Development and Validation of a Model-Based Combustion Controller for Water Injection Management

This manuscript reports the overall development of a Ph.D. research project during the “Mechanics and advanced engineering sciences” course at the Department of Industrial Engineering of the University of Bologna. The project is focused on the development of a combustion control system for an innovative Spark Ignited engine layout. In details, the controller is oriented to manage a prototypal engine equipped with a Port Water Injection system. The water injection technology allows an increment of combustion efficiency due to the knock mitigation effect that permits to keep the combustion phasing closer to the optimal position with respect to the traditional layout. At the beginning of the project, the effects and the possible benefits achievable by water injection have been investigated by a focused experimental campaign. Then the data obtained by combustion analysis have been processed to design a control-oriented combustion model. The model identifies the correlation between Spark Advance, combustion phasing and injected water mass, and two different strategies are presented, both based on an analytic and semi-empirical approach and therefore compatible with a real-time application. The model has been implemented in a combustion controller that manages water injection to reach the best achievable combustion efficiency while keeping knock levels under a pre-established threshold. Three different versions of the algorithm are described in detail. This controller has been designed and pre-calibrated in a software-in-the-loop environment and later an experimental validation has been performed with a rapid control prototyping approach to highlight the performance of the system on real set-up. To further make the strategy implementable on an onboard application, an estimation algorithm of combustion phasing, necessary for the controller, has been developed during the last phase of the PhD Course, based on accelerometric signals.

Development of Mass Spectrometry-based analytical tools for characterization of bioconjugate vaccines in E. coli

Antigen design is generally driven by the need to obtain enhanced stability,efficiency and safety in vaccines.Unfortunately,the antigen modification is rarely proceeded in parallel with analytical tools development characterization.The analytical tools set up is required during steps of vaccine manufacturing pipeline,for vaccine production modifications,improvements or regulatory requirements.Despite the relevance of bioconjugate vaccines,robust and consistent analytical tools to evaluate the extent of carrier glycosylation are missing.Bioconjugation is a glycoengineering technology aimed to produce N-glycoprotein in vivo in E.coli cells,based on the PglB-dependent system by C. jejuni,applied for production of several glycoconjugate vaccines.This applicability is due to glycocompetent E. coli ability to produce site-selective glycosylated protein used,after few purification steps, as vaccines able to elicit both humoral and cell-mediate immune-response.Here, S.aureus Hla bioconjugated with CP5 was used to perform rational analytical-driven design of the glycosylation sites for the glycosylation extent quantification by Mass Spectrometry.The aim of the study was to develop a MS-based approach to quantify the glycosylation extent for in-process monitoring of bioconjugate production and for final product characterization.The three designed consensus sequences differ for a single amino-acid residue and fulfill the prerequisites for engineered bioconjugate more appropriate from an analytical perspective.We aimed to achieve an optimal MS detectability of the peptide carrying the consensus sequences,complying with the well-characterized requirements for N-glycosylation by PglB.Hla carrier isoforms,bearing these consensus sequences allowed a recovery of about 20 ng/μg of periplasmic protein glycosylated at 40%.The SRM-MS here developed was successfully applied to evaluate the differential site occupancy when carrier protein present two glycosites.The glycosylation extent in each glycosite was determined and the difference in the isoforms were influenced either by the overall source of protein produced and by the position of glycosite insertion.The analytical driven design of the bioconjugated antigen and the development of accurate,precise and robust analytical method allowed to finely characterize the vaccine.

New bio-based polymers: from synthesis to characterization

The environmental problems caused by human activity are one of the main themes of debate of the last Century. As regard plastics, the use of non-renewable sources together with the accumulation of waste in natural habitats are causing serious pollution problems. For this reason, a continuously growing interest is recorded around sustainable materials, potential candidate for the replacement of traditional recalcitrant plastics. Promising results have been obtained with biopolymers, in particular with the class of biopolyesters. Their potential biodegradability and biobased nature is particularly interesting mainly for food packaging, where the multilayer systems normally used and the contamination by organic matter create severe recycling limits. In this framework, the present research has been conducted with the aim of synthetizing, modifying and characterizing biopolymers for food packaging application. New bioplastics based on monomers derived from renewable resources were successfully synthetized by two-step melt polycondensation and chain extension reaction following the “Green chemistry” principles. Moreover, well-known biopolyesters have been modified by blending or copolymerization, both resulting effective techniques to ad hoc tune the polymer final characteristics. The materials obtained have been processed and characterized from the chemical, structural, thermal and mechanical point of view; more specific characterizations as compostability tests, surface hydrophilicity film evaluation and barrier property measurements were conducted.

