Theoretical and experimental studies of gold catalysts for glucose oxidation

The glucaric acid (GLA) has been identified as a “top value-added chemical from biomass” that can be employed for many uses; for instance, it could be a precursor of adipic acid, a monomer of Nylon-6,6. GLA can be synthetized by the oxidation of glucose (GLU), passing through the intermediate gluconic acid (GLO). In recent years, a new process has been sought to obtain GLA in an economic and environmental sustainable way, in order to replace the current use of HNO3 as a stoichiometric oxidant, or electrocatalysis and biochemical synthesis, which show several disadvantages. Thereby, this work is focused on the study of catalysts based on gold nanoparticles supported on activated carbon for the oxidation reaction of GLU to GLA using O2 as an oxidant agent and NaOH as base. The sol-immobilization method leads us to obtain small and well dispersed nanoparticles, characterized by UV-Vis, XRD and TEM techniques. Repeating the reaction on different batches of catalyst, both the synthesis and the reaction were confirmed to be reproducible. The effect of the reaction time feeding GLO as reagent was studied: the results show that the conversion of GLO increases as the reaction time increases; however, the yields of GLA and others increase up to 1 hour, and then they remain constant. In order to obtain information on the catalytic mechanism at the atomistic level, a computational study based on density functional theory and atomistic modeling of the gold nano-catalyst were performed. Highly symmetric (icosahedral and cubo-octahedral) and distorted Au55 nanoparticles have been optimized along with Au(111) and Au(100) surfaces. Distorted structures were found to be more stable than symmetrical ones due to relativistic effects. On these various models the adsorptions of various species involved in the catalysis have been studied, including OH- species, GLU and GLO. The study carried out aims to provide a method for approaching to the study of nanoparticellary catalytic systems.

Development of novel multi-substituted apatite nanophases with advanced functionalities for bone regeneration

In the field of bone substitutes is highly researched an innovative material able to fill gaps with high mechanical performances and able to stimulate cell response, permitting the complete restoration of the bone portion. In this respect, the synthesis of new bioactive materials able to mimic the compositional, morphological and mechanical features of bone is considered as the elective approach for effective tissue regeneration. Hydroxyapatite (HA) is the main component of the inorganic part of bone. Additionally ionic substitution can be performed in the apatite lattice producing different effects, depending from the selected ions. Magnesium, in substitution of calcium, and carbonate, in substitution of phosphate, extensively present in the biological bones, are able to improve properties naturally present in the apatitic phase, (i.e. biomimicry, solubility e osteoinductive properties). Other ions can be used to give new useful properties, like antiresorptive or antimicrobial properties, to the apatitic phase. This thesis focused on the development of hydroxyapatite nanophases with multiple ionic substitutions including gallium, or zinc ions, in association with magnesium and carbonate, with the purpose to provide double synergistic functionality as osteogenic and antibacterial biomaterial. Were developed bioactive materials based on Sr-substituted hydroxyapatite in the form of sintered targets. The obtained targets were treated with Pulsed Plasma Deposition (PED) resulting in the deposition of thin film coatings able to improve the roughness and wettability of PEEK, enhancing its osteointegrability. Were investigated heterogeneous gas-solid reactions, addressed to the biomorphic transformations of natural 3D porous structures into bone scaffolds with biomimetic composition and hierarchical organization, for application in load-bearing sites. The kinetics of the different reactions of the process were optimized to achieve complete and controlled phase transformation, maintaining the original 3-D morphology. Massive porous scaffolds made of ion-substituted hydroxyapatite and bone-mimicking structure were developed and tested in 3-D cell culture models.

Design and Off-design modelling of advanced Power-to-Gas energy storage systems

Power-to-Gas storage systems have the potential to address grid-stability issues that arise when an increasing share of power is generated from sources that have a highly variable output. Although the proof-of-concept of these has been promising, the behaviour of the processes in off-design conditions is not easily predictable. The primary aim of this PhD project was to evaluate the performance of an original Power-to-Gas system, made up of innovative components. To achieve this, a numerical model has been developed to simulate the characteristics and the behaviour of the several components when the whole system is coupled with a renewable source. The developed model has been applied to a large variety of scenarios, evaluating the performance of the considered process and exploiting a limited amount of experimental data. The model has been then used to compare different Power-to-Gas concepts, in a real scenario of functioning. Several goals have been achieved. In the concept phase, the possibility to thermally integrate the high temperature components has been demonstrated. Then, the parameters that affect the energy performance of a Power-to-Gas system coupled with a renewable source have been identified, providing general recommendations on the design of hybrid systems; these parameters are: 1) the ratio between the storage system size and the renewable generator size; 2) the type of coupled renewable source; 3) the related production profile. Finally, from the results of the comparative analysis, it is highlighted that configurations with a highly oversized renewable source with respect to the storage system show the maximum achievable profit.

