Effect of acid or alkaline catalyst and of different capping agents on the optical properties of CdS nanoparticles incorporated within a diureasil hybrid matrix

CdS nanoparticles (NPs) were synthesized using colloidal methods and incorporated within a diureasil hybrid matrix. The surface capping of the CdS NPs by 3-mercaptopropyltrimethoxysilane (MPTMS) and 3-aminopropyltrimethoxysilane (APTMS) organic ligands during the incorporation of the NPs within the hybrid matrix has been investigated. The matrix is based on poly(ethylene oxide)/poly(propylene oxide) chains grafted to a siliceous skeleton through urea bonds and was produced by sol–gel process. Both alkaline and acidic catalysis of the sol–gel reaction were used to evaluate the effect of each organic ligand on the optical properties of the CdS NPs. The hybrid materials were characterized by absorption, steady-state and time-resolved photoluminescence spectroscopy and High Resolution Transmission Electron Microscopy (HR-TEM). The preservation of the optical properties of the CdS NPs within the diureasil hybrids was dependent on the experimental conditions used. Both organic ligands (APTMS and MPTMS) demonstrated to be crucial in avoiding the increase of size distribution and clustering of the NPs within the hybrid matrix. The use of organic ligands was also shown to influence the level of interaction between the hybrid host and the CdS NPs. The CdS NPs showed large Stokes shifts and long average lifetimes, both in colloidal solution and in the xerogels, due to the origin of the PL emission in surface states. The CdS NPs capped with MPTMS have lower PL lifetimes compared to the other xerogel samples but still larger than the CdS NPs in the original colloidal solution. An increase in PL lifetimes of the NPs after their incorporation within the hybrid matrix is related to interaction between the NPs and the hybrid host matrix.

Thin films composed of Ag nanoclusters dispersed in TiO2: Influence of composition and thermal annealing on the microstructure and physical responses

Noble metal powders containing gold and silver have been used for many centuries, providing different colours in the windows of the medieval cathedrals and in ancient Roman glasses. Nowadays, the interest in nanocomposite materials containing noble nanoparticles embedded in dielectric matrices is related with their potential use for a wide range of advanced technological applications. They have been proposed for environmental and biological sensing, tailoring colour of functional coatings, or for surface enhanced Raman spectroscopy. Most of these applications rely on the so-called localised surface plasmon resonance absorption, which is governed by the type of the noble metal nanoparticles, their distribution, size and shape and as well as of the dielectric characteristics of the host matrix. The aim of this work is to study the influence of the composition and thermal annealing on the morphological and structural changes of thin films composed of Ag metal clusters embedded in a dielectric TiO2 matrix. Since changes in size, shape and distribution of the clusters are fundamental parameters for tailoring the properties of plasmonic materials, a set of films with different Ag concentrations was prepared. The optical properties and the thermal behaviour of the films were correlated with the structural and morphological changes promoted by annealing. The films were deposited by DC magnetron sputtering and in order to promote the clustering of the Ag nanoparticles the as-deposited samples were subjected to an in-air annealing protocol. It was demonstrated that the clustering of metallic Ag affects the optical response spectrum and the thermal behaviour of the films.

Microstructural evolution of Au/TiO2 nanocomposite films: The influence of Au concentration and thermal annealing

Nanocomposite thin films consisting of a dielectric matrix, such as titanium oxide (TiO2), with embedded gold (Au) nanoparticles were prepared and will be analysed and discussed in detail in the present work. The evolution of morphological and structural features was studied for a wide range of Au concentrations and for annealing treatments in air, for temperatures ranging from 200 to 800 °C. Major findings revealed that for low Au atomic concentrations (at.%), there are only traces of clustering, and just for relatively high annealing temperatures, T ≥ 500 °C. Furthermore, the number of Au nanoparticles is extremely low, even for the highest annealing temperature, T = 800 °C. It is noteworthy that the TiO2 matrix also crystallizes in the anatase phase for annealing temperatures above 300 °C. For intermediate Au contents (5 at.% ≤ CAu ≤ 15 at.%), the formation of gold nanoclusters was much more evident, beginning at lower annealing temperatures (T ≥ 200 °C) with sizes ranging from 2 to 25 nm as the temperature increased. A change in the matrix crystallization from anatase to rutile was also observed in this intermediate range of compositions. For the highest Au concentrations (> 20 at.%), the films tended to form relatively larger clusters, with sizes above 20 nm (for T ≥ 400 °C). It is demonstrated that the structural and morphological characteristics of the films are strongly affected by the annealing temperature, as well as by the particular amounts, size and distribution of the Au nanoparticles dispersed in the TiO2 matrix.

