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Methodologies and integrated architecture for advance sensing on next-generation smart battery cells
No full textBatteries are the catalyst for the shift towards sustainable and smart mobility, as well as supplying clean, affordable, and renewable energy sources. To improve the battery performance at level of management and control of the system, new methodologies need to be found to monitor in operando and in situ the batteries' state parameters, thus strengthening safety, reliability, and cycle life of batteries. The vision of this PhD project is to integrate smart functionalities at the cell level and study possible data fusion algorithms to create predictive models of the battery state parameters. In particular, the thesis is focused on the investigation of the Elecrochemical Impedance Spectoscopy (EIS) as diagnosis tool for the online monitoring of the battery. The first step towards this goal is to define the sensing technologies to be integrated in a single battery cell to enable the in operando and in situ measurement of battery physical quantities. EIS can respond to the challenges of shortening the measurement time and reducing the dimensions of the system to be integrated into the battery cell. A novel approach to perform broadband EIS based on a multi-band multisine excitation signal is proposed to optimize the measurement time and signal-to-noise ratio (SNR). The related EIS-based sensing system based on a sigma-delta architecture is developed and tested as impedance demonstrator for a future integration at the cell level. Finally, experimental EIS data of lithium battery cells are collected and evaluated, to demonstrate that the proposed methodologies are suitable for the online battery monitoring
Epigenetic effects of lifestyle in patients affected by gynecological tumors
No full textGynecological cancers are among the most frequent malignancies in women, with over 3.5 million women affected globally. This thesis focuses on endometrial (EC) and ovarian cancers (OC). EC is the sixth most common cancer in women, with obesity being a significant risk factor. Although less common, OC is the most lethal gynecological cancer due to the lack of specific symptoms and early detection biomarkers. Epigenetics investigates gene expression changes that occur without DNA sequence alterations but arise from environmental factors. microRNAs (miRNAs) are non-coding RNA molecules involved in the development of several diseases, including cancer. The aim of the present thesis was to clarify the epigenetic role of lifestyle in gynecological cancers. To achieve this goal, three tasks were planned: Task 1 addressed obesity-related EC, Task 2 explored physical activity’s role in OC, and Task 3 focused on OC organoid models.
In Task 1, tissue and plasma samples from obese and non-obese EC patients, as well as from obese non-cancer women, were analysed to investigate the potential link between obesity and miRNA expression in EC. Results revealed a significant miRNA deregulation in obese EC patients, suggesting that obesity-induced epigenetic changes may contribute to EC development and progression. These findings could help identify new biomarkers for managing obese EC patients.
Task 2 analysed miRNA expression in OC patients who were either enrolled in or not enrolled in a structured physical activity program. Results revealed significant variations in miRNA expression, suggesting that regular exercise may influence the molecular mechanisms underlying tumor biology.
Lastly, Task 3 focused on developing a 3D OC organoid model to support future functional studies based on the previous findings.
This study provides new insights into the epigenetic role of lifestyle in gynecological cancers, with potential implications for the development of personalized therapies based on miRNAs
Development of the GCI combustion through a combined approach with experimental data and three-dimensional CFD simulations
No full textThe future of automotive mobility is increasingly shaped by stringent Homologation Standards, driving the development of Powertrain technologies focused on reducing emissions and improving fuel efficiency. Over the past decades, research has optimized individual components while integrating progressive electrification.
A key aspect of this evolution is enhancing engine-out performance by optimizing combustion physics. Pollutant formation in Compression-Ignited (CI) engines is influenced by local mixture conditions, with high temperatures promoting Particulate Matter (PM) and Nitrogen Oxides (NOx). In Spark-Ignited (SI) engines, throttling and knock limit efficiency. Hybrid combustion regimes, particularly Low-Temperature Combustion (LTC), merge CI and SI benefits, enabling efficient, low-emission operation through controlled auto-ignition.