Advanced voxel-based CAD modelling for FSI simulations for automotive structures design

Additive Manufacturing (AM) is nowadays considered an important alternative to traditional manufacturing processes. AM technology shows several advantages in literature as design flexibility, and its use increases in automotive, aerospace and biomedical applications. As a systematic literature review suggests, AM is sometimes coupled with voxelization, mainly for representation and simulation purposes. Voxelization can be defined as a volumetric representation technique based on the model’s discretization with hexahedral elements, as occurs with pixels in the 2D image. Voxels are used to simplify geometric representation, store intricated details of the interior and speed-up geometric and algebraic manipulation. Compared to boundary representation used in common CAD software, voxel’s inherent advantages are magnified in specific applications such as lattice or topologically structures for visualization or simulation purposes. Those structures can only be manufactured with AM employment due to their complex topology. After an accurate review of the existent literature, this project aims to exploit the potential of the voxelization algorithm to develop optimized Design for Additive Manufacturing (DfAM) tools. The final aim is to manipulate and support mechanical simulations of lightweight and optimized structures that should be ready to be manufactured with AM with particular attention to automotive applications. A voxel-based methodology is developed for efficient structural simulation of lattice structures. Moreover, thanks to an optimized smoothing algorithm specific for voxel-based geometries, a topological optimized and voxelized structure can be transformed into a surface triangulated mesh file ready for the AM process. Moreover, a modified panel code is developed for simple CFD simulations using the voxels as a discretization unit to understand the fluid-dynamics performances of industrial components for preliminary aerodynamic performance evaluation. The developed design tools and methodologies perfectly fit the automotive industry’s needs to accelerate and increase the efficiency of the design workflow from the conceptual idea to the final product.

Development of advanced methods for the simulation of the reacting mixture formation in internal combustion engines with the use of machine learning algorithms

Besides increasing the share of electric and hybrid vehicles, in order to comply with more stringent environmental protection limitations, in the mid-term the auto industry must improve the efficiency of the internal combustion engine and the well to wheel efficiency of the employed fuel. To achieve this target, a deeper knowledge of the phenomena that influence the mixture formation and the chemical reactions involving new synthetic fuel components is mandatory, but complex and time intensive to perform purely by experimentation. Therefore, numerical simulations play an important role in this development process, but their use can be effective only if they can be considered accurate enough to capture these variations. The most relevant models necessary for the simulation of the reacting mixture formation and successive chemical reactions have been investigated in the present work, with a critical approach, in order to provide instruments to define the most suitable approaches also in the industrial context, which is limited by time constraints and budget evaluations. To overcome these limitations, new methodologies have been developed to conjugate detailed and simplified modelling techniques for the phenomena involving chemical reactions and mixture formation in non-traditional conditions (e.g. water injection, biofuels etc.). Thanks to the large use of machine learning and deep learning algorithms, several applications have been revised or implemented, with the target of reducing the computing time of some traditional tasks by orders of magnitude. Finally, a complete workflow leveraging these new models has been defined and used for evaluating the effects of different surrogate formulations of the same experimental fuel on a proof-of-concept GDI engine model.

Development of Advanced Combustions using Cylinder Pressure Signal

Zero-carbon powertrains development has become one of the main challenges for automotive industries around the world. Following this guideline, several approaches such as powertrain electrification, advanced combustions, and hydrogen internal combustion engines have been aimed to achieve the goal. Low Temperature Combustions, characterized by a simultaneous reduction of fuel consumption and emissions, represent one of the most studied solutions moving towards a sustainable mobility. Previous research demonstrate that Gasoline partially premixed Compression Ignition combustion is one of the most promising LTC. Mainly characterized by the high-pressure direct-injection of gasoline and the spontaneous ignition of the premixed air-fuel mixture, GCI combustion has shown a good potential to achieve the high thermal efficiency and low pollutants in compression ignited engines required by future emission regulations. Despite its potential, GCI combustion might suffer from low combustion controllability and stability, because gasoline spontaneous ignition is significantly affected by slight variations of the local in-cylinder thermal conditions. Therefore, to properly control GCI combustion assuring the maximum performance, a deep knowledge of the combustion process, i.e., gasoline auto-ignition and the effect of the control parameters on the combustion and pollutants, is mandatory. This PhD dissertation focuses on the study of GCI combustion in a light-duty compression ignited engine. Starting from a standard 1.3L diesel engine, this work describes the activities made moving toward the full conversion of the engine. A preliminary study of the GCI combustion was conducted in a “Single-Cylinder” engine configuration highlighting combustion characteristics and dependencies on the control parameters. Then, the full engine conversion was performed, and a wide experimental campaign allowed to confirm the benefits of this advanced combustion methodologies in terms of pollutants and thermal efficiency. The analysis of the in-cylinder pressure signal allowed to study in depth the GCI combustion and develop control-oriented models aimed to improve the combustion stability.

