Self-healing thermal annealing: surface morphological restructuring control of GaN nanorods

With advances in nanolithography and dry etching, top-down methods of nanostructuring have become a widely used tool for improving the efficiency of optoelectronics. These nano dimensions can offer various benefits to the device performance in terms of light extraction and efficiency, but often at the expense of emission color quality. Broadening of the target emission peak and unwanted yellow luminescence are characteristic defect-related effects due to the ion beam etching damage, particularly for III–N based materials. In this article we focus on GaN based nanorods, showing that through thermal annealing the surface roughness and deformities of the crystal structure can be “self-healed”. Correlative electron microscopy and atomic force microscopy show the change from spherical nanorods to faceted hexagonal structures, revealing the temperature-dependent surface morphology faceting evolution. The faceted nanorods were shown to be strain- and defect-free by cathodoluminescence hyperspectral imaging, micro-Raman, and transmission electron microscopy (TEM). In-situ TEM thermal annealing experiments allowed for real time observation of dislocation movements and surface restructuring observed in ex-situ annealing TEM sampling. This thermal annealing investigation gives new insight into the redistribution path of GaN material and dislocation movement post growth, allowing for improved understanding and in turn advances in optoelectronic device processing of compound semiconductors.

Development, Evaluation and Optimization of Fabrication Processes for Daylight Guiding Systems Based on Micromirror Arrays

In this work, fabrication processes for daylight guiding systems based on micromirror arrays are developed, evaluated and optimized.Two different approaches are used: At first, nanoimprint lithography is used to fabricate large area micromirrors by means of Substrate Conformal Imprint Lithography (SCIL).Secondly,a new lithography technique is developed using a novel bi-layered photomask to fabricate large area micromirror arrays. The experimental results showing a reproducible stable process, high yield, and is consuming less material, time, cost and effort.

Physicochemical complexity in complex chemical systems

Self-replication and compartmentalization are two central properties thought to be essential for minimal life, and understanding how such processes interact in the emergence of complex reaction networks is crucial to exploring the development of complexity in chemistry and biology. Autocatalysis can emerge from multiple different mechanisms such as formation of an initiator, template self-replication and physical autocatalysis (where micelles formed from the reaction product solubilize the reactants, leading to higher local concentrations and therefore higher rates). Amphiphiles are also used in artificial life studies to create protocell models such as micelles, vesicles and oil-in-water droplets, and can increase reaction rates by encapsulation of reactants. So far, no template self-replicator exists which is capable of compartmentalization, or transferring this molecular scale phenomenon to micro or macro-scale assemblies. Here a system is demonstrated where an amphiphilic imine catalyses its own formation by joining a non-polar alkyl tail group with a polar carboxylic acid head group to form a template, which was shown to form reverse micelles by Dynamic Light Scattering (DLS). The kinetics of this system were investigated by 1H NMR spectroscopy, showing clearly that a template self-replication mechanism operates, though there was no evidence that the reverse micelles participated in physical autocatalysis. Active oil droplets, composed from a mixture of insoluble organic compounds in an aqueous sub-phase, can undergo processes such as division, self-propulsion and chemotaxis, and are studied as models for minimal cells, or protocells. Although in most cases the Marangoni effect is responsible for the forces on the droplet, the behaviour of the droplet depends heavily on the exact composition. Though theoretical models are able to calculate the forces on a droplet, to model a mixture of oils on an aqueous surface where compounds from the oil phase are dissolving and diffusing through the aqueous phase is beyond current computational capability. The behaviour of a droplet in an aqueous phase can only be discovered through experiment, though it is determined by the droplet's composition. By using an evolutionary algorithm and a liquid handling robot to conduct droplet experiments and decide which compositions to test next, entirely autonomously, the composition of the droplet becomes a chemical genome capable of evolution. The selection is carried out according to a fitness function, which ranks the formulation based on how well it conforms to the chosen fitness criteria (e.g. movement or division). Over successive generations, significant increases in fitness are achieved, and this increase is higher with more components (i.e. greater complexity). Other chemical processes such as chemiluminescence and gelation were investigated in active oil droplets, demonstrating the possibility of controlling chemical reactions by selective droplet fusion. Potential future applications for this might include combinatorial chemistry, or additional fitness goals for the genetic algorithm. Combining the self-replication and the droplet protocells research, it was demonstrated that the presence of the amphiphilic replicator lowers the interfacial tension between droplets of a reaction mixture in organic solution and the alkaline aqueous phase, causing them to divide. Periodic sampling by a liquid handling robot revealed that the extent of droplet fission increased as the reaction progressed, producing more individual protocells with increased self-replication. This demonstrates coupling of the molecular scale phenomenon of template self-replication to a macroscale physicochemical effect.