Among LTC strategies, Gasoline Compression Ignition (GCI) has been extensively studied in this thesis. GCI utilizes multiple late-cycle injections of gasoline-like fuel in a high-compression ratio engine, generating a stratified charge that auto-ignites depending on local mixture conditions. This work presents a methodology combining experimental data and Computational Fluid Dynamics (CFD) simulations to analyze GCI combustion, structured as follows:
- Engine CAD modeling: A 3D scanner captured the geometry to build a reliable moving mesh validated against test bench data.
- Spray development analysis: Experimental tests in a constant-volume chamber informed CFD setup to simulate transient fuel dynamics accurately.
- Droplet-wall interaction study: Tests captured the Leidenfrost effect, refining CFD modeling of fuel impingement and its impact on auto-ignition.
- Combustion model validation: A sector mesh accelerated simulations, validated against extensive engine operating conditions.
- GCI optimization: CFD simulations assessed injection strategies to enhance efficiency and reduce emissions, extending the engine's operational range.
The findings contribute to improving CFD predictability, offering a robust tool for future Powertrains and injection systems
Phasor measurement unit implementation across embedded, edge, and cloud environments for modern grid monitoring systems
No full textPhasor Measurement Units (PMUs) play a critical role in ensuring reliable, real-time monitoring of electrical power grids, but traditional PMU designs often face scalability challenges due to high costs and specialized hardware requirements. This dissertation addresses these limitations by investigating three distinct implementation approaches: a low-cost embedded PMU, a virtualized PMU operating on edge devices, and a novel cloudbased PMU concept. The first approach focuses on designing a cost-effective, stand-alone PMU using embedded technology, achieving high measurement precision while reducing production costs. The second approach leverages edge computing to virtualize PMU functions, implementing a virtual PMU on an edge device to reduce reliance on dedicated hardware. The third approach extends PMU capabilities to a cloud environment, where synchrophasor estimation is performed within cloud infrastructure, offering potential for improved scalability and accessibility in large-scale grid monitoring. Each implementation is evaluated to determine its feasibility, performance, and suitability for real-world grid applications. Through these three approaches, this research demonstrates that PMUs can be adapted and optimized for a wide range of system architectures, from low-cost embedded devices to scalable cloud infrastructures, paving the way for more accessible grid monitoring solutions
Neuroinflammation and neurological condition: a translation path toward regenerative medicine
No full textNeuroinflammation is a complex pathological condition characterized by a wide range of cellular and molecular events involving peripheral inflammatory and immune cells, and various central nervous system (CNS) cells. We focused on its critical aspects in different conditions, such as traumatic injuries (spinal cord injury-SCI), immune-mediated inflammatory-demyelinating disorders (multiple sclerosis-MS), and neurodegenerative diseases. In this thesis work, we approached this complex issue trying to dissect specific aspects and questions in the path supporting the use of cellular therapies to control neuroinflammation. Firstly, we investigated how inflammation alters lipid microdomains and membrane fluidity in red blood cells and key cell types relevant to MS, including macrophages, neurons and oligodendrocyte precursor cells. Results show altered lipid compositions in these cells during inflammation, suggest that peripheral cell membrane lipids could serve as potential biomarkers. We also investigated the impact of different inflammatory stimuli on endothelial-to-mesenchymal transition (EndMT) in several endothelial cells, including brain endothelial cells. We found that inflammatory stimuli induce EndMT through the TGFβ pathway and it’s irreversible in our experimental condition. Subsequently, we investigated the variability of mesenchymal stromal cells (MSCs) used in cell therapies by characterizing the secretome of adipose-derived MSCs (adMSCs). We found substantial inter-donor variability in neuroprotective factors, which influenced the protective effect of adMSCs on neural-derived stem cells, suggesting the opportunity to introduce exclusion criteria among donors based on biological properties of MSCs. Lastly, we investigated the impact of altered extracellular matrix (ECM) environments in SCI on stem cell over time, revealing that ECM from the SCI acute phase significantly hinders cell viability and differentiation, whereas ECM from the chronic phase supports better stem cell differentiation and viability. The study emphasizes the importance of timing for effective cell-based therapies in SCI. Together, these studies contribute to the understanding of the multifaceted role of neuroinflammation in CNS pathology
