Design of biobased additives for tuning the properties of biopolymers

This work mainly arises from the necessity to support the rapid introduction of different biobased polymers that the industrial sector has been facing lately. Indeed, while considerable efforts are being made to find environmentally and economically sustainable materials, less attention is paid to their need to be properly compounded to fulfil increasingly rigorous technical and quality requirements. Therefore, there is a strong demand for the development of a novel generation of compatible additives able to improve the properties of biobased polymers while respecting sustainability. With this in mind, a new class of biobased plasticizers is herein proposed. Five different ketal-diesters were selectively synthesized starting from levulinic acid, a promising renewable chemical platform. These molecules were added to poly(vinyl chloride) as model polymer to test their plasticizing effectiveness. Complete morphological, thermal and viscoelastic characterizations showed a clear correlation between the structural features of the ketal-esters and the properties of the material. In addition, no significant leaching was found in both hydrophilic and lipophilic environments. Importantly, the proposed ketal-diesters performed comparably and, in some cases, even better than commercial plasticizers. The same molecules were then added to bacterial poly(3-hydroxybutyrate), a semicrystalline polyester characterized by poor thermal and mechanical properties. Morphology assessments showed no phase separation and the plasticizing effectiveness was confirmed by thermal and viscoelastic analyses, while leaching tests showed low extraction values. Readily usable fractions with controlled structure and tailored properties were obtained from highly heterogeneous industrial grade Kraft lignin. These fractions were then added to poly(vinyl alcohol). Promising preliminary results in terms of compatibility were achieved, with thermograms showing only one glass transition temperature. Finally, a fully biobased glycerol-trilevulinate was successfully synthesized by means of a mild and solvent-free route. Its plasticizing effectiveness was evaluated on poly(vinyl chloride), showing a significant decrease of the glass transition temperature of the material.

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.

Design and characterization of automated agricultural vehicle systems

Nowadays, technological advancements have brought industry and research towards the automation of various processes. Automation brings a reduction in costs and an improvement in product quality. For this reason, companies are pushing research to investigate new technologies. The agriculture industry has always looked towards automating various processes, from product processing to storage. In the last years, the automation of harvest and cultivation phases also has become attractive, pushed by the advancement of autonomous driving. Nevertheless, ADAS systems are not enough. Merging different technologies will be the solution to obtain total automation of agriculture processes. For example, sensors that estimate products' physical and chemical properties can be used to evaluate the maturation level of fruit. Therefore, the fusion of these technologies has a key role in industrial process automation. In this dissertation, ADAS systems and sensors for precision agriculture will be both treated. Several measurement procedures for characterizing commercial 3D LiDARs will be proposed and tested to cope with the growing need for comparison tools. Axial errors and transversal errors have been investigated. Moreover, a measurement method and setup for evaluating the fog effect on 3D LiDARs will be proposed. Each presented measurement procedure has been tested. The obtained results highlight the versatility and the goodness of the proposed approaches. Regarding the precision agriculture sensors, a measurement approach for the Moisture Content and density estimation of crop directly on the field is presented. The approach regards the employment of a Near Infrared spectrometer jointly with Partial Least Square statistical analysis. The approach and the model will be described together with a first laboratory prototype used to evaluate the NIRS approach. Finally, a prototype for on the field analysis is realized and tested. The test results are promising, evidencing that the proposed approach is suitable for Moisture Content and density estimation.

Test vector generation for the phase II ATLAS event filter trigger upgrade

In the near future, the LHC experiments will continue to be upgraded as the LHC luminosity will increase from the design 1034 to 7.5 × 1034, with the HL-LHC project, to reach 3000 × f b−1 of accumulated statistics. After the end of a period of data collection, CERN will face a long shutdown to improve overall performance by upgrading the experiments and implementing more advanced technologies and infrastructures. In particular, ATLAS will upgrade parts of the detector, the trigger, and the data acquisition system. It will also implement new strategies and algorithms for processing and transferring the data to the final storage. This PhD thesis presents a study of a new pattern recognition algorithm to be used in the trigger system, which is a software designed to provide the information necessary to select physical events from background data. The idea is to use the well-known Hough Transform mathematical formula as an algorithm for detecting particle trajectories. The effectiveness of the algorithm has already been validated in the past, independently of particle physics applications, to detect generic shapes in images. Here, a software emulation tool is proposed for the hardware implementation of the Hough Transform, to reconstruct the tracks in the ATLAS Trigger and Data Acquisition system. Until now, it has never been implemented on electronics in particle physics experiments, and as a hardware implementation it would provide overall latency benefits. A comparison between the simulated data and the physical system was performed on a Xilinx UltraScale+ FPGA device.