Development of advanced analytical methodologies for Alzheimer’s disease drug discovery

Advanced analytical methodologies were developed to characterize new potential active MTDLs on isolated targets involved in the first stages of Alzheimer’s disease (AD). In addition, the methods investigated drug-protein bindings and evaluated protein-protein interactions involved in the neurodegeneration. A high-throughput luminescent assay allowed the study of the first in class GSK-3β/ HDAC dual inhibitors towards the enzyme GSK-3β. The method was able to identify an innovative disease-modifying agent with an activity in the micromolar range both on GSK-3β, HDAC1 and HDAC6. Then, the same assay reliably and quickly selected true positive hit compounds among natural Amaryllidaceae alkaloids tested against GSK-3β. Hence, given the central role of the amyloid pathway in the multifactorial nature of AD, a multi-methodological approach based on mass spectrometry (MS), circular dichroism spectroscopy (CD) and ThT assay was applied to characterize the potential interaction of CO releasing molecules (CORMs) with Aβ1-42 peptide. The comprehensive method provided reliable information on the different steps of the fibrillation process and regarding CORMs mechanism of action. Therefore, the optimal CORM-3/Aβ1−42 ratio in terms of inhibitory effect was identified by mass spectrometry. CD analysis confirmed the stabilizing effect of CORM-3 on the Aβ1−42 peptide soluble form and the ThT Fluorescent Analysis ensured that the entire fibrillation process was delayed. Then the amyloid aggregation process was studied in view of a possible correlation with AD lipid brain alterations. Therefore, SH-SY5Y cells were treated with increasing concentration of Aß1-42 at different times and the samples were analysed by a RP-UHPLC system coupled with a high-resolution quadrupole TOF mass spectrometer in comprehensive data-independent SWATH acquisition mode. Each lipid class profiling in SH-SY5Y cells treated with Aß1-42 was compared to the one obtained from the untreated. The approach underlined some peculiar lipid alterations, suitable as biomarkers, that might be correlated to Aß1-42 different aggregation species.

Characterization of pyrolysis and oxidation processes of biomaterials, biomasses and biofuels

The urgent need for alternative solutions mitigating the impacts of human activities on the environment has strongly opened new challenges and opportunities in view of the energy transition. Indeed, the automotive industry is going through a revolutionary moment in its quest to reduce its carbon footprint, with biofuels being one of the viable alternatives. The use of different classes of biofuels as fuel additives/standalone components has attracted the attention of many researchers. Despite their beneficial effects, biofuel’s combustion can also result in the production of undesirable pollutants, requiring complete characterization of the phenomena occurring during their production and consumption. Industrial scale-up of biomass conversion is challenging owing to the complexity of its chemistry and transport phenomena involved in the process. In this view, the role of solid-phase and gas-phase chemistry is paramount. Thus, this study is devoted to detailed analysis of physical-chemical phenomena characterizing biomass pyrolysis and biofuel oxidation. The pyrolysis mechanism has been represented by 20 reactions whereas, the gas-phase kinetic models; manually upgraded model (KiBo_MU) and automated model (KiBo_AG), comprises 141 species and 453 reactions, and 631 species and 28329 reactions, respectively. The accuracy of the kinetic models was tested against experimental data and the models captured experimental trends very well. While the development and validation of detailed kinetic mechanisms is the main deliverable of this project, the realized procedure integrating schematic classifications with methodologies for the identification of common decomposition pathways and intermediates represents an additional source of novelty. Besides, the fundamentally oriented nature of the adopted method allows the identification of most relevant reactions and species under the operating conditions different industrial applications, paving the way for reduced kinetic mechanisms. Ultimately, the resulting detailed mechanisms can be used to integrate with more complex fluid dynamics model to accurately reproduce the behavior of real systems and reactors.