Designing low-power AI solutions for the edge: from CPUs to specialized accelerators
No full textThis thesis addresses the challenge of deploying Artificial Intelligence (AI) algorithms at the edge—a critical issue in the evolving Internet of Things (IoT) landscape, where applications like smart cities, autonomous drones, and augmented reality demand near-sensor processing under strict power, performance, and storage constraints. With traditional hardware scaling methods reaching their limits, this work advances architectural innovations on both the host CPU and AI accelerator in IoT System-on-Chips. On the host side, the first contribution introduces a technique to mitigate load-use hazards in the CVA6 CPU—a 6-stage, single-issue, open-source RISC-V processor. This redesign increases maximum frequency by 4% while reducing area and power consumption by 2.5%. The backend improvements yield an average 6.5% gain in IPC, with peaks of 29%, leading to overall performance boosts of up to 35% and energy efficiency improvements averaging 6.5% at 1 GHz. The second host contribution enhances the dual-issue superscalar configuration of the CVA6 core by implementing a renaming scheme to eliminate write-after-write hazards, a low-overhead ALU-ALU forwarding mechanism, and an improved branch predictor. With an 11% increase in area, this extension achieves a 45% IPC increase. On the accelerator side, two works target low-power embedded environments. The first presents Dustin, a fully flexible accelerator in 65nm TSMC technology featuring a 16-core RISC-V compute cluster. Dustin incorporates mixed-precision support via hardware-based packing/unpacking and a novel Vector Lockstep Execution Mode (VLEM) that allows switching from a MIMD to a SIMD-like model, yielding up to 40% power savings. The final contribution explores heterogeneous acceleration through Analog In-Memory Computing. By integrating two specialized accelerators with a flexible compute cluster, this approach achieves performance and efficiency improvements of up to 10× over core-only implementation, with nearly 1 TOPS in performance, and 6.4 TOPS/W in efficiency, underscoring the promise of heterogeneous architectures for future AI devices
Biomechanical and clinical evidence of vertebral metastases to predict the risk of fracture
No full textCancer is becoming a chronic disease increasing the numbers of cancer survivors which are at risk of developing metastases. Spine is among the most common sites affected by bone metastases. The current patients’ stratification to assess the risk of spinal instability is only partially reliable, leading most patients to be under or over-treated. In order to understand how the metastases are responsible for the altered microstructural and mechanical properties of the metastatic vertebrae, this PhD project focused on a comprehensive experimental biomechanical characterization of the human metastatic spine.
This aim was reached investigating the microarchitectural alteration in metastatic vertebrae and assessing the contribute of the metastatic lesions and of the adjacent structures (e.g. IVDs) in the mechanical behaviour of the vertebrae. More than 80 human (metastatic/healthy) vertebrae were scanned with clinical and high-resolution imaging, and were biomechanically tested, in different loading conditions, while experimental strain measurements were performed with Digital Volume Correlation (inside the vertebrae) and Digital Image Correlation (on the surface of the vertebrae and of the adjacent intervertebral discs). This work created an unprecedented experimental dataset essential to identify those features associated with the risk of vertebral failure. The results pointed out that the microstructural alterations within metastatic vertebrae affected the mechanical behaviour differently for each metastatic vertebra and also for the adjacent vertebrae. Additionally, the different role played by degenerated/non-degenerated intervertebral discs in driving the vertebral failure was identified.
These findings highlight the need for a more specific clinical stratification system based on digital tools (i.e. Digital Twin, Explainable Artificial Intelligence, mechanistic models). Moreover, the collected data can serve as a benchmark for their initial implementation
Crystal engineering of co-crystals and host-guest systems for environmentally friendly applications: sunscreens stabilization, pollutant sequestering and herbicide reformulation.
