Revestimento de superfícies metálicas com TiN e AIN produzidos com plasma magnetrão

Este trabalho visa a obtenção e o estudo das características dos revestimentos de AlN e TiN em substratos metálicos, produzidos por pulverização catódica em plasma magnetrão, num equipamento com cátodo oco, desenvolvido no LEF do CEFITEC. Este equipamento foi adaptado para o presente trabalho, através de alguns elementos adicionais, designadamente de um porta-amostras que permitiu o revestimento de provetes em lotes. Deste estudo conclui-se que a aplicação de uma tensão de “bias” na amostra altera a morfologia dos revestimentos e as características dos materiais que constituem o filme, não só no que diz respeito à sua composição, como também proporciona estruturas mais densas e com menos porosidade. As tensões de “bias” típicas foram de –100 V no caso de AlN e de –75 V e com uma potência de 2,0 kW no cátodo no caso de TiN. Neste último foi considerado apenas o objectivo da obtenção da fase d, de estrutura CFC (cor dourada), por ser a única de interesse industrial. Por difracção de raios x verificou-se a obtenção de TiN e TiN0,9 com as características pretendidas. Também se verificou que as tensões residuais dos filmes são de compressão e isotrópicas.

Artefacts induced on c-type haem proteins by electrode surfaces

J Biol Inorg Chem (2011) 16:209–215 DOI 10.1007/s00775-010-0717-z

Traduzir Teatro no Estado Novo: Gata em Telhado de Zinco Quente (1959), tradução de Sérgio Guimarães, do original Cat on a Hot Tin Roof (1955), de Tennessee Williams

À luz da viragem cultural dos Estudos de Tradução ocorrida nos anos 80 e tendo em conta a interdisciplinaridade abordada nos campos literário, cultural e histórico pela Manipulation School (Lefevere, Bassnett, Lambert, Hermans e Toury), na esteira de Itamar Even-Zohar com a Teoria dos Polissistemas (1979), a presente dissertação pretende analisar a tradução portuguesa da peça Cat on a Hot Tin Roof (1955), da autoria de Tennessee Williams, intitulada Gata em Telhado de Zinco Quente (1959), de Sérgio Guimarães. Este pode ser um caso representativo de como a tradução para teatro actua na cultura receptora numa perspectiva diatópica, antevendo a dimensão intercultural da tradução para o palco. É ao tradutor que cabe a tarefa de transferir a peça de um sistema linguístico e cultural para outro, conhecendo, se possível, o grau de representabilidade da mesma e o contexto cultural de chegada. Deste modo, é evidenciada a competência artístico-criativa do tradutor teatral que trabalha com o intuito de manter, fidus interpres, as intenções do autor da obra original. No período em que Cat on a Hot Tin Roof foi escrita, ensombrado pelo controlo sociopolítico do Macartismo nos E.U.A. e o contexto em que a tradução foi concretizada, sob a vigência da Ditadura de Salazar, a (auto)censura desempenha um papel fundamental ao moldar a produção literária nos dois sistemas culturais. Numa época em que, mais do que nos dias de hoje, traduzir consistia numa actividade subserviente e secundária, Vasco Morgado, detentor do monopólio de teatros em Lisboa encomendou a Sérgio Guimarães a tradução de uma peça de Tennessee Williams. Com base na teoria desenvolvida por Lawrence Venuti em The Translator’s Invisibility (1995), não é despiciente problematizar, neste estudo de caso, a invisibilidade do tradutor/mediador entre o texto e a representação, abordando simultaneamente as estratégias então necessárias para a peça ser aprovada e posta em cena.

Nanostructuring silicon probes via electrodeposition: characterization of electrode coatings for acute in vivo neural recordings

Understanding how the brain works will require tools capable of measuring neuron elec-trical activity at a network scale. However, considerable progress is still necessary to reliably increase the number of neurons that are recorded and identified simultaneously with existing mi-croelectrode arrays. This project aims to evaluate how different materials can modify the effi-ciency of signal transfer from the neural tissue to the electrode. Therefore, various coating materials (gold, PEDOT, tungsten oxide and carbon nano-tubes) are characterized in terms of their underlying electrochemical processes and recording ef-ficacy. Iridium electrodes (177-706 μm2) are coated using galvanostatic deposition under different charge densities. By performing electrochemical impedance spectroscopy in phosphate buffered saline it is determined that the impedance modulus at 1 kHz depends on the coating material and decreased up to a maximum of two orders of magnitude for PEDOT (from 1 MΩ to 25 kΩ). The electrodes are furthermore characterized by cyclic voltammetry showing that charge storage capacity is im-proved by one order of magnitude reaching a maximum of 84.1 mC/cm2 for the PEDOT: gold nanoparticles composite (38 times the capacity of the pristine). Neural recording of spontaneous activity within the cortex was performed in anesthetized rodents to evaluate electrode coating performance.