Analysis of Dyscalculia Evidences through Artificial Intelligence Systems

Dyscalculia is usually perceived of as a specific learning difficulty for mathematics or, more appropriately, arithmetic. Because definitions and diagnoses of dyscalculia are in their infancy and sometimes are contradictory. However, mathematical learning difficulties are certainly not in their infancy and are very prevalent and often devastating in their impact. Co-occurrence of learning disorders appears to be the rule rather than the exception. Co-occurrence is generally assumed to be a consequence of risk factors that are shared between disorders, for example, working memory. However, it should not be assumed that all dyslexics have problems with mathematics, although the percentage may be very high, or that all dyscalculics have problems with reading and writing. Because mathematics is very developmental, any insecurity or uncertainty in early topics will impact on later topics, hence to need to take intervention back to basics. However, it may be worked out in order to decrease its degree of severity. For example, disMAT, an app developed for android may help children to apply mathematical concepts, without much effort, that is turning in itself, a promising tool to dyscalculia treatment. Thus, this work will focus on the development of a Decision Support System to estimate children evidences of dyscalculia, based on data obtained on-the-fly with disMAT. The computational framework is built on top of a Logic Programming approach to Knowledge Representation and Reasoning, grounded on a Case-based approach to computing, that allows for the handling of incomplete, unknown, or even self-contradictory information.

Peptide-based low molecular weight gelators for the preparation of self-assembled materials

Low molecular weight gelators (LMWGs) based on pseudo-peptides are here studied for the preparation of supramolecular materials. These compounds can self-assemble through non-covalent interactions such as hydrogen bonds and π-π stacking, forming fibres and gels. A wide variety of materials can be prepared starting from these building blocks, which can be tuned and functionalised depending on the application. In this work, derivatives of the three aromatic amino acids L-Phenylalanine, L-Tyrosine and L-DOPA (3,4-dihydroxiphenylalanine) were synthesised and tested as gelators for water or organic solvents. First, the optimal gelating conditions were studied for each compound, varying concentration, solvent and trigger. Then the materials were characterised in terms of mechanical properties and morphology. Water remediation from dye pollution was the first focus of this work. Organogels were studied as absorbent of dyes from contaminated water. Hydrogels functionalised with TiO2 nanoparticles and graphene platelets were proposed as efficient materials for the photo-degradation of dyes. An efficient method for the incorporation of graphene inside hydrogels using the gelator itself as dispersant was proposed. In these materials a high storage modulus coexists with good self-healing and biocompatibility. The incorporation of a mineral phase inside the gel matrix was then investigated, leading to the preparation of composite organic/inorganic materials. In a first study, the growth of calcium carbonate crystals was achieved inside the hydrogel, which preserved its structure after crystal formation. Then the self-assembled fibres made of LMWGs were used for the first time instead of the polymeric ones as reinforcement inside calcium phosphate cements (CPCs) for bone regeneration. Gel-to-crystal transitions occurring with time in a metastable gel were also examined. The formation of organic crystals in gels can be achieved in multicomponent systems, in which a second gelator constitutes the independent gel network. Finally, some compounds unable to gelate were tested as underwater adhesives.