Chemical looping reforming from methane to syngas: investigation on CeO2 oxygen carrier lifetime and optimal process times

Emissions of CO2 are constantly growing since the beginning of industrial era. Interruption of the production of major emitters sectors (energy and agriculture) is not a viable way and reducing all the emission through carbon capture and storage (CCS) is not economically viable and little publicly accepted, therefore, it becomes fundamentals to take actions like retrofitting already developed infrastructure employing cleanest resources, modify the actual processes limiting the emissions, and reduce the emissions already present through direct air capture. The present thesis will deeply discuss the aspects mentioned in regard to syngas and hydrogen production since they have a central role in the market of energy and chemicals. Among the strategies discussed, greater emphasis is given to the application of looping technologies and to direct air capture processes, as they have been the main point of this work. Particularly, chemical looping methane reforming to syngas was studied with Aspen Plus thermodynamic simulations, thermogravimetric analysis characterization (TGA) and testing in a fixed bed reactor. The process was studied cyclically exploiting the redox properties of a Ce-based oxide oxygen carrier synthetized with a simple forming procedure. The two steps of the looping cycles were studied isothermally at 900 °C and 950° C with a mixture of 10 %CH4 in N2 and of 3% O2 in N2, for carrier reduction and oxidation, respectively. During the stay abroad, in collaboration with the EHT of Zurich, a CO2 capture process in presence of amine solid sorbents was investigated, studying the difference in the performance achievable with the use of contactors of different geometry. The process was studied at two concentrations (382 ppm CO2 in N2 and 5.62% CO2 in N2) and at different flow rates, to understand the dynamics of the adsorption process and to define the mass transfer limiting step.

Advanced statistical models for the segregation, identification and measurement of coexisting sound sources

Long-term monitoring of acoustical environments is gaining popularity thanks to the relevant amount of scientific and engineering insights that it provides. The increasing interest is due to the constant growth of storage capacity and computational power to process large amounts of data. In this perspective, machine learning (ML) provides a broad family of data-driven statistical techniques to deal with large databases. Nowadays, the conventional praxis of sound level meter measurements limits the global description of a sound scene to an energetic point of view. The equivalent continuous level Leq represents the main metric to define an acoustic environment, indeed. Finer analyses involve the use of statistical levels. However, acoustic percentiles are based on temporal assumptions, which are not always reliable. A statistical approach, based on the study of the occurrences of sound pressure levels, would bring a different perspective to the analysis of long-term monitoring. Depicting a sound scene through the most probable sound pressure level, rather than portions of energy, brought more specific information about the activity carried out during the measurements. The statistical mode of the occurrences can capture typical behaviors of specific kinds of sound sources. The present work aims to propose an ML-based method to identify, separate and measure coexisting sound sources in real-world scenarios. It is based on long-term monitoring and is addressed to acousticians focused on the analysis of environmental noise in manifold contexts. The presented method is based on clustering analysis. Two algorithms, Gaussian Mixture Model and K-means clustering, represent the main core of a process to investigate different active spaces monitored through sound level meters. The procedure has been applied in two different contexts: university lecture halls and offices. The proposed method shows robust and reliable results in describing the acoustic scenario and it could represent an important analytical tool for acousticians.

Electrochemical oxidation of Kraft and Dealkaline lignin to produce value-added chemicals on Nickel electrocatalysts

One of the most important scientific and environmental issues is reducing global dependence on fossil sources and one of the solutions is to use biomass as feedstock. In particular, the use of lignocellulosic biomass to obtain molecules with considerable commercial importance is gaining more and more interest. Lignin, the most recalcitrant part of lignocellulosic biomass, is a valuable source of sustainable and renewable aromatic molecules, currently produced from petrochemical processes. Vanillin, one of the most important aromatic aldehydes on an industrial level, can be obtained through catalytic lignin oxidation. An alternative to the conventional catalytic oxidation process is the electro-catalytic process, which can be carried out at ambient temperature and pressure, using water as solvent, and it can be considered as a renewable energy storage. In this thesis, the electrocatalytic oxidation of Kraft and Dealkaline lignin in NaOH was investigated over Ni foam catalysts. The effect of the reaction parameters (i.e. time, applied potential, lignin concentration, NaOH concentration, and temperature) on the yields of vanillin and other valuable products was evaluated. After the screening of the reaction conditions, a systematic study of the contribution of the homogeneous reaction (lignin depolymerization due to the basic solvent) to the yield of the product was accomplished. Finally, considering the obtained results, an alternative reaction procedure was proposed.