Direct electrochemistry of the Desulfovibrio gigas aldehyde oxidoreductase

Eur. J. Biochem. 271, 1329–1338 (2004)

Electrochemical studies on small electron transfer proteins using membrane electrodes

Journal of Electroanalytical Chemistry 541 (2003) 153-162

Automatic learning for the classification of chemical reactions and in statistical thermodynamics

This Thesis describes the application of automatic learning methods for a) the classification of organic and metabolic reactions, and b) the mapping of Potential Energy Surfaces(PES). The classification of reactions was approached with two distinct methodologies: a representation of chemical reactions based on NMR data, and a representation of chemical reactions from the reaction equation based on the physico-chemical and topological features of chemical bonds. NMR-based classification of photochemical and enzymatic reactions. Photochemical and metabolic reactions were classified by Kohonen Self-Organizing Maps (Kohonen SOMs) and Random Forests (RFs) taking as input the difference between the 1H NMR spectra of the products and the reactants. The development of such a representation can be applied in automatic analysis of changes in the 1H NMR spectrum of a mixture and their interpretation in terms of the chemical reactions taking place. Examples of possible applications are the monitoring of reaction processes, evaluation of the stability of chemicals, or even the interpretation of metabonomic data. A Kohonen SOM trained with a data set of metabolic reactions catalysed by transferases was able to correctly classify 75% of an independent test set in terms of the EC number subclass. Random Forests improved the correct predictions to 79%. With photochemical reactions classified into 7 groups, an independent test set was classified with 86-93% accuracy. The data set of photochemical reactions was also used to simulate mixtures with two reactions occurring simultaneously. Kohonen SOMs and Feed-Forward Neural Networks (FFNNs) were trained to classify the reactions occurring in a mixture based on the 1H NMR spectra of the products and reactants. Kohonen SOMs allowed the correct assignment of 53-63% of the mixtures (in a test set). Counter-Propagation Neural Networks (CPNNs) gave origin to similar results. The use of supervised learning techniques allowed an improvement in the results. They were improved to 77% of correct assignments when an ensemble of ten FFNNs were used and to 80% when Random Forests were used. This study was performed with NMR data simulated from the molecular structure by the SPINUS program. In the design of one test set, simulated data was combined with experimental data. The results support the proposal of linking databases of chemical reactions to experimental or simulated NMR data for automatic classification of reactions and mixtures of reactions. Genome-scale classification of enzymatic reactions from their reaction equation. The MOLMAP descriptor relies on a Kohonen SOM that defines types of bonds on the basis of their physico-chemical and topological properties. The MOLMAP descriptor of a molecule represents the types of bonds available in that molecule. The MOLMAP descriptor of a reaction is defined as the difference between the MOLMAPs of the products and the reactants, and numerically encodes the pattern of bonds that are broken, changed, and made during a chemical reaction. The automatic perception of chemical similarities between metabolic reactions is required for a variety of applications ranging from the computer validation of classification systems, genome-scale reconstruction (or comparison) of metabolic pathways, to the classification of enzymatic mechanisms. Catalytic functions of proteins are generally described by the EC numbers that are simultaneously employed as identifiers of reactions, enzymes, and enzyme genes, thus linking metabolic and genomic information. Different methods should be available to automatically compare metabolic reactions and for the automatic assignment of EC numbers to reactions still not officially classified. In this study, the genome-scale data set of enzymatic reactions available in the KEGG database was encoded by the MOLMAP descriptors, and was submitted to Kohonen SOMs to compare the resulting map with the official EC number classification, to explore the possibility of predicting EC numbers from the reaction equation, and to assess the internal consistency of the EC classification at the class level. A general agreement with the EC classification was observed, i.e. a relationship between the similarity of MOLMAPs and the similarity of EC numbers. At the same time, MOLMAPs were able to discriminate between EC sub-subclasses. EC numbers could be assigned at the class, subclass, and sub-subclass levels with accuracies up to 92%, 80%, and 70% for independent test sets. The correspondence between chemical similarity of metabolic reactions and their MOLMAP descriptors was applied to the identification of a number of reactions mapped into the same neuron but belonging to different EC classes, which demonstrated the ability of the MOLMAP/SOM approach to verify the internal consistency of classifications in databases of metabolic reactions. RFs were also used to assign the four levels of the EC hierarchy from the reaction equation. EC numbers were correctly assigned in 95%, 90%, 85% and 86% of the cases (for independent test sets) at the class, subclass, sub-subclass and full EC number level,respectively. Experiments for the classification of reactions from the main reactants and products were performed with RFs - EC numbers were assigned at the class, subclass and sub-subclass level with accuracies of 78%, 74% and 63%, respectively. In the course of the experiments with metabolic reactions we suggested that the MOLMAP / SOM concept could be extended to the representation of other levels of metabolic information such as metabolic pathways. Following the MOLMAP idea, the pattern of neurons activated by the reactions of a metabolic pathway is a representation of the reactions involved in that pathway - a descriptor of the metabolic pathway. This reasoning enabled the comparison of different pathways, the automatic classification of pathways, and a classification of organisms based on their biochemical machinery. The three levels of classification (from bonds to metabolic pathways) allowed to map and perceive chemical similarities between metabolic pathways even for pathways of different types of metabolism and pathways that do not share similarities in terms of EC numbers. Mapping of PES by neural networks (NNs). In a first series of experiments, ensembles of Feed-Forward NNs (EnsFFNNs) and Associative Neural Networks (ASNNs) were trained to reproduce PES represented by the Lennard-Jones (LJ) analytical potential function. The accuracy of the method was assessed by comparing the results of molecular dynamics simulations (thermal, structural, and dynamic properties) obtained from the NNs-PES and from the LJ function. The results indicated that for LJ-type potentials, NNs can be trained to generate accurate PES to be used in molecular simulations. EnsFFNNs and ASNNs gave better results than single FFNNs. A remarkable ability of the NNs models to interpolate between distant curves and accurately reproduce potentials to be used in molecular simulations is shown. The purpose of the first study was to systematically analyse the accuracy of different NNs. Our main motivation, however, is reflected in the next study: the mapping of multidimensional PES by NNs to simulate, by Molecular Dynamics or Monte Carlo, the adsorption and self-assembly of solvated organic molecules on noble-metal electrodes. Indeed, for such complex and heterogeneous systems the development of suitable analytical functions that fit quantum mechanical interaction energies is a non-trivial or even impossible task. The data consisted of energy values, from Density Functional Theory (DFT) calculations, at different distances, for several molecular orientations and three electrode adsorption sites. The results indicate that NNs require a data set large enough to cover well the diversity of possible interaction sites, distances, and orientations. NNs trained with such data sets can perform equally well or even better than analytical functions. Therefore, they can be used in molecular simulations, particularly for the ethanol/Au (111) interface which is the case studied in the present Thesis. Once properly trained, the networks are able to produce, as output, any required number of energy points for accurate interpolations.

