Swelling properties of alkali-metal doped polymeric anion-exchange membranes in alcohol media for application in fuel cells

Swelling properties of four commercial anion-exchange membranes with different structure have been analyzed in several hydro-organic media. With this target, the liquid uptake and the surface expansion of the membranes in contact with different pure liquids, water and alcohols (methanol, ethanol and 1-propanol), and with water alcohol mixtures with different concentrations have been experimentally determined in presence and in absence of an alkaline medium (LiOH, NaOH and KOH of different concentrations). The alkali-metal doping effect on the membrane water uptake has also been investigated, analyzing the influence of the hydroxide concentration and the presence of an alcohol in the doping solution. The results show that the membrane structure plays an essential role in the influence that alcohol nature and alkaline media has on the selective properties of the membrane. The heterogeneous membranes, with lower density, show higher liquid uptakes and dimensional changes than the homogeneous membranes, regardless of the doping conditions. (C) 2016 Hydrogen Energy Publications LLC. Published by Elsevier Ltd. All rights reserved.

Anti-parasitic peptides from arthropods and their application in drug therapy.

2016

Photoredox Catalysis and Nucleophilic Organometallic Reagents – Application in Organic Synthesis

The main purpose of my PhD was the combination of the principles of transition metal catalysis with photoredox catalysis. We focused our attention on the development of novel dual catalytic protocols for the functionalization of carbonyl compounds through the generation of transient nucleophilic organometallic species. Specifically, we focused on the development of new methodologies combining photoredox catalysis with titanium and nickel in low oxidation state. Firstly, a Barbier-type allylation of aromatic and aliphatic aldehydes –catalytic in titanium– in the presence of a blue photon-absorbing dye was developed. Parallelly, we were pleased to observe that the developed methodology could also be extended to the propargylation of aldehydes under analogous conditions. After an extensive re–optimization of all the reaction parameters, we developed an enantioselective and diastereoselective pinacol coupling of aromatic aldehydes promoted by non-toxic, cheap and easy to synthetize titanium complexes. The key feature, that allows the complete (dia)stereocontrol played by titanium, is the employment of a red-absorbing organic dye. The tailored (photo)redox properties of the red-absorbing organic dye [nPr–DMQA+][BF4–] promote the selective reduction of Ti(IV) to Ti(III). Moreover, even if the major contribution in dual photoredox and nickel catalysis is devoted to the realization of cross-coupling-type reactions, we wanted to evaluate different possible scenarios. Our focus was on the possibility of exploiting intermediates arising from the oxidative addition of nickel complexes as transient nucleophilic species. The first topic considered regarded the possibility to perform allylation of aldehydes by dual photoredox and nickel catalysis. In the first instance, a non–stereocontrolled version of the reaction was presented. Finally, after a long series of drastic modification of the reaction conditions, a highly enantioselective variant of the protocol was also reported. All the reported methodologies are supported by careful photophysical analysis and, in some cases, computational modelling.

Functional engineering of hybrid heterostructures for application in electronic, optical and optoelectronic nanostructured devices

Interfacing materials with different intrinsic chemical-physical characteristics allows for the generation of a new system with multifunctional features. Here, this original concept is implemented for tailoring the functional properties of bi-dimensional black phosphorus (2D bP or phosphorene) and organic light-emitting transistors (OLETs). Phosphorene is highly reactive under atmospheric conditions and its small-area/lab-scale deposition techniques have hampered the introduction of this material in real-world applications so far. The protection of 2D bP against the oxygen by means of functionalization with alkane molecules and pyrene derivatives, showed long-term stability with respect to the bare 2D bP by avoiding remarkable oxidation up to 6 months, paving the way towards ultra-sensitive oxygen chemo-sensors. A new approach of deposition-precipitation heterogeneous reaction was developed to decorate 2D bP with Au nanoparticles (NP)s, obtaining a “stabilizer-free” that may broaden the possible applications of the 2D bP/Au NPs interface in catalysis and biodiagnostics. Finally, 2D bP was deposited by electrospray technique, obtaining oxidized-phosphorous flakes as wide as hundreds of µm2 and providing for the first time a phosphorous-based bidimensional system responsive to electromechanical stimuli. The second part of the thesis focuses on the study of organic heterostructures in ambipolar OLET devices, intriguing optoelectronic devices that couple the micro-scaled light-emission with electrical switching. Initially, an ambipolar single-layer OLET based on a multifunctional organic semiconductor, is presented. The bias-depending light-emission shifted within the transistor channel, as expected in well-balanced ambipolar OLETs. However, the emitted optical power of the single layer-based device was unsatisfactory. To improve optoelectronic performance of the device, a multilayer organic architecture based on hole-transporting semiconductor, emissive donor-acceptor blend and electron-transporting semiconductor was optimized. We showed that the introduction of a suitable electron-injecting layer at the interface between the electron-transporting and light-emission layers may enable a ≈ 2× improvement of efficiency at reduced applied bias.