Synthesis and characterization of heteroleptic Cu(I) complexes based on quinolin-yl-1,2,3-triazole and pyridin-yl-1,2,3 triazole

The present work is part of a research project that involves the study of new copper based complexes to be employed as photosensitizer in carbon dioxide photoreduction reaction. My research project is focused on the synthesis and characterization of 1,2,3 triazoles with a quinoline or pyridine in the lateral chain, which have been successively utilized to synthesize heteroleptic Cu(I) complexes. Redox potential and photophysic properties have been studied.

Development of new chemical entities to target neuroinflammatory pathways.

Neuroinflammatory pathways are main culprits of neurodegenerative diseases' onset and progression, including Alzheimer’s disease (AD). On this basis, several anti-inflammatory drugs were repurposed in clinical trials. However, they have failed, probably because neuroinflammation is a complex network, still not fully understood. From these evidences, this thesis focused on the design and synthesis of new chemical entities as potential neuroinflammatory drugs or chemical probes. Projects 1 and 2 aimed to multi-target-directed ligand (MTDL) development to target neuroinflammation in AD. Polypharmacology by MTDLs is considered one of the most promising strategies to face the multifactorial nature of neurodegenerative diseases. Particularly, Project 1 took inspiration from a cromolyn-ibuprofen drug combination polypharmacological approach, which was recently investigated in AD clinical trials. Based on that, two cromolyn-(S)-ibuprofen codrug series were designed and synthesized. Parent drugs were combined via linking or fusing strategies in 1:2 or 1:1 ratio, by means of hydrolyzable bonds. Project 2 started from a still ongoing AD clinical trial on investigational drug neflamapimod. It is a selective inhibitor of p38α-MAPK, a kinase strictly involved in neuroinflammatory pathways. On the other side, rasagiline, an anti-Parkinson drug, was also repurposed as AD treatment. Indeed, rasagiline’s propargylamine fragment demonstrated to be responsible not only for the MAO-B selective inhibition, but also for the neuroprotective activity. Thus, to synergistically combine these two effects into single-molecules, a small set of neflamapimod-rasagiline hybrids was developed. In the end BMX, a poorly investigated kinase, which seems to be involved in pro-inflammatory mediator production, was explored for the development of new chemical probes. High-quality chemical probes are a powerful tool in target validation and starting points for the development of new drug candidates. Thus, Project 3 focused on the design and synthesis of two series of optimized BMX covalent inhibitors as selective chemical probes.

Noises: a Nuisance and a Resource. Development of New Decomposition Methods of Noisy Data

Noise is constant presence in measurements. Its origin is related to the microscopic properties of matter. Since the seminal work of Brown in 1828, the study of stochastic processes has gained an increasing interest with the development of new mathematical and analytical tools. In the last decades, the central role that noise plays in chemical and physiological processes has become recognized. The dual role of noise as nuisance/resource pushes towards the development of new decomposition techniques that divide a signal into its deterministic and stochastic components. In this thesis I show how methods based on Singular Spectrum Analysis have the right properties to fulfil the previously mentioned requirement. During my work I applied SSA to different signals of interest in chemistry: I developed a novel iterative procedure for the denoising of powder X-ray diffractograms; I “denoised” bi-dimensional images from experiments of electrochemiluminescence imaging of micro-beads obtaining new insight on ECL mechanism. I also used Principal Component Analysis to investigate the relationship between brain electrophysiological signals and voice emission.

Development of a Computer-Based methodology for tolerance selection and optimization applied to the automotive sector

The design optimization of industrial products has always been an essential activity to improve product quality while reducing time-to-market and production costs. Although cost management is very complex and comprises all phases of the product life cycle, the control of geometrical and dimensional variations, known as Dimensional Management (DM), allows compliance with product and process requirements. Hence, the tolerance-cost optimization becomes the main practice to provide an effective application of Design for Tolerancing (DfT) and Design to Cost (DtC) approaches by enabling a connection between product tolerances and associated manufacturing costs. However, despite the growing interest in this topic, a profitable application in the industry of these techniques is hampered by their complexity: the definition of a systematic framework is the key element to improving design optimization, enhancing the concurrent use of Computer-Aided tools and Model-Based Definition (MBD) practices. The present doctorate research aims to define and develop an integrated methodology for product/process design optimization, to better exploit the new capabilities of advanced simulations and tools. By implementing predictive models and multi-disciplinary optimization, a Computer-Aided Integrated framework for tolerance-cost optimization has been proposed to allow the integration of DfT and DtC approaches and their direct application for the design of automotive components. Several case studies have been considered, with the final application of the integrated framework on a high-performance V12 engine assembly, to achieve both functional targets and cost reduction. From a scientific point of view, the proposed methodology provides an improvement for the tolerance-cost optimization of industrial components. The integration of theoretical approaches and Computer-Aided tools allows to analyse the influence of tolerances on both product performance and manufacturing costs. The case studies proved the suitability of the methodology for its application in the industrial field, providing the identification of further areas for improvement and refinement.