In-situ X-ray diffraction studies during growth of Ni-Ti shape memory alloy films and their complementary ex-situ characterization

Shape Memory Alloy (SMA) Ni-Ti films have attracted much interest as functional and smart materials due to their unique properties. However, there are still important issues unresolved like formation of film texture and its control as well as substrate effects. Thus, the main challenge is not only the control of the microstructure, including stoichiometry and precipitates, but also the identification and control of the preferential orientation since it is a crucial factor in determining the shape memory behaviour. The aim of this PhD thesis is to study the optimisation of the deposition conditions of films of Ni-Ti in order to obtain the material fully crystallized at the end of the deposition, and to establish a clear relationship between the substrates and texture development. In order to achieve this objective, a two-magnetron sputter deposition chamber has been used allowing to heat and to apply a bias voltage to the substrate. It can be mounted into the six-circle diffractometer of the Rossendorf Beamline (ROBL) at the European Synchrotron Radiation Facility (ESRF), Grenoble, France, enabling an in-situ characterization by X-ray diffraction(XRD) of the films during their growth and annealing. The in-situ studies enable us to identify the different steps of the structural evolution during deposition with a set of parameters as well as to evaluate the effect of changing parameters on the structural characteristics of the deposited film. Besides the in-situ studies, other complementary ex-situ characterization techniques such as XRD at a laboratory source, Rutherford backscattering spectroscopy(RBS), Auger electron spectroscopy (AES), cross-sectional transmission electron microscopy (X-TEM), scanning electron microscopy (SEM), and electrical resistivity (ER) measurements during temperature cycling have been used for a fine structural characterization. In this study, mainly naturally and thermally oxidized Si(100) substrates, TiN buffer layers with different thicknesses (i.e. the TiN topmost layer crystallographic orientation is thickness dependent) and MgO(100) single crystals were used as substrates. The chosen experimental procedure led to a controlled composition and preferential orientation of the films. The type of substrate plays an important role for the texture of the sputtered Ni-Ti films and according to the ER results, the distinct crystallographic orientations of the Ni-Ti films influence their phase transformation characteristics.

Descargas luminescentes anómalas com cátodo magnetrão – descargas reactivas

Dissertação apresentada para a obtenção do Grau de Doutor em Engenharia Física, especialidade de Engenharia de Superfícies, pela Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia

Write-erase and read paper memory transistor

Applied Physics Letters, Vol.93, issue 20

Fluorescence in nanostructured fulleride films

Applied Physics Letters, 89

Chemical analysis of 17th century Millefiori glasses excavated in the Monastery of Sta. Clara‐a‐Velha: comparison with Venetian and façon‐de‐Venise production

Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para obtenção do grau de Mestre em Conservação e Restauro,Área de especialização Cerâmica e Vidro

A study on metallurgy and corrosion of ancient copper-based artefacts from the portuguese territory

Dissertação apresentada para a obtenção do Grau de Doutor em Conservação e Restauro, especialidade Ciências da Conservação, pela Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia