adjacent sides of the square ring to make it a dual-polarization converter. The converter is also stable over a wide range of incident angles. Furthermore, a meta-element based intelligent surface has been designed to work in the reflection mode at 5 GHz. In this research activity, interdigital capacitors (IDCs) instead of ICs are introduced and a thin layer of the HfZrO between substrate and meta elements is placed whose response can be tuned and controlled with the applied voltage to achieve IRS.

Design and testing of innovative, artificial intelligence-based techniques to model and control the combustion process and to reduce the Co2 emissions in modern, high-performance, gasoline direct injection engines

This work deals with the development of calibration procedures and control systems to improve the performance and efficiency of modern spark ignition turbocharged engines. The algorithms developed are used to optimize and manage the spark advance and the air-to-fuel ratio to control the knock and the exhaust gas temperature at the turbine inlet. The described work falls within the activity that the research group started in the previous years with the industrial partner Ferrari S.p.a. . The first chapter deals with the development of a control-oriented engine simulator based on a neural network approach, with which the main combustion indexes can be simulated. The second chapter deals with the development of a procedure to calibrate offline the spark advance and the air-to-fuel ratio to run the engine under knock-limited conditions and with the maximum admissible exhaust gas temperature at the turbine inlet. This procedure is then converted into a model-based control system and validated with a Software in the Loop approach using the engine simulator developed in the first chapter. Finally, it is implemented in a rapid control prototyping hardware to manage the combustion in steady-state and transient operating conditions at the test bench. The third chapter deals with the study of an innovative and cheap sensor for the in-cylinder pressure measurement, which is a piezoelectric washer that can be installed between the spark plug and the engine head. The signal generated by this kind of sensor is studied, developing a specific algorithm to adjust the value of the knock index in real-time. Finally, with the engine simulator developed in the first chapter, it is demonstrated that the innovative sensor can be coupled with the control system described in the second chapter and that the performance obtained could be the same reachable with the standard in-cylinder pressure sensors.