Dipartimento di Fisica - Tesi di Dottorato

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Questa collezione raccoglie le Tesi di Dottorato afferenti al Dipartimento di Fisica dell'Università della Calabria.

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Author: search.filters.author.Critelli, Salvatore

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    Applicazione dei big data nel turismo, marketing ed education
    (Università della Calabria, 2020-03-18) Giglio, Simona; Critelli, Salvatore; Pantano, Pietro
    Il mondo è attualmente inondato da dati e l’avanzare delle tecnologie digitali amplifica questo fenomeno in modo esponenziale. Tale fenomeno viene etichettato con il concetto di Big Data ovvero le tracce digitali che le nostre attività quotidiane lasciano per effetto dell’uso massiccio dei sistemi ICT (Information Communication Technologies). I Big Data sono diventati il nuovo microscopio che rende “misurabile” la società. Per tali ragioni, la ricerca è incentrata sull’analisi dei Big data, estratti dai social media, da indagini online, da piattaforme di recensioni e da database, attraverso l’applicazione di tecniche e strumenti sviluppati nell’ambito dell’Intelligenza Artificiale. Algoritmi di machine learning, analisi semantica ed analisi statistica sono stati utilizzati per estrarre, dai Big Data, informazione sotto forma di “conoscenza” e “valore”, dimostrando come dati di grandi dimensioni possano fungere da ricca fonte di informazione, da un lato, per comprendere il comportamento dell’utente, parte integrante di una società complessa (conoscenza), e dall’altro, per sostenere i processi decisionali e i servizi forniti agli utenti/consumatori (valore). Il lavoro si caratterizza per un approccio multidisciplinare tra settori differenti quali le scienze sociali, le scienze statistiche e l’informatica. Questo ha permesso di fondare la ricerca sui Big Data nella teoria, e fornire un efficace recupero e analisi dei dati nella pratica. Le tecniche di machine learning sono state applicate per (i) il riconoscimento delle immagini, (ii) per la creazione di cluster, (iii) per l’analisi del testo (sentiment analysis) e (iv) per la profilazione di classi di utenti. Per il riconoscimento delle immagini l’approccio ha richiamato le reti neurali artificiali (deep artificial neural networks), algoritmi e sistemi computazionali ispirati al cervello umano utilizzando le potenzialità del programma Wolfram Mathematica e la disponibilità di dati estratti da social network quali Flickr, Twitter, Instagram ed altre piattaforme come TripAdvisor. Gli strumenti utilizzati nella ricerca hanno permesso di indagare e di rilevare in modo oggettivo dall’analisi di immagini e di testi condivisi sul web, alcuni comportamenti cognitivi degli utenti/consumatori alla base delle loro scelte nonché l’attrattività di una destinazione turistica e la qualità dell’esperienza dell’utente. Lo studio del significato delle parole nel testo ha aperto la strada al web semantico che permette ad un utente di acquisire informazioni approfondite durante una ricerca attraverso un sistema formato da una rete di relazioni e connessioni tra documenti. Partendo dalle ricerche di Ogden e Richards sullo studio del significato e di Jakobson che studiò i processi comunicativi, si è cercato di strutturare e sistematizzare un processo che riflette un atto comunicativo ed informativo tale che un simbolo (immagine) attraverso l’applicazione di un significante (machine learning che si sostituisce al processo mentale proprio dell’uomo) permettesse l’esplicitazione di un referente (oggetto\etichetta) che opportunatamente porta alla trasmissione di un messaggio sotto forma di conoscenza. Il tutto coordinato da un sistema in grado di coniugare fattori differenti in un’ottica interdisciplinare dove l’analisi dei dati combacia perfettamente con la linguistica. Attingendo da studi precedenti, i risultati raggiunti dimostrano che gli algoritmi di analisi dei Big Data quali l’apprendimento automatico contribuiscono da un lato alla comprensione sull’esperienza dell’utente verso un luogo, una destinazione; d’altra parte, la loro analisi fornisce una conoscenza sistematica delle valutazioni dei consumatori su un determinato prodotto o servizio e verso lo sviluppo di una sorta di “intelligenza sociale”. Inoltre i risultati della ricerca propongono come, un approccio più sofisticato al monitoraggio dei social media nel contesto turistico e nel marketing, nonché nel settore dell’education, possa contribuire a migliorare le decisioni strategiche e le politiche operative degli stakeholder nonché ad avere una visione psicologica sugli atteggiamenti e sul comportamento di un ampio spettro di utenti.