Design, synthesis and biological evaluation of dual inhibitors of GSK-3B and Fyn kinases for the study of inflammatory pathways in neurodegenerative diseases

Neuroinflammation represents a key hallmark of neurodegenerative diseases and is the result of a complex network of signaling cascades within microglial cells. A positive feedback loop exists between inflammation, microglia activation and protein misfolding processes, that, together with oxidative stress and excitotoxicity, lead to neuronal degeneration. Therefore, targeting this vicious cycle can be beneficial for mitigating neurodegeneration and cognitive decline in central nervous system disorders. At molecular level, GSK-3B and Fyn kinases play a crucial role in microglia activation and their deregulation has been associated to many neurodegenerative diseases. Thus, we envisioned their combined targeting as an effective approach to disrupt this toxic loop. Specifically in this project, a hit compound, based on a 7-azaindole-3-aminothiazole structure, was first identified in a virtual screening campaign, and displayed a weak dual inhibitory activity on GSK-3B and Fyn, unbalanced towards the former. Then, in a commitment to uncover the structural features required for modulating the activity on the two targets, we systematically manipulated this compound by inserting various substitution patterns in different positions. The most potent compounds obtained were advanced to deeper investigations to test their ability of tackling the inflammatory burden also in cellular systems and to unveil their binding modes within the catalytic pocket. The new class of molecules synthesized emerged as a valuable tool to deepen our understanding of the complex network governing the inflammatory events in neurodegenerative disorders.

Navigation design and flight dynamics operations of the ArgoMoon cis-lunar CubeSat.

On November 16, 2022, the NASA’s Space Launch System (SLS) has been launched for the first time in the context of Artemis-1 mission where, together with the Orion Multi-Purpose Crew Vehicle, a set of 10 CubeSats have been delivered into a translunar trajectory. Among the small satellites deployed during Artemis-1 there is ArgoMoon, a 6U CubeSat built by the Italian company Argotec and coordinated by Italian Space Agency (ASI). The primary goal of ArgoMoon is to capture images of the Interim Cryogenic Propulsion Stage. The ArgoMoon trajectory has been designed as a highly elliptical geocentric orbit, with several encounters with the Moon. In order to successfully fly ArgoMoon along the designed cis-lunar trajectory, a ground-based navigation system has been developed exploiting the guidance techniques also used for regular deep space missions. The navigation process is subdivided into Orbit Determi- nation (OD) and a Flight Path Control (FPC), and it is designed to follow the reference trajectory, prevent impacts with the Earth and the Moon, intensively test the navigation techniques, and guarantee the spacecraft disposal at the end of the mission. The work done in this thesis has accomplished the navigation of ArgoMoon, covering all aspects of the project life, from pre-launch design and analysis to actual operations. Firstly, the designed navigation process and the pre-mission assessment of its performance will be presented. Then, the results of the ArgoMoon navigation operations performed after the launch in November 2022 will be described in detail by discussing the main encountered challenges and the adopted solutions. The results of the operations confirmed the robustness of the designed navigation which allowed to accurately estimate the trajectory of ArgoMoon despite a series of complex events.

Development and characterization of cutting-edge equipment for EMC measurements and advanced power line filter design

This Doctoral Thesis aims at studying, developing, and characterizing cutting edge equipment for EMC measurements and proposing innovative and advanced power line filter design techniques. This document summarizes a three-year work, is strictly industry oriented and relies on EMC standards and regulations. It contains the main results, findings, and effort with the purpose of bringing innovative contributions at the scientific community. Conducted emissions interferences are usually suppressed with power line filters. These filters are composed by common mode chokes, X capacitors and Y capacitors in order to mitigate both the differential mode and common mode noise, which compose the overall conducted emissions. However, even at present days, available power line filter design techniques show several disadvantages. First of all, filters are designed to be implemented in ideal 50 Ω systems, condition which is far away from reality. Then, the attenuation introduced by the filter for common or differential mode noise is analyzed independently, without considering the possible mode conversion that can be produced by impedance mismatches, or asymmetries in either the power line filter itself or the equipment under test. Ultimately, the instrumentation used to perform conducted emissions measurement is, in most cases, not adequate. All these factors lead to an inaccurate design, contributing at increasing the size of the filter, making it more expensive and less performant than it should be.