Measure of Global Specialization and Spatial Clustering for the Identification of "Specialized" Agglomeration

The intensity of regional specialization in specific activities, and conversely, the level of industrial concentration in specific locations, has been used as a complementary evidence for the existence and significance of externalities. Additionally, economists have mainly focused the debate on disentangling the sources of specialization and concentration processes according to three vectors: natural advantages, internal, and external scale economies. The arbitrariness of partitions plays a key role in capturing these effects, while the selection of the partition would have to reflect the actual characteristics of the economy. Thus, the identification of spatial boundaries to measure specialization becomes critical, since most likely the model will be adapted to different scales of distance, and be influenced by different types of externalities or economies of agglomeration, which are based on the mechanisms of interaction with particular requirements of spatial proximity. This work is based on the analysis of the spatial aspect of economic specialization supported by the manufacturing industry case. The main objective is to propose, for discrete and continuous space: i) a measure of global specialization; ii) a local disaggregation of the global measure; and iii) a spatial clustering method for the identification of specialized agglomerations.

Chemiluminescence DNA-based Nanotechnologies for Bioanalytical Applications

DNA as powerful building molecule, is widely used for the assembly of molecular structures and dynamic molecular devices with different potential applications, ranging from synthetic biology to diagnostics. The feature of sequence programmability, which makes it possible to predict how single stranded DNA molecules fold and interact with one another, allowed the development of spatiotemporally controlled nanostructures and the engineering of supramolecular devices. The first part of this thesis addresses the development of an integrated chemiluminescence (CL)-based lab-on-chip sensor for detection of Adenosine-5-triphosphate (ATP) life biomarker in extra-terrestrial environments.Subsequently, we investigated whether it is possible to study the interaction and the recognition between biomolecules and their targets, mimicking the intracellular environment in terms of crowding, confinement and compartmentalization. To this purpose, we developed a split G-quadruplex DNAzyme platform for the chemiluminescent and quantitative detection of antibodies based on antibody-induced co-localization proximity mechanism in which a split G-quadruplex DNAzyme is led to reassemble into the functional native G-quadruplex conformation as the effect of a guided spatial nanoconfinement.The following part of this thesis aims at developing chemiluminescent nanoparticles for bioimaging and photodynamic therapy applications.In chapter5 a realistic and accurate evaluation of the potentiality of electrochemistry and chemiluminescence (CL) for biosensors development (i.e., is it better to “measure an electron or a photon”?), has been achieved.In chapter 6 the emission anisotropy phenomenon for an emitting dipole bound to the interface between two media with different refractive index has been investigated for chemiluminescence detection.

Modelling of ORC components and systems for low-medium temperature heat recovery applications with reduced environmental impact

Although its great potential as low to medium temperature waste heat recovery (WHR) solution, the ORC technology presents open challenges that still prevent its diffusion in the market, which are different depending on the application and the size at stake. Focusing on the micro range power size and low temperature heat sources, the ORC technology is still not mature due to the lack of appropriate machines and working fluids. Considering instead the medium to large size, the technology is already available but the investment is still risky. The intention of this thesis is to address some of the topical themes in the ORC field, paying special attention in the development of reliable models based on realistic data and accounting for the off-design performance of the ORC system and of each of its components. Concerning the “Micro-generation” application, this work: i) explores the modelling methodology, the performance and the optimal parameters of reciprocating piston expanders; ii) investigates the performance of such expander and of the whole micro-ORC system when using Hydrofluorocarbons as working fluid or their new low GWP alternatives and mixtures; iii) analyzes the innovative ORC reversible architecture (conceived for the energy storage), its optimal regulation strategy and its potential when inserted in typical small industrial frameworks. Regarding the “Industrial WHR” sector, this thesis examines the WHR opportunity of ORCs, with a focus on the natural gas compressor stations application. This work provides information about all the possible parameters that can influence the optimal sizing, the performance and thus the feasibility of installing an ORC system. New WHR configurations are explored: i) a first one, relying on the replacement of a compressor prime mover with an ORC; ii) a second one, which consists in the use of a supercritical CO2 cycle as heat recovery system.