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    Development of advanced systems for energy conversion based on innovative two- dimensional materials
    (Università della Calabria, 2021-09-27) Zappia, Isabella; Critelli, Salvatore; Chiarello, Gennaro; Cupolillo, Anna
    The even growing energy demand due to the demographic growth and the consequent economic expansion has led to the search for innovative technologies available for energy production and conversion from green and renewable sources such as solar energy. In this context, twodimensional (2D) materials, including either single- and few-layer flake forms, are constantly attracting more and more interest as potential advanced photo(electro)catalysts for redox reactions leading to green fuel production. Recently, layered semiconductors of group-III and group-IV, which can be exfoliated in their 2D form due to low cleavage energy (typically < 0.5 J m-2), have been theoretically predicted as water splitting photocatalysts for hydrogen production. For example, their large surface-to-volume ratio intrinsically guarantees that the charge carriers are directly photogenerated at the interface with the electrolyte, where redox reactions take place before they recombine. Moreover, their electronic structure can be tuned by controlling the number of layers, fulfilling the fundamental requirements for water splitting photocatalysts, i.e.: 1) conduction band minimum (CBM) energy (ECBM) > reduction potential of H+/H2 (E(H+/H2)); 2) valence band maximum (VBM) energy (EVBM) < reduction potential of O2/H2O (E(O2/H2O)). A requirement for large-scale applications is the development of low-cost, reliable industrial production processes. In this scenario, liquid-phase exfoliation (LPE) methods provide scalable production of 2D materials in form of liquid dispersions, enabling their processing in thin-film through low‐cost and industrially relevant deposition techniques. This thesis investigates, for the first time, the photoelectrochemical (PEC) activity of single-/fewlayer flakes of GaS, GaSe, and GeSe produced through ultrasound-assisted LPE in environmentally friendly solvents (e.g., 2-propanol) in aqueous media. Our results are consequently used to design proof-of-concept PEC water splitting photoelectrodes, as well as PEC-type photodetectors. Moreover, structural and electronic properties of PtTe2 have been investigated, being this material a potential catalyst for the hydrogen evolution reaction (HER) and other fuel-producing electrochemical reactions.
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    Synthesis and cherization of low-dimensional materials
    (Università della Calabria, 2020-04-16) Alessandro, Francesca; Critelli, Salvatore; Caputi, Lorenzo; Cupolillo, Anna
    The main aim of this thesis is to synthesize and study low-dimensional materials, with special focus on: silicene, PtTe2, carbon nano-onions and activated carbon. The first section of this work describes the study of the collective modes in silicene and PtTe2. Silicene, the silicon equivalent of graphene, is attracting increasing scientific and technological interest in view of the exploitation of its exotic electronic properties. This material has been theoretically predicted to exist as a free-standing layer in a low-buckled, stable form, and can be synthesized by the deposition of Si on appropriate crystalline substrates. Using a combined experimental (High-Resolution Electron-Energy-Loss Spectroscopy, HR-EELS) and theoretical (Time Dependent Density Functional Theory, TDDFT) approach the electronic excitations of two phases of silicene growth on silver were studied showing that silicene grown in a mixed phase on Ag(111), preserves part of the semimetallic character of its freestanding form, exhibiting an interband π-like plasmon. Recently, the PtTe2 has emerged as one of the most promising among layered materials ―beyond graphene‖. In this work, the electronic excitations of the bulk PtTe2 were investigated by means of EELS and DFT detecting a sequence of modes at 3.9, 7.5 and 19.0 eV. The comparison of the excitation spectrum with the calculated density of states (DOS) allowed to ascribe spectral features to transitions between specific electronic states. Moreover, it has been observed that, in contrast to graphene, the high-energy plasmon in PtTe2 gets red-shifted by 2.5 eV with increasing thickness. The second section of this thesis reports the synthesis of polyhedral carbon nano-onions