Study and characterization of polymorphs of BTBT derivatives and their application in organic electronics

The perquisites of organic semiconductors (OSCs) in the field of organic electronics have attracted much attention due to the advantages like cost-effectiveness, solution processibility, etc. A key property in OSCs is charge carrier mobility, which depends on molecular packing, as even the slightest changes in the packing of OSC can significantly impact the mobility. Organic molecules are constructed by weak interactions, which makes the OSCs prone to adopt multiple packing arrangements, thus giving rise to polymorphism. Therefore, polymorph screening in bulk and thin films is crucial for material development. This thesis aims to present a systematic study of polymorphism of [1]benzothieno[3,2-b]benzothiophene (BTBT) derivatives functionalized with different side chains. The role of peripheral side chains has been studied since they can promote different packing arrangements. The bulk polymorph screening of OSCs was approached with conventional solution mediated recrystallization experiments like evaporation, slurry maturation, anti-solvent precipitation, etc. Each of the polymorphs were inspected for their relative stability and the kinetics of transformation was evaluated. Polymorphism in thin films was also investigated for selected OSCs. Non-equilibrium methods like, thermal gradient and solution shearing were employed to examine the nucleation, crystal growth and morphology in controlled crystallization conditions. After careful analysis of crystal phases in bulk and thin films, OFETs have been fabricated by optimizing the manufacturing conditions and the hole mobility values were extracted. The charge transport property of the OSCs tested for OFETs was supported by the ionization potential and transfer integrals calculation. An attempt to correlate the solid-state structure to electronic properties was carried out. For some of the molecules, mechanical properties have been also investigated, as the response to mechanical stress is highly susceptible to packing arrangements and the intermolecular interaction energy contributions. Additionally, collaborative research was carried out by solving and analysing the crystal structures of six oligorylene molecules.

Anticancer drug discovery using artificial intelligence: an application in pharmacological activity prediction

Hematological cancers are a heterogeneous family of diseases that can be divided into leukemias, lymphomas, and myelomas, often called “liquid tumors”. Since they cannot be surgically removable, chemotherapy represents the mainstay of their treatment. However, it still faces several challenges like drug resistance and low response rate, and the need for new anticancer agents is compelling. The drug discovery process is long-term, costly, and prone to high failure rates. With the rapid expansion of biological and chemical "big data", some computational techniques such as machine learning tools have been increasingly employed to speed up and economize the whole process. Machine learning algorithms can create complex models with the aim to determine the biological activity of compounds against several targets, based on their chemical properties. These models are defined as multi-target Quantitative Structure-Activity Relationship (mt-QSAR) and can be used to virtually screen small and large chemical libraries for the identification of new molecules with anticancer activity. The aim of my Ph.D. project was to employ machine learning techniques to build an mt-QSAR classification model for the prediction of cytotoxic drugs simultaneously active against 43 hematological cancer cell lines. For this purpose, first, I constructed a large and diversified dataset of molecules extracted from the ChEMBL database. Then, I compared the performance of different ML classification algorithms, until Random Forest was identified as the one returning the best predictions. Finally, I used different approaches to maximize the performance of the model, which achieved an accuracy of 88% by correctly classifying 93% of inactive molecules and 72% of active molecules in a validation set. This model was further applied to the virtual screening of a small dataset of molecules tested in our laboratory, where it showed 100% accuracy in correctly classifying all molecules. This result is confirmed by our previous in vitro experiments.

Integrating structural variant calling, annotation and prioritization into whole genome analysis workflows: a practical application in the molecular diagnosis of neurodevelopmental disorders

Background: WGS is increasingly used as a first-line diagnostic test for patients with rare genetic diseases such as neurodevelopmental disorders (NDD). Clinical applications require a robust infrastructure to support processing, storage and analysis of WGS data. The identification and interpretation of SVs from WGS data also needs to be improved. Finally, there is a need for a prioritization system that enables downstream clinical analysis and facilitates data interpretation. Here, we present the results of a clinical application of WGS in a cohort of patients with NDD. Methods: We developed highly portable workflows for processing WGS data, including alignment, quality control, and variant calling of SNVs and SVs. A benchmark analysis of state-of-the-art SV detection tools was performed to select the most accurate combination for SV calling. A gene-based prioritization system was also implemented to support variant interpretation. Results: Using a benchmark analysis, we selected the most accurate combination of tools to improve SV detection from WGS data and build a dedicated pipeline. Our workflows were used to process WGS data from 77 NDD patient-parent families. The prioritization system supported downstream analysis and enabled molecular diagnosis in 32% of patients, 25% of which were SVs and suggested a potential diagnosis in 20% of patients, requiring further investigation to achieve diagnostic certainty. Conclusion: Our data suggest that the integration of SNVs and SVs is a main factor that increases diagnostic yield by WGS and show that the adoption of a dedicated pipeline improves the process of variant detection and interpretation.