Clustering of variables around latent components: an application in consumer science

The present work proposes a method based on CLV (Clustering around Latent Variables) for identifying groups of consumers in L-shape data. This kind of datastructure is very common in consumer studies where a panel of consumers is asked to assess the global liking of a certain number of products and then, preference scores are arranged in a two-way table Y. External information on both products (physicalchemical description or sensory attributes) and consumers (socio-demographic background, purchase behaviours or consumption habits) may be available in a row descriptor matrix X and in a column descriptor matrix Z respectively. The aim of this method is to automatically provide a consumer segmentation where all the three matrices play an active role in the classification, getting homogeneous groups from all points of view: preference, products and consumer characteristics. The proposed clustering method is illustrated on data from preference studies on food products: juices based on berry fruits and traditional cheeses from Trentino. The hedonic ratings given by the consumer panel on the products under study were explained with respect to the product chemical compounds, sensory evaluation and consumer socio-demographic information, purchase behaviour and consumption habits.

Thiophene- Based Materials for Photovoltaic Applications

Thiophene oligomers (OTs) and polymers (PTs) are currently attracting remarkable attention as organic materials showing semiconducting, fluorescent, nonlinear optical and liquid crystalline properties. All these properties can be fine-tuned through minor structural modifications. As a consequence, thiophene oligomers and polymers are among the most investigated compounds for applications in organic electronics, optoelectronics and thin film devices such as field effect transistors (FETs), light emitting diodes (LEDs) and photovoltaic devices (PVDs). Our research aims to explore the self-assembly features and the optical, electrical and photovoltaic properties of a class of thiophene based materials so far scarcely investigated, namely that of oligo- and polythiophenes head-to-head substituted with alkyl or S-alkyl chains. In particular, we synthesized these compounds in short reaction times, high yields, high purity and environmentally friendly procedures taking advantage of ultrasound (US) and microwave (MW) enabling technologies in Suzuki-Miyaura cross-couplings.

Employing Distances in Design-based Spatial Estimation

In the last couple of decades we assisted to a reappraisal of spatial design-based techniques. Usually the spatial information regarding the spatial location of the individuals of a population has been used to develop efficient sampling designs. This thesis aims at offering a new technique for both inference on individual values and global population values able to employ the spatial information available before sampling at estimation level by rewriting a deterministic interpolator under a design-based framework. The achieved point estimator of the individual values is treated both in the case of finite spatial populations and continuous spatial domains, while the theory on the estimator of the population global value covers the finite population case only. A fairly broad simulation study compares the results of the point estimator with the simple random sampling without replacement estimator in predictive form and the kriging, which is the benchmark technique for inference on spatial data. The Monte Carlo experiment is carried out on populations generated according to different superpopulation methods in order to manage different aspects of the spatial structure. The simulation outcomes point out that the proposed point estimator has almost the same behaviour as the kriging predictor regardless of the parameters adopted for generating the populations, especially for low sampling fractions. Moreover, the use of the spatial information improves substantially design-based spatial inference on individual values.

Development and characterization of innovative graphene-based composites

Over the last decade, graphene and related materials (GRM) have drawn significant interest and resources for their development into the next generation of composite materials. This is because these nanoparticles have the ability to operate as reinforcing additives capable of imparting considerable mechanical property increases while also embedding multi-functional advantages on the host matrix. Because graphene and 2D materials are still in their early stages, the relative maturity of different types of composite systems varies. As a result, certain nanocomposite systems are currently commercially accessible, while others are not yet sufficiently developed to enter the market. A substantial emphasis has been placed on developing thermoplastic and thermosetting materials that combine a variety of mechanical and functional qualities. These include higher strength and stiffness, increased thermal and electrical conductivity, improved barrier properties, fire retardancy, and others, with the ultimate goal of providing multifunctionality to already employed composites. The work presented in this thesis investigates the use and benefits that GRM could bring to composites for a variety of applications, with the goal of realizing multifunctional components with improved properties that leads to lightweight and, as a result, energy and cost savings and pollution reduction in the environment. In particular, we worked on the following topics: • Benchmarking of commercial GRM-based master batches; • GRM-coatings for water uptake reduction; • GRM as thermo-electrical anti-icing /de-icing system; • GRM for Out of Oven curing of composites.