A glassful of graphene: graphene-based materials for drinking water remediation

Modern world suffers from an intense water crisis. Emerging contaminants represent one of the most concerning elements of this issue. Substances, molecules, ions, and microorganisms take part in this vast and variegated class of pollutants, which main characteristic is to be highly resistant to traditional water purification technologies. An intense international research effort is being carried out in order to find new and innovative solutions to this problem, and graphene-based materials are one of the most promising options. Graphene oxide (GO) is a nanostructured material where domains populated by oxygenated groups alternate with interconnected areas of sp2 hybridized carbon atoms, on the surface of a one-atom thick nanosheets. GO can adsorb a great number of molecules and ions on its surface, thanks to the variety of different interactions that it can express, such as hydrogen bonding, p-p stacking, and electrostatic and hydrophobic interaction. These characteristics, added to the high superficial area, make it an optimal material for the development of innovative materials for drinking water remediation. The main concern in the use of GO in this field is to avoid secondary contaminations (i.e. GO itself must not become a pollutant). This issue can be faced through the immobilization of GO onto polymeric substrates, thus developing composite materials. The use of micro/ultrafiltration polymeric hollow fibers as substrates allows the design of adsorptive membranes, meaning devices that can perform filtration and adsorption simultaneously. In this thesis, two strategies for the development of adsorptive membranes were investigated: a core-shell strategy, where hollow fibers are coated with GO, and a coextrusion strategy, where GO is embedded in the polymeric matrix of the fibers. The so-obtained devices were exploited for both fundamental studies (i.e. molecular and ionic behaviour in between GO nanosheets) and real applications (the coextruded material is now at TRL 9).

PCM-based in-memory computing: architectures, circuits and applications

Analog In-memory Computing (AIMC) has been proposed in the context of Beyond Von Neumann architectures as a valid strategy to reduce internal data transfers energy consumption and latency, and to improve compute efficiency. The aim of AIMC is to perform computations within the memory unit, typically leveraging the physical features of memory devices. Among resistive Non-volatile Memories (NVMs), Phase-change Memory (PCM) has become a promising technology due to its intrinsic capability to store multilevel data. Hence, PCM technology is currently investigated to enhance the possibilities and the applications of AIMC. This thesis aims at exploring the potential of new PCM-based architectures as in-memory computational accelerators. In a first step, a preliminar experimental characterization of PCM devices has been carried out in an AIMC perspective. PCM cells non-idealities, such as time-drift, noise, and non-linearity have been studied to develop a dedicated multilevel programming algorithm. Measurement-based simulations have been then employed to evaluate the feasibility of PCM-based operations in the fields of Deep Neural Networks (DNNs) and Structural Health Monitoring (SHM). Moreover, a first testchip has been designed and tested to evaluate the hardware implementation of Multiply-and-Accumulate (MAC) operations employing PCM cells. This prototype experimentally demonstrates the possibility to reach a 95% MAC accuracy with a circuit-level compensation of cells time drift and non-linearity. Finally, empirical circuit behavior models have been included in simulations to assess the use of this technology in specific DNN applications, and to enhance the potentiality of this innovative computation approach.

Design, synthesis and photovoltaic properties of some thiophene-based conjugated polymers for organic solar cells

