Engineering of metal oxide nanoparticles for application in electrochemical devices

The growing demand for materials and devices with new functionalities led to the increased inter-est in the field of nanomaterials and nanotechnologies. Nanoparticles, not only present a reduced size as well as high reactivity, which allows the development of electronic and electrochemical devices with exclusive properties, when compared with thin films. This dissertation aims to explore the development of several nanostructured metal oxides by sol-vothermal synthesis and its application in different electrochemical devices. Within this broad theme, this study has a specific number of objectives: a) research of the influence of the synthesis parameters to the structure and morphology of the nanoparticles; b) improvement of the perfor-mance of the electrochromic devices with the application of the nanoparticles as electrode; c) application of the nanoparticles as probes to sensing devices; and d) production of solution-pro-cessed transistors with a nanostructured metal oxide semiconductor. Regarding the results, several conclusions can be exposed. Solvothermal synthesis shows to be a very versatile method to control the growth and morphology of the nanoparticles. The electrochromic device performance is influenced by the different structures and morphologies of WO3 nanoparticles, mainly due to the surface area and conductivity of the materials. The dep-osition of the electrochromic layer by inkjet printing allows the patterning of the electrodes without wasting material and without any additional steps. Nanostructured WO3 probes were produced by electrodeposition and drop casting and applied as pH sensor and biosensor, respectively. The good performance and sensitivity of the devices is explained by the high number of electrochemical reactions occurring at the surface of the na-noparticles. GIZO nanoparticles were deposited by spin coating and used in electrolyte-gated transistors, which promotes a good interface between the semiconductor and the dielectric. The produced transistors work at low potential and with improved ON-OFF current ratio, up to 6 orders of mag-nitude. To summarize, the low temperatures used in the production of the devices are compatible with flexible substrates and additionally, the low cost of the techniques involved can be adapted for disposable devices.

Learning domain-specific sentiment lexicons with applications to recommender systems

Search is now going beyond looking for factual information, and people wish to search for the opinions of others to help them in their own decision-making. Sentiment expressions or opinion expressions are used by users to express their opinion and embody important pieces of information, particularly in online commerce. The main problem that the present dissertation addresses is how to model text to find meaningful words that express a sentiment. In this context, I investigate the viability of automatically generating a sentiment lexicon for opinion retrieval and sentiment classification applications. For this research objective we propose to capture sentiment words that are derived from online users’ reviews. In this approach, we tackle a major challenge in sentiment analysis which is the detection of words that express subjective preference and domain-specific sentiment words such as jargon. To this aim we present a fully generative method that automatically learns a domain-specific lexicon and is fully independent of external sources. Sentiment lexicons can be applied in a broad set of applications, however popular recommendation algorithms have somehow been disconnected from sentiment analysis. Therefore, we present a study that explores the viability of applying sentiment analysis techniques to infer ratings in a recommendation algorithm. Furthermore, entities’ reputation is intrinsically associated with sentiment words that have a positive or negative relation with those entities. Hence, is provided a study that observes the viability of using a domain-specific lexicon to compute entities reputation. Finally, a recommendation system algorithm is improved with the use of sentiment-based ratings and entities reputation.