Photoconductivity and Electro-Optical Properties of Wide Band Gap Metal Oxides

The PhD activity described in this Thesis was focused on the study of metal-oxide wide-bandgap materials, aiming at fabricating new optoelectronic devices such as solar-blind UV photodetectors, high power electronics, and gas sensors. Photocurrent spectroscopy and DC photocurrent time evolution were used to investigate the performance of prototypes under different atmospheres, temperatures and excitation wavelengths (or dark conditions). Cathodoluminescence, absorption spectroscopy, XRD and SEM were used to assess structural, morphologic, electrical and optical properties of materials. This thesis is divided into two main sections, each describing the work done on a different metal-oxide semiconductor. 1) MOVPE-grown Ga2O3 thin films for UV solar-blind photodetectors and high power devices The semiconducting oxides, among them Ga2O3, have been employed for several decades as transparent conducting oxide (TCO) electrodes for fabrication of solar cells, displays, electronic, and opto-electronic devices. The interest was mainly confined to such applications, as these materials tend to grow intrinsically n-type, and attempts to get an effective p-type doping has consistently failed. The key requirements of TCO electrodes are indeed high electrical conductivity and good transparency, while crystallographic perfection is a minor issue. Furthermore, for a long period no high-quality substrates and epi-layers were available, which in turn impeded the development of a truly full-oxide electronics. Recently, Ga2O3 has attracted renewed interest, as large single crystals and high-quality homo- and hetero-epitaxial layers became available, which paved the way to novel application areas. Our research group spent the last two years in developing a low temperature (500-700°C) MOVPE growth procedure to obtain thin films of Ga2O3 on different substrates (Dept. of Physics and IMEM-CNR at UNIPR). We obtained a significant result growing on oriented sapphire epitaxial films of high crystalline, undoped, pure phase -Ga2O3 (hexagonal). The crystallographic properties of this phase were investigated by XRD, in order to clarify the lattice parameters of the hexagonal cell. First design and development of solar blind UV photodetectors based on -phase was carried out and the optoelectronic performance is evaluated by means of photocurrent spectroscopy. The UV-response is adequately fast and reliable to render this unusual phase a subject of great interest for future applications. The availability of a hexagonal phase of Ga2O3 stable up to 700°C, belonging to the same space group of gallium nitride, with high crystallinity and tunable electrical properties, is intriguing in view of the development of nitride-based devices, by taking advantage of the more favorable symmetry and epitaxial relationships with respect to the monoclinic β-phase. In addition, annealing at temperatures higher than 700°C demonstrate that the hexagonal phase converts totally in the monoclinic one. 2) ZnO nano-tetrapods: charge transport mechanisms and time-response in optoelectronic devices and sensors Size and morphology of ZnO at the nanometer scale play a key role in tailoring its physical and chemical properties. Thanks to the possibility of growing zinc oxide in a variety of different nanostructures, there is a great variety of applications, among which gas sensors, light emitting diodes, transparent conducting oxides, solar cells. Even if the operation of ZnO nanostructure-based devices has been recently demonstrated, the mechanisms of charge transport in these assembly is still under debate. The candidate performed an accurate investigation by photocurrent spectroscopy and DC-photocurrent time evolution of electrical response of both single-tetrapod and tetrapod-assembly devices. During the research done for this thesis, a thermal activation energy enables the performance of samples at high temperatures (above about 300°C). The energy barrier is related to the leg-to-leg interconnection in the assembly of nanotetrapods. Percolation mechanisms are responsible for both the very slow photo-response (minutes to hours or days) and the significant persistent photocurrent. Below the bandgap energy, electronic states were investigated but their contribution to the photocurrent are two-three order of magnitude lower than the band edge. Such devices are suitable for employ in photodetectors as well as in gas sensors, provided that the mechanism by which the photo-current is generated and gas adsorption on the surface modify the conductivity of the material are known.

Asymptotic theory of time varying networks with memory and heterogeneous activation pattern

In this thesis work we develop a new generative model of social networks belonging to the family of Time Varying Networks. The importance of correctly modelling the mechanisms shaping the growth of a network and the dynamics of the edges activation and inactivation are of central importance in network science. Indeed, by means of generative models that mimic the real-world dynamics of contacts in social networks it is possible to forecast the outcome of an epidemic process, optimize the immunization campaign or optimally spread an information among individuals. This task can now be tackled taking advantage of the recent availability of large-scale, high-quality and time-resolved datasets. This wealth of digital data has allowed to deepen our understanding of the structure and properties of many real-world networks. Moreover, the empirical evidence of a temporal dimension in networks prompted the switch of paradigm from a static representation of graphs to a time varying one. In this work we exploit the Activity-Driven paradigm (a modeling tool belonging to the family of Time-Varying-Networks) to develop a general dynamical model that encodes fundamental mechanism shaping the social networks' topology and its temporal structure: social capital allocation and burstiness. The former accounts for the fact that individuals does not randomly invest their time and social interactions but they rather allocate it toward already known nodes of the network. The latter accounts for the heavy-tailed distributions of the inter-event time in social networks. We then empirically measure the properties of these two mechanisms from seven real-world datasets and develop a data-driven model, analytically solving it. We then check the results against numerical simulations and test our predictions with real-world datasets, finding a good agreement between the two. Moreover, we find and characterize a non-trivial interplay between burstiness and social capital allocation in the parameters phase space. Finally, we present a novel approach to the development of a complete generative model of Time-Varying-Networks. This model is inspired by the Kaufman's adjacent possible theory and is based on a generalized version of the Polya's urn. Remarkably, most of the complex and heterogeneous feature of real-world social networks are naturally reproduced by this dynamical model, together with many high-order topological properties (clustering coefficient, community structure etc.).