The current issue of the resource of energy combined with the tendency to give a green footprint to our lifestyle have prompted the research to focus the attention on alternative sources with great strides in the optimization of polymeric photovoltaic devices. The research work described in this dissertation consists in the study of different semiconducting π-conjugated materials based on polythiophenes (Chapter I). In detail, the GRIM polymerization was deepened defining the synthetic conditions to obtain regioregular poly(3-alkylthiophene) (Chapter II). Since the use of symmetrical monomers functionalized with oxygen atom(s) allows to adopt easy synthesis leading to performing materials, disubstituted poly(3,4-dialkoxythiophene)s were successfully prepared, characterized and tested as photoactive materials in solar cells (Chapter III). A “green” resource of energy should be employed through sustainable devices and, for this purpose, the research work was continued on the synthesis of thiophene derivatives soluble in eco-friendly solvents. To make this possible, the photoactive layer was completely tailored starting from the electron-acceptor material. A fullerene derivative soluble in alcohols was successfully synthetized and adopted for the realization of the new devices (Chapter IV). New water/alcohol soluble electron-donor materials with different functional groups were prepared and their properties were compared (Chapter V). Once found the best ionic functional group, a new double-cable material was synthetized optimizing the surface area between the different materials (Chapter VI). Finally, other water/alcohol soluble materials were synthetized, characterized and used as cathode interlayers in eco-friendly devices (Chapter VII). In this work, all prepared materials were characterized by spectroscopy analyses, gel permeation chromatography and thermal analyses. Cyclic voltammetry, X-ray diffraction, atomic force microscopy and external quantum efficiency were used to investigate some peculiar aspects.

Study of genes involved in her2-positive breast cancer progression for identification of new therapeutic targets

HER2 overexpression is observed in 20-30% of invasive breast carcinomas and it is correlated with poor prognosis. Although targeted therapies have revolutionized the treatment of HER2-positive breast cancer, a high number of patients presented primary or acquired resistance to monoclonal antibodies and tyrosine kinase inhibitors. Tumor heterogenicity, epithelial to mesenchymal transition (EMT) and cancer stem cells are key factors in target therapy resistance and tumor progression. The aim of this project was to discover alternative therapeutic strategies to over-come tumor resistance by harnessing immune system and looking for new targetable molecules. The results reported introduce a virus-like particles-based vaccine against HER2 as promising therapeutic approach to treat HER2-positive tumors. The high and persistent anti-HER2 antibody titers elicited by the vaccine significantly inhibited tumor growth and metastases onset. Furthermore, the polyclonal response induced by the vaccine also inhibited human HER2-positive breast cancer cells resistant to trastuzumab in vitro, suggesting its efficacy also on trastuzumab resistant tumors. To identify new therapeutic targets to treat progressed breast cancer, we took advantage from a dynamic model of HER2 expression obtained in our laboratory, in which HER2 loss and cancer progression were associated with the acquisition of EMT and stemness features. Targeting EMT-involved molecules, such as PDGFR-β, or the induction of epithelial markers, like E-cadherin, proved to be successful strategy to impair HER2-negative tumor growth. Density alterations, which might be induced by anti-HER2 target therapies, in cell culture condition of a cell line with a labile HER2 expression, caused HER2 loss probably as consequence of more aggressive subpopulations which prevail over the others. These subpopulations showed an increased EMT and stemness profile, confirming that targeting EMT-involved molecules or antigen expressed by cancer stem cells together with anti-HER2 target therapies is a valid strategy to inhibit HER2-positive cells and simultaneously prevent selection of more aggressive clone.

Monitoring of New Psychoactive Substances in the hair of patients with a history of addiction. Evaluation of the public health impact.

Introduction. The term New Psychoactive Substances (NPS) encompasses a broad category of drugs which have become available on the market in recent years and whose illicit use for recreational purposes has recently exploded. The analysis of NPS usually requires mass spectrometry based techniques. The aim of our study was to define the preva-lence of NPS consumption in patients with a history of drug addiction followed by Public Services for Pathological Addictions, with the purpose of highlighting the effective presence of NPS within the area of Bologna and evaluating their association with classical drugs of abuse (DOA). Materials and methods. Sustained by literature, a multi-analyte UHPLC-MS/MS method for the identification of 127 NPS (phenethylamines, arylcyclohexylamines, synthetic opioids, tryptamines, synthetic cannabinoids, synthetic cathinones, designer benzodiazepines) and 15 classic drugs of abuse (DOA) in hair samples was developed and validated according to International Guidelines [112]. Samples pretreatment consisted of washing steps and overnight incubation at 45°C in an acid mixture of methanol and water. After cooling, supernatant were injected into the chromatographic system coupled with a tandem mass spectrometry detector. Results. Successful validation was achieved for almost all of the compounds. The method met all the required technical parameters. LOQ was set from 4 to 80 pg/mg The developed method was applied to 107 cases (85 males and 22 females) of clinical interest. Out of 85 hair samples resulting positive to classical drugs of abuse, NPS were found in twelve (8 male and 4 female). Conclusion. The present methodology represents an easy, low cost, wide-panel method for the de-tection of 127 NPS and 15 DOA in hair samples. Such multi-analyte methods facilitates the study of the prevalence of drugs abused that will enable the competent control authorities to obtain evi-dence-based reports regarding the critical spread of the threat represented by NPS.