Anaerobic oxidation of ethanol over spinel mixed oxides: the first step in the steam-iron process for H2 production

The future hydrogen demand is expected to increase, both in existing industries (including upgrading of fossil fuels or ammonia production) and in new technologies, like fuel cells. Nowadays, hydrogen is obtained predominantly by steam reforming of methane, but it is well known that hydrocarbon based routes result in environmental problems and besides the market is dependent on the availability of this finite resource which is suffering of rapid depletion. Therefore, alternative processes using renewable sources like wind, solar energy and biomass, are now being considered for the production of hydrogen. One of those alternative methods is the so-called “steam-iron process” which consists in the reduction of a metal-oxide by hydrogen-containing feedstock, like ethanol for instance, and then the reduced material is reoxidized with water to produce “clean” hydrogen (water splitting). This kind of thermochemical cycles have been studied before but currently some important facts like the development of more active catalysts, the flexibility of the feedstock (including renewable bio-alcohols) and the fact that the purification of hydrogen could be avoided, have significantly increased the interest for this research topic. With the aim of increasing the understanding of the reactions that govern the steam-iron route to produce hydrogen, it is necessary to go into the molecular level. Spectroscopic methods are an important tool to extract information that could help in the development of more efficient materials and processes. In this research, ethanol was chosen as a reducing fuel and the main goal was to study its interaction with different catalysts having similar structure (spinels), to make a correlation with the composition and the mechanism of the anaerobic oxidation of the ethanol which is the first step of the steam-iron cycle. To accomplish this, diffuse reflectance spectroscopy (DRIFTS) was used to study the surface composition of the catalysts during the adsorption of ethanol and its transformation during the temperature program. Furthermore, mass spectrometry was used to monitor the desorbed products. The set of studied materials include Cu, Co and Ni ferrites which were also characterized by means of X-ray diffraction, surface area measurements, Raman spectroscopy, and temperature programmed reduction.

New markov chain based methods for single and cross-domain sentiment classification

Nowadays communication is switching from a centralized scenario, where communication media like newspapers, radio, TV programs produce information and people are just consumers, to a completely different decentralized scenario, where everyone is potentially an information producer through the use of social networks, blogs, forums that allow a real-time worldwide information exchange. These new instruments, as a result of their widespread diffusion, have started playing an important socio-economic role. They are the most used communication media and, as a consequence, they constitute the main source of information enterprises, political parties and other organizations can rely on. Analyzing data stored in servers all over the world is feasible by means of Text Mining techniques like Sentiment Analysis, which aims to extract opinions from huge amount of unstructured texts. This could lead to determine, for instance, the user satisfaction degree about products, services, politicians and so on. In this context, this dissertation presents new Document Sentiment Classification methods based on the mathematical theory of Markov Chains. All these approaches bank on a Markov Chain based model, which is language independent and whose killing features are simplicity and generality, which make it interesting with respect to previous sophisticated techniques. Every discussed technique has been tested in both Single-Domain and Cross-Domain Sentiment Classification areas, comparing performance with those of other two previous works. The performed analysis shows that some of the examined algorithms produce results comparable with the best methods in literature, with reference to both single-domain and cross-domain tasks, in $2$-classes (i.e. positive and negative) Document Sentiment Classification. However, there is still room for improvement, because this work also shows the way to walk in order to enhance performance, that is, a good novel feature selection process would be enough to outperform the state of the art. Furthermore, since some of the proposed approaches show promising results in $2$-classes Single-Domain Sentiment Classification, another future work will regard validating these results also in tasks with more than $2$ classes.

Dynamics of Bora wind over the Adriatic sea: atmospheric water balance and role of air-sea fluxes and orography

The Bora wind is a mesoscale phenomenon which typically affects the Adriatic Sea basin for several days each year, especially during winter. The Bora wind has been studied for its intense outbreak across the Dinaric Alps. The properties of the Bora wind are widely discussed in the literature and scientific papers usually focus on the eastern Adriatic coast where strong turbulence and severe gust intensity are more pronounced. However, the impact of the Bora wind can be significant also over Italy, not only in terms of wind speed instensity. Depending on the synoptic pressure pattern (cyclonic or anticyclonic Bora) and on the season, heavy snowfall, severe storms, storm surges and floods can occur along the Adriatic coast and on the windward flanks of the Apennines. In the present work five Bora cases that occurred in recent years have been selected and their evolution has been simulated with the BOLAM-MOLOCH model set, developed at ISAC-CNR in Bologna. Each case study has been addressed by a control run and by several sensitivity tests, performed with the purpose of better understanding the role played by air-sea latent and sensible heat fluxes. The tests show that the removal of the fluxes induces modifications in the wind approching the coast and a decrease of the total precipitation amount predicted over Italy. In order to assess the role of heat fluxes, further analysis has been carried out: column integrated water vapour fluxes have been computed along the Italian coastline and an atmospheric water balance has been evaluated inside a box volume over the Adriatic Sea. The balance computation shows that, although latent heat flux produces a significant impact on the precipitation field, its contribution to the balance is relatively minor. The most significant and lasting case study, that of February 2012, has been studied in more detail in order to explain the impressive drop in the total precipitation amount simulated in the sensitivity tests with removed heat fluxes with respect to the CNTRL run. In these experiments relative humidity and potential temperature distribution over different cross-sections have been examined. With respect to the CNTRL run a drier and more stable boundary layer, characterised by a more pronounced wind shear at the lower levels, has been observed to establish above the Adriatic Sea. Finally, in order to demonstrate that also the interaction of the Bora flow with the Apennines plays a crucial role, sensitivity tests varying the orography height have been considered. The results of such sensitivity tests indicate that the propagation of the Bora wind over the Adriatic Sea, and in turn its meteorological impact over Italy, is influenced by both the large air-sea heat fluxes and the interaction with the Apennines that decelerate the upstream flow.