Study and characterization of low molecular weight polymer solutions for application in lubricating oils

The aim of this thesis is to evaluate the possibility of using short linear polymer chains as additives in lubricating oil applications. Through previous works, it has been seen that they are particularly resistant to mechanical degradation, which is the main reason why lubricating oils need to be changed after a while. This is the main reason why they could be proposed as alternatives in the market. The results of this work have been split into two major phases: the first concentrated on characterizing a target product obtained through thermal degradation, starting from the original long chain parent polymer, and the second focused on the technological advancement of heat exchangers. Through the studies carried out, we’ve characterized our innovative polymers and the solutions made with them and base oil at different concentrations. The most promising result is that these short random coiled polymeric chains obey to a more general universal function which express the value of specific viscosity as function of a dimensionless quantity c/c*. For the design of the unit operation, several alternatives were proposed and these all shared the same final goal: cooling the polymer without the presence of oxygen to avoid oxidation and formation of unwanted substances. We’ve analyzed the main difficulties related to the presence of these highly viscous substances and, more importantly, how to deal with this situation (e.g. by considering radial static mixer or even more complex conformations).

Characterization of an OPCPA laser amplifier based on the nonlinear crystal YCOB

The work described in this thesis was performed at the Laboratory for Intense Lasers (L2I) of Instituto Superior Técnico, University of Lisbon (IST-UL). Its main contribution consists in the feasibility study of the broadband dispersive stages for an optical parametric chirped pulse amplifier based on the nonlinear crystal yttrium calcium oxi-borate (YCOB). In particular, the main goal of this work consisted in the characterization and implementation of the several optical devices involved in pulse expansion and compression of the amplified pulses to durations of the order of a few optical cycles (20 fs). This type of laser systems find application in fields such as medicine, telecommunications and machining, which require high energy, ultrashort (sub-100 fs) pulses. The main challenges consisted in the preliminary study of the performance of the broadband amplifier, which is essential for successfully handling pulses with bandwidths exceeding 100 nm when amplified from the μJ to 20 mJ per pulse. In general, the control, manipulation and characterization of optical phenomena on the scale of a few tens of fs and powers that can reach the PW level are extremely difficult and challenging due to the complexity of the phenomena of radiation-matter interaction and their nonlinearities, observed at this time scale and power level. For this purpose the main dispersive components were characterized in detail, specifically addressing the demonstration of pulse expansion and compression. The tested bandwidths are narrower than the final ones, in order to confirm the parameters of these elements and predict the performance for the broadband pulses. The work performed led to additional tasks such as a detailed characterization of laser oscillator seeding the laser chain and the detection and cancelling of additional sources of dispersion.

Investigando a aplicação da realidade virtual na educação: vídeo game

A evolução constante da tecnologia está impulsionando a educação para novos rumos, enfatizando a utilização de novas ferramentas, propiciando uma evolução no processo de ensino/aprendizagem. A Realidade Virtual terá e já está tendo um papel definitivo nessa evolução. A presente dissertação visa contribuir para o entendimento das percepções dos estudantes da cidade de Curitiba sobre o uso dos computadores na educação. Para investigar e interpretar tais percepções foram consideradas as principais características das Geração Boomer e Geração Y e os alicerces básicos necessários para a utilização dos conceitos de Realidade Virtual, Educação a Distância, Era Digital, seus efeitos e sua possível aplicação na educação, de modo a permitir que o estudante descubra, explore e construa o seu próprio conhecimento. Buscou-se ainda identificar se as interpretações sobre a tecnologia de Realidade Virtual são convergentes ou divergentes entre os estudantes. Para atingir os objetivos propostos, a coleta de dados se deu a partir da aplicação de questionários estruturados a estudantes do ensino fundamental, médio e superior, matriculados no ano letivo de 2009. A análise dos dados revelou haver uma convergência unânime entre as respostas dos entrevistados e os objetivos da pesquisa.