by arc discharge in water and the electrochemical performance of activated carbon in aqueous electrolytes. CNOs, in their spherical or polyhedral forms, represent an important class of nanomaterials, due to their peculiar physical and chemical properties. In this work, polyhedral carbon nano-onions (CNOs) were obtained by underwater arc discharge of graphite electrodes using an innovative experimental arrangement. Dispersed nanomaterials and a black hard cathodic deposit were generated during the discharges and studied by scanning electron microscopy (SEM), transmission electron microscopy (TEM), Raman spectroscopy and thermogravimetric analysis (TGA). A model for the formation of the deposit was proposed, in which the crystallization is driven by an intense temperature gradient in the space very close to the cathode surface. Electric double layer capacitors (EDLC) are gaining increasing popularity in high power energy storage applications. Novel carbon materials with high surface area, high electrical conductivity, as well as a range of shapes, sizes and pore size distributions are being constantly developed and tested as potential supercapacitor electrodes. In this thesis, the electrochemical behavior of a highly microporous activated carbon was studied as electrode for symmetric and asymmetric capacitors in acid and neutral media. The highest capacity and energy density values were obtained in the case of the activated carbon in acid solution.
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    Synthesis and characterization of nanomaterials: graphene, silicene and carbon nano- onions
    (2017-10-20) Osman, Salih Mohamed; Critelli, Salvatore; Caputi, Lorenzo
    The electronic structure of the graphene/Ni(111) system was investigated by means of electron energy-loss spectroscopy (EELS). A single layer of graphene has been obtained on Ni(111) by dissociation of ethylene. Angle-resolved EEL spectra show a low energy plasmon dispersing up to about 2 eV, resulting from fluctuation of a charge density located around the Fermi energy, due to hybridization between Ni and graphene states. The dispersion is typical of a two-dimensional charge layer, and the calculated Fermi velocity is a factor of ~0.5 lower than in isolated graphene. The interface-π plasmon, related to interband transitions involving hybridized states at the K point of the hexagonal Brillouin zone, has been measured at different scattering geometries. The resulting dispersion curve exhibits a square root behavior, indicating also in this case a two-dimensional character of the interface charge density. As well, it has been shown that it is possible to use EELS in the reflection mode to measure the fine structure of the carbon K-edge in monolayer graphene on Ni(111), thus demonstrating that reflection EELS is a very sensitive tool, particularly useful in cases where the TEM-based ELNES cannot be applied. Clean Ag(111) surface and the two phases of silicene on Ag(111), mixed (4×4, √13×√13R19°, 2√3×2√3R30°) and 2√3×2√3R30, have been studied by XPS, LEED and EELS. EEL spectra of the Ag(111) surface covered by silicene in the (4×4, √13×√13R19°, 2√3×2√3R30°) mixed phase shows a well-defined plasmon peak whose center is located at about 1.75 eV. The 2√3×2√3R30° phase shows EEL spectra that exhibit a peak located at about 0.75 eV loss, which moves clearly towards higher energies with increasing momentum transfer. The typical parabolic dispersion relation obtained from such spectra confirms that the peak is due to a collective excitation which is evidently associated to the silicene layer. These plasmons associated to silicene have never been observed in the past. Our results show that the plasmonic properties of silicene on Ag(111) are strongly dependent on the geometrical arrangement of Si atoms with respect to the substrate. Carbonaceous nanomaterials have been obtained by underwater arc discharge between graphite electrodes. TEM images showed that the resulting particles suspended in water consist of CNOs with other carbonaceous materials such as CNTs and graphene. We observed for the first time the formation of a solid agglomerate on the cathode surface. Raman and TEM studies revealed that the agglomerate is made exclusively of CNOs. The defragmentation of such agglomerate allows to obtain CNOs free of other carbonaceous materials without the complex purification procedures needed for floating nanomaterials
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