Intelligent Sensor Systems for Structural Health Monitoring Applications

The convergence between the recent developments in sensing technologies, data science, signal processing and advanced modelling has fostered a new paradigm to the Structural Health Monitoring (SHM) of engineered structures, which is the one based on intelligent sensors, i.e., embedded devices capable of stream processing data and/or performing structural inference in a self-contained and near-sensor manner. To efficiently exploit these intelligent sensor units for full-scale structural assessment, a joint effort is required to deal with instrumental aspects related to signal acquisition, conditioning and digitalization, and those pertaining to data management, data analytics and information sharing. In this framework, the main goal of this Thesis is to tackle the multi-faceted nature of the monitoring process, via a full-scale optimization of the hardware and software resources involved by the {SHM} system. The pursuit of this objective has required the investigation of both: i) transversal aspects common to multiple application domains at different abstraction levels (such as knowledge distillation, networking solutions, microsystem {HW} architectures), and ii) the specificities of the monitoring methodologies (vibrations, guided waves, acoustic emission monitoring). The key tools adopted in the proposed monitoring frameworks belong to the embedded signal processing field: namely, graph signal processing, compressed sensing, ARMA System Identification, digital data communication and TinyML.

Fracture toughness characterization of aluminium-epoxy adhesive joints reinforced with electrospun Nylon 6,6 nanofibers

The use of adhesives to join two different substrates is an efficient replacement to classic joining technologies such as welding and soldering. One the one hand adhesion has different advantages over those techniques such as an improved stress distribution and the potential weight reduction of the structure; on the other hand, two of the most important drawbacks are a relatively low fracture toughness and the need of an accurate surface preparation. These two aspects will be accurately analysed in the present work: the use of Nylon nanofibers as reinforcement for the adhesive should increase fracture toughness, while a surface preparation method consisting of mechanical and chemical treatments will be developed. After the specimens are produced, they will be tested in mode I fracture using a DCB (Double Beam Cantilever) test, which allows to measure the fracture toughness during crack propagation. At the end of the test, the surfaces of the adherends will be visually observed and SEM (Scanning Electronic Microscope) analysed in order to evaluate if adhesive or cohesive fracture occurred, and thus if surface treatments has been well developed to allow a better adhesive-aluminium joining.

Power flow forecasting and smart charging for electric vehicle charging systems with photovoltaic integration

An essential role in the global energy transition is attributed to Electric Vehicles (EVs) the energy for EV traction can be generated by renewable energy sources (RES), also at a local level through distributed power plants, such as photovoltaic (PV) systems. However, EV integration with electrical systems might not be straightforward. The intermittent RES, combined with the high and uncontrolled aggregate EV charging, require an evolution toward new planning and paradigms of energy systems. In this context, this work aims to provide a practical solution for EV charging integration in electrical systems with RES. A method for predicting the power required by an EV fleet at the charging hub (CH) is developed in this thesis. The proposed forecasting method considers the main parameters on which charging demand depends. The results of the EV charging forecasting method are deeply analyzed under different scenarios. To reduce the EV load intermittency, methods for managing the charging power of EVs are proposed. The main target was to provide Charging Management Systems (CMS) that modulate EV charging to optimize specific performance indicators such as system self-consumption, peak load reduction, and PV exploitation. Controlling the EV charging power to achieve specific optimization goals is also known as Smart Charging (SC). The proposed techniques are applied to real-world scenarios demonstrating performance improvements in using SC strategies. A viable alternative to maximize integration with intermittent RES generation is the integration of energy storage. Battery Energy Storage Systems (BESS) may be a buffer between peak load and RES production. A sizing algorithm for PV+BESS integration in EV charging hubs is provided. The sizing optimization aims to optimize the system's energy and economic performance. The results provide an overview of the optimal size that the PV+BESS plant should have to improve whole system performance in different scenarios.