Estudo avaliativo de um algoritmo genético auto-organizável e multiobjetivo utilizando aprendizado de máquina para aplicações de telecomunicações

This paper presents an evaluative study about the effects of using a machine learning technique on the main features of a self-organizing and multiobjective genetic algorithm (GA). A typical GA can be seen as a search technique which is usually applied in problems involving no polynomial complexity. Originally, these algorithms were designed to create methods that seek acceptable solutions to problems where the global optimum is inaccessible or difficult to obtain. At first, the GAs considered only one evaluation function and a single objective optimization. Today, however, implementations that consider several optimization objectives simultaneously (multiobjective algorithms) are common, besides allowing the change of many components of the algorithm dynamically (self-organizing algorithms). At the same time, they are also common combinations of GAs with machine learning techniques to improve some of its characteristics of performance and use. In this work, a GA with a machine learning technique was analyzed and applied in a antenna design. We used a variant of bicubic interpolation technique, called 2D Spline, as machine learning technique to estimate the behavior of a dynamic fitness function, based on the knowledge obtained from a set of laboratory experiments. This fitness function is also called evaluation function and, it is responsible for determining the fitness degree of a candidate solution (individual), in relation to others in the same population. The algorithm can be applied in many areas, including in the field of telecommunications, as projects of antennas and frequency selective surfaces. In this particular work, the presented algorithm was developed to optimize the design of a microstrip antenna, usually used in wireless communication systems for application in Ultra-Wideband (UWB). The algorithm allowed the optimization of two variables of geometry antenna - the length (Ls) and width (Ws) a slit in the ground plane with respect to three objectives: radiated signal bandwidth, return loss and central frequency deviation. These two dimensions (Ws and Ls) are used as variables in three different interpolation functions, one Spline for each optimization objective, to compose a multiobjective and aggregate fitness function. The final result proposed by the algorithm was compared with the simulation program result and the measured result of a physical prototype of the antenna built in the laboratory. In the present study, the algorithm was analyzed with respect to their success degree in relation to four important characteristics of a self-organizing multiobjective GA: performance, flexibility, scalability and accuracy. At the end of the study, it was observed a time increase in algorithm execution in comparison to a common GA, due to the time required for the machine learning process. On the plus side, we notice a sensitive gain with respect to flexibility and accuracy of results, and a prosperous path that indicates directions to the algorithm to allow the optimization problems with "η" variables

Teoria da Ruína em um Modelo de Markov com dois Estados

In this work, we present a risk theory application in the following scenario: In each period of time we have a change in the capital of the ensurance company and the outcome of a two-state Markov chain stabilishs if the company pays a benece it heat to one of its policyholders or it receives a Hightimes c > 0 paid by someone buying a new policy. At the end we will determine once again by the recursive equation for expectation the time ruin for this company

Contexto esportivo e as restrições comportamentais: reflexões a luz da psicologia bioecológica

To deal with restrictions takes in them to a boarding that has been studied as perspective theoretician to understand as the practitioners acquire standards of coordination in the chosen sports (ARAUJO, 2005). It is basic for the training that if has a knowledge concerning the restrictions more significant than they act on the human performance of the athletes, because this will make possible one adequate recital in the work proposal of the team staff. The question of the theory application, in the world of the sport, is a tool has very desired and pursued, however, nor always if they apply the theoretical knowledge in experimental research that promotes enough and important alterations, that can favor the real additions to Sport Sciences. This study it is an attempt to collaborate in this intention, in way to locate and to modify beginning usual routines between experts and of the sports, in special to the considered situation sports, as the Volleyball (IVOILOV, 2001). This objective is not fixed only in the relative questions to the teach-learning processes, nor so little to the sportive training, but it advances, also, for the instructions given for the coaches to commanded its, at moments any of the sportive trajectory of these; it innovates when searching to exemplify, directly, in a modality of international domain but with few systematic analyses on the human performances in question.

Anderson localization and momentum-space entanglement

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Application for fault location in electrical power distribution systems

Fault location has been studied deeply for transmission lines due to its importance in power systems. Nowadays the problem of fault location on distribution systems is receiving special attention mainly because of the power quality regulations. In this context, this paper presents an application software developed in Matlabtrade that automatically calculates the location of a fault in a distribution power system, starting from voltages and currents measured at the line terminal and the model of the distribution power system data. The application is based on a N-ary tree structure, which is suitable to be used in this application due to the highly branched and the non- homogeneity nature of the distribution systems, and has been developed for single-phase, two-phase, two-phase-to-ground, and three-phase faults. The implemented application is tested by using fault data in a real electrical distribution power system