Impact Of Chemical Changes On The Sensory Characteristics Of Coffee Beans During Storage.

Sensory changes during the storage of coffee beans occur mainly due to lipid oxidation and are responsible for the loss of commercial value. This work aimed to verify how sensory changes of natural coffee and pulped natural coffee are related to the oxidative processes during 15 months of storage. During this period, changes in the content of free fatty acids (1.4-3.8 mg/g oil), TBARS values (8.8-10.2 nmol MDA/g), and carbonyl groups (2.6-3.5 nmol/mg of protein) occurred. The intensity of rested coffee flavour in the coffee brew increased (2.1-6.7) and 5-caffeoylquinic acid concentration decreased (5.2-4.6g/100g). Losses were also observed in seed viability, colour of the beans and cellular structure. All the results of the chemical analyses are coherent with the oxidative process that occurred in the grains during storage. Therefore, oxidation would be also responsible for the loss of cellular structure, seed viability and sensory changes.

Electrochemical Oxidation Of Landfill Leachate In A Flow Reactor: Optimization Using Response Surface Methodology.

Response surface methodology based on Box-Behnken (BBD) design was successfully applied to the optimization in the operating conditions of the electrochemical oxidation of sanitary landfill leachate aimed for making this method feasible for scale up. Landfill leachate was treated in continuous batch-recirculation system, where a dimensional stable anode (DSA(©)) coated with Ti/TiO2 and RuO2 film oxide were used. The effects of three variables, current density (milliampere per square centimeter), time of treatment (minutes), and supporting electrolyte dosage (moles per liter) upon the total organic carbon removal were evaluated. Optimized conditions were obtained for the highest desirability at 244.11 mA/cm(2), 41.78 min, and 0.07 mol/L of NaCl and 242.84 mA/cm(2), 37.07 min, and 0.07 mol/L of Na2SO4. Under the optimal conditions, 54.99 % of chemical oxygen demand (COD) and 71.07 ammonia nitrogen (NH3-N) removal was achieved with NaCl and 45.50 of COD and 62.13 NH3-N with Na2SO4. A new kinetic model predicted obtained from the relation between BBD and the kinetic model was suggested.

[meanings Of The Sickening Process For Patients With Systemic Lupus Erythematosus: A Review Of The Literature.]

Systemic lupus erythematosus is an autoimmune disease that causes many psychological repercussions that have been studied through qualitative research. These are considered relevant, since they reveal the amplitude experienced by patients. Given this importance, this study aims to map the qualitative production in this theme, derived from studies of experiences of adult patients of both genders and that had used as a tool a semi-structured interview and/or field observations, and had made use of a sampling by a saturation criterion to determine the number of participants in each study. The survey was conducted in Pubmed, Lilacs, Psycinfo e Cochrane databases, searching productions in English and Portuguese idioms published between January 2005 and June 2012. The 19 revised papers that have dealt with patients in the acute phase of the disease showed themes that were categorized into eight topics that contemplated the experienced process at various stages, from the onset of the disease, extending through the knowledge of the diagnosis and the understanding of the manifestations of the disease, drug treatment and general care, evolution and prognosis. The collected papers also point to the difficulty of understanding, of the patients, on what consists the remission phase, revealing also that this is a clinical stage underexplored by psychological studies.

Correlation Between Vascular Endothelial Growth Factor Expression And Presence Of Lymph Node Metastasis In Advanced Squamous Cell Carcinoma Of The Larynx.

Squamous cell carcinoma is the most common neoplasm of the larynx, and its evolution depends on tumor staging. Vascular endothelial growth factor is a marker of angiogenesis, and its expression may be related to increased tumor aggressiveness, as evidenced by the presence of cervical lymphatic metastases. To evaluate the expression of the vascular endothelial growth factor marker in non-glottic advanced squamous cell carcinoma of the larynx (T3/T4) and correlate it with the presence of cervical lymph node metastases. Retrospective clinical study and immunohistochemical analysis of vascular endothelial growth factor through the German scale of immunoreactivity in products of non-glottic squamous cell carcinomas. This study analyzed 15 cases of advanced non-glottic laryngeal tumors (T3/T4), four of which exhibited cervical lymphatic metastases. There was no correlation between vascular endothelial growth factor expression and the presence of cervical metastases. Although vascular endothelial growth factor was expressed in a few cases, there was no correlation with the spread of cervical lymph metastases.