Governing the water conservation in the Urmia Lake Basin: addressing macro systems’ fit and micro users’ behavior

To change unadapted water governing systems, and water users’ traditional conducts in line with climate change, understanding of systems’ structures and users’ behaviors is necessary. To this aim, comprehensive and pragmatic research was designed and implemented in the Urmia Lake Basin where due to the severe droughts, and human-made influences, especially through the agricultural development, the lake has been shrunken drastically. To analyze the water governance and conservation issues in the basin, an innovative framework was developed based on mathematical physics concepts and pro-environmental behavior theories. Accordingly, in system level (macro/meso), the problem of fit of the early-shaped water governing system associating with the function of “political-security” and “political-economic” factors in the basin was identified through mean-field models. Furthermore, the effect of a “political-environmental” factor, the Urmia Lake Restoration Program (ULRP), on reforming the system structure and hence its fit was assessed. The analysis results revealed that by revising the provincial boundaries (horizontal alternation) for the entity of Kurdistan province to permit that interact with the headquarter of West Azerbaijan province for its water demand-supply initiatives, the system fit can increase. Also, the constitution of the ULRP (vertical arrangement) not only could increase the structural fit of the water governing system to the basin, but also significantly could enhance the system fit through its water-saving policy. Besides, in individual level (micro), the governing factors of water conservation behavior of the major users/farmers were identified through rational and moral socio-psychological models. In rational approach, incorporating PMT and TPB, the SEM results demonstrated that “Perceived Vulnerability”, “Self-Efficacy”, “Response Efficacy”, “Response Cost”, “Subjective Norms” and “Institutional Trust” significantly affect the water-saving intention/behavior. Likewise, NAM based analysis as a moral approach, uncovered the significant effects of “Awareness of Consequences”, “Appraisal of Responsibility”, “Personal Norms” as well as “Place Attachment” and “Emotions” on water-saving intention.

Considerations on indirect adhesive restorations at the material and tooth interfaces

Objective: Lithium-silicate (LiSi) ceramic is nowadays widely used in dentistry. However, for the longevity of LiSi indirect restorations, it is important to pretreat the material and the dental substrate adequately. However, is not certain how the simplification of the manufacturing and conditioning procedures influences the bonding performances of LiSi ceramic restorations. Accordingly, the aims of this thesis were to investigate the effect of: 1) different LiSi ceramic surface decontamination procedures on the shear bond strength (SBS) to resin composite; 2) different types of lithium-disilicate (LiDi) (pressed vs CAD-CAM) on SBS to resin composite; 3) an experimental metal salt-based zirconium oxynitrate etchant [ZrO(NO3)2] on bonding performances to dentin. Materials and Methods: SBS test was used to investigate the influence of different cleaning protocols applied, or different processing techniques (CAD or PRESS) on the bond strength to composite resin. The third study tackled the interface between restorative materials and dentin, and investigated the microtensile bond strength test (µTBS), nanoleakage expression analysis (NL), gelatin zymography and in situ zymography of dentin conditioned with an experimental metal salt-based zirconium oxynitrate etchant [ZrO(NO3)2]. Results: MEP showed comparable bond strength to the double HP etching and higher compared to other groups. BS of press LiSi to composite was higher than that of CAD/CAM LiSi. ZON pretreatment increased bond strength to dentin when used with a universal adhesive, and inhibited dentinal endogenous enzymes. Conclusions: While simplification of the LiSi conditioning and cleaning procedures seems to yield bond strength comparable to the traditional procedures, it could be recommended in the clinical practice. However, pressed LiSi still seems to perform better in terms of bond strength compared to the CAD/CAM LiSi. Further, the novel ZON etchant seems to perform better compared to the traditional phosphoric dentin etching.

Analysis and design considerations of resonator arrays for inductive power transfer systems