No full textSolid state engineered materials have proven to be useful and suitable tools in the quest of new materials. In this thesis different crystalline compounds were synthesized to provide more sustainable products for different applications, as in cosmetics or in agrochemistry, to propose pollutants removal strategy or to obtain materials for electrocatalysis. Therefore, the research projects presented here can be divided into three main topics: (i) sustainable preparation of solid materials of widely used active ingredients aimed at the reduction of their occurrence in the natural environment. The systems studied in this section are cyclodextrins host-guest compounds, obtained via mechanochemical and slurry synthesis. The first chemicals studied are sunscreens inclusion complexes, that proved to have enhanced photostability and desired photoprotection.
The same synthetic methods were applied to obtain inclusion complexes of bentazon, a herbicide often found to leach in groundwaters. The resulting products showed to have desired water solubility properties. The same herbicide was also adsorbed on amorphous calcium phosphate nanoparticles, to obtain a biocompatible formulation of this agrochemical. This herbicide could benefit by the adsorption on nanoparticles for what concerns its kinetic release in different media as well as its photostability.
(ii) Sustainable synthesis of co-crystals based on polycyclic aromatic hydrocarbons, for the proposal of a sequestering method with a resulting material with enhanced properties.
The co-crystallization via mechanochemical means proved that these pollutants can be sequestered via simple solvent-free synthesis and the obtained materials present better photochemical properties when compared to the starting co-formers.
(iii) Crystallization from mild solvents of nanosized materials useful for the application in electrocatalysis.
The study of compounds based on nickel and cobalt metal ions resulted in the obtainment of 2D and 1D coordination polymers. Moreover, solid solutions were obtained. These crystals showed layered structures and, according to preliminary results, they can be exfoliated
Wheat adaptation to climate change in the Mediterranean Basin: retracing the past to predict the future
No full textWheat productivity is alarmingly threatened by climate change in the Mediterranean Basin, where it is mainly cultivated as a rainfed crop and where the latest climatic projections foresee a rise in temperatures and a reduction in precipitation, with important yield losses expected, being drought the main abiotic stress hampering wheat productivity. Assessing and quantifying the alterations in wheat life cycle caused by climate change is thus a key goal, as well as understating the underlying mechanisms of drought resistance. The first part of this thesis is focused on these main topics. A precise quantification of climate change effects on wheat in this area was performed through a case study, coupling phenological, meteorological and grain quality data before and after climate change. Then, accurate and detailed literature search was performed, reviewing the main controversies regarding the reliability of various functional traits to be used as breeding tools for improving wheat drought stress resistance. The second part of this thesis is focused in identifying interesting genetic material to improve wheat drought stress resistance in the Mediterranean Basin, analyzing drought response on a panel of tetraploid wheat accessions in vitro and in vivo as well as in open field trials, chosen in the attempt to represent as much as possible the biodiversity of tetraploid wheat. The third part of this thesis highlights differences in technological, nutritional and nutraceutical quality between modern cultivars and landraces, focusing on lipids, primary metabolites and bioactive compounds. In fact, wheat adaptation to climate change does not only mean to guarantee satisfactory yields in adverse conditions. It also means to provide millions of consumers with a diet-base food crop, with an improved nutraceutical and nutritional quality. Therefore, investigation and selection process for abiotic stress resistance and for improved quality has to go hand in hand
A philological commentary on Plato, Philebus
No full textLa tesi contiene un’edizione critica di Filebo, 31b2–59e5, preceduta da un’Introduzione e da una Nota al Testo. L’Introduzione discute il titolo del dialogo, la sua posizione tetralogica, la data di composizione, l’identità dei personaggi. La Nota al Testo discute i rapporti tra i testimoni primari e contiene un Index testimoniorum. L’edizione è seguita da un commento per lemmi.My thesis is a critical edition of Plato, Phlb. 31b2–59e5, preceded by an Introduction and a Note to the Text. The Introduction discusses the title of the dialogue, its placement in the tetralogical order, its date of composition and the identity of its speakers. In the Note to the Text the relationships between the primary witnesses are discussed and an Index testimoniorum is given.
The edition is followed by a line-by-line commentary