In the frame of inductive power transfer (IPT) systems, arrays of magnetically coupled resonators have received increasing attention as they are cheap and versatile due to their simple structure. They consist of magnetically coupled coils, which resonate with their self-capacitance or lumped capacitive networks. Of great industrial interest are planar resonator arrays used to power a receiver that can be placed at any position above the array. A thorough circuit analysis has been carried out, first starting from traditional two-coil IPT devices. Then, resonator arrays have been introduced, with particular attention to the case of arrays with a receiver. To evaluate the system performance, a circuit model based on original analytical formulas has been developed and experimentally validated. The results of the analysis also led to the definition of a new doubly-fed array configuration with a receiver that can be placed above it at any position. A suitable control strategy aimed at maximising the transmitted power and the efficiency has been also proposed. The study of the array currents has been carried out resorting to the theory of magneto-inductive waves, allowing useful insight to be highlighted. The analysis has been completed with a numerical and experimental study on the magnetic field distribution originating from the array. Furthermore, an application of the resonator array as a position sensor has been investigated. The position of the receiver is estimated through the measurement of the array input impedance, for which an original analytical expression has been also obtained. The application of this sensing technique in an automotive dynamic IPT system has been discussed. The thesis concludes with an evaluation of the possible applications of two-dimensional resonator arrays in IPT systems. These devices can be used to improve system efficiency and transmitted power, as well as for magnetic field shielding.

Development and testing of methodologies for the control and diagnosis of innovative combustion systems

In pursuit of aligning with the European Union's ambitious target of achieving a carbon-neutral economy by 2050, researchers, vehicle manufacturers, and original equipment manufacturers have been at the forefront of exploring cutting-edge technologies for internal combustion engines. The introduction of these technologies has significantly increased the effort required to calibrate the models implemented in the engine control units. Consequently the development of tools that reduce costs and the time required during the experimental phases, has become imperative. Additionally, to comply with ever-stricter limits on 〖"CO" 〗_"2" emissions, it is crucial to develop advanced control systems that enhance traditional engine management systems in order to reduce fuel consumption. Furthermore, the introduction of new homologation cycles, such as the real driving emissions cycle, compels manufacturers to bridge the gap between engine operation in laboratory tests and real-world conditions. Within this context, this thesis showcases the performance and cost benefits achievable through the implementation of an auto-adaptive closed-loop control system, leveraging in-cylinder pressure sensors in a heavy-duty diesel engine designed for mining applications. Additionally, the thesis explores the promising prospect of real-time self-adaptive machine learning models, particularly neural networks, to develop an automatic system, using in-cylinder pressure sensors for the precise calibration of the target combustion phase and optimal spark advance in a spark-ignition engines. To facilitate the application of these combustion process feedback-based algorithms in production applications, the thesis discusses the results obtained from the development of a cost-effective sensor for indirect cylinder pressure measurement. Finally, to ensure the quality control of the proposed affordable sensor, the thesis provides a comprehensive account of the design and validation process for a piezoelectric washer test system.

Analytic models of self-gravitating rotating gaseous tori with central black hole

In this thesis project, I present stationary models of rotating fluids with toroidal distributions that can be used to represent the active galactic nuclei (AGN) central obscurers, i.e. molecular tori (Combes et al., 2019), as well as geometrically thick accretion discs, like ADAF discs (Narayan and Yi, 1995) or Polish doughnuts (Abramowicz, 2005). In particular, I study stationary rotating systems with a more general baroclinic distribution (with a vertical gradient of the angular velocity), which are often more realistic and less studied, due to their complexity, than the barotropic ones (with cylindrical rotation), which are easier to construct. In the thesis, I compute analytically the main intrinsic and projected properties of the power-law tori based on the potential-density pairs of Ciotti and Bertin (2005). I study the density distribution and the resulting gravitational potential for different values of α, in the range 2 < α < 5. For the same models, I compute the surface density of the systems when seen face-on and edge-on. I then apply the stationary Euler equations to obtain rotational velocity and temperature distributions of the self-gravitating models in the absence of an external gravitational potential. In the thesis I also consider the power-law tori with the presence of a central black hole in addition to the gas self-gravity, and solving analytically the stationary Euler equations, I compute how the properties of the system are modified by the black hole and how they vary as a function of the black hole mass. Finally, applying the Solberg-Høiland criterion, I show that these baroclinic stationary models are linearly stable in the absence of the black hole. In the presence of the black hole I derive the analytical condition for stability, which depends on α and on the black hole mass. I also study the stability of the tori in the hypothesis that they are weakly magnetized, finding that they are always unstable to this instability.