Sistema de apoio à decisão clínica: quality of life system

Dissertação de mestrado integrado em Engenharia e Gestão de Sistemas de Informação

Segmentação de imagens fetais com potencial para desenvolvimento de ferramentas de apoio ao diagnóstico

Programa Doutoral em Engenharia Eletrónica e de Computadores

Single line for assembly just-in-sequence multiple models

Programa Doutoral em Líderes para as Indústrias Tecnológicas

A network approach to brain aging through multimodal neuroimaging

Tese de Doutoramento em Ciências da Saúde.

Transmission and progression to disease of Mycobacterium tuberculosis phylogenetic lineages in The Netherlands

The aim of this study was to determine if mycobacterial lineages affect infection risk, clustering, and disease progression among Mycobacterium tuberculosis cases in The Netherlands. Multivariate negative binomial regression models adjusted for patient-related factors and stratified by patient ethnicity were used to determine the association between phylogenetic lineages and infectivity (mean number of positive contacts around each patient) and clustering (as defined by number of secondary cases within 2 years after diagnosis of an index case sharing the same fingerprint) indices. An estimate of progression to disease by each risk factor was calculated as a bootstrapped risk ratio of the clustering index by the infectivity index. Compared to the Euro-American reference, Mycobacterium africanum showed significantly lower infectivity and clustering indices in the foreign-born population, while Mycobacterium bovis showed significantly lower infectivity and clustering indices in the native population. Significantly lower infectivity was also observed for the East African Indian lineage in the foreign-born population. Smear positivity was a significant risk factor for increased infectivity and increased clustering. Estimates of progression to disease were significantly associated with age, sputum-smear status, and behavioral risk factors, such as alcohol and intravenous drug abuse, but not with phylogenetic lineages. In conclusion, we found evidence of a bacteriological factor influencing indicators of a strain's transmissibility, namely, a decreased ability to infect and a lower clustering index in ancient phylogenetic lineages compared to their modern counterparts. Confirmation of these findings via follow-up studies using tuberculin skin test conversion data should have important implications on M. tuberculosis control efforts.

HOXA9 as a key regulator in glioma initiation, aggressiveness and response to therapy

Tese de Doutoramento em Ciências da Saúde

Visual data analysis in air traffic management

Visual data mining, multi-dimensional scaling, POLARMAP, Sammon's mapping, clustering, outlier detection

Online-Data-Mining auf Datenströmen : Methoden zur Clusteranalyse und Klassifikation

Online Data Mining, Data Streams, Classification, Clustering

Temporal and spatial variation of rocky shores intertidal benthic communities in Southeast Brazil

The relationships between environmental factors and temporal and spatial variations of benthic communities of three rocky shores of the state of Espírito Santo, Southeast Brazil, were studied. Sampling was conducted every three months, from August 2006 to May 2007, using intersection points. Chthamalus bisinuatus (Pilsbry, 1916) (Crustacea) and Brachidontes spp. (Mollusca) were the most abundant taxa, occupying the upper level of the intertidal zone of the rocky shore. The species richness was higher at the lower levels. The invasive species Isognomon bicolor (C. B. Adams, 1845) (Mollusca) occurred at low densities in the studied areas. The clustering analysis dendrogram indicated a separation of communities based on exposed and sheltered areas. According to the variance analyses, the communities were significantly different among the studied areas and seasons. The extent of wave exposure and shore slope influenced the species variability. The Setibão site showed the highest diversity and richness, most likely due to greater wave exposure. The communities showed greater variation in the lower levels where environmental conditions were less severe, relative to the other levels.

Are one factor logarithmic volatility models useful to fit the features of financial data? An application to microsoft data.

This paper provides empirical evidence that continuous time models with one factor of volatility, in some conditions, are able to fit the main characteristics of financial data. It also reports the importance of the feedback factor in capturing the strong volatility clustering of data, caused by a possible change in the pattern of volatility in the last part of the sample. We use the Efficient Method of Moments (EMM) by Gallant and Tauchen (1996) to estimate logarithmic models with one and two stochastic volatility factors (with and without feedback) and to select among them.

Repeated games played in a network

Delayed perfect monitoring in an infinitely repeated discounted game is modelled by letting the players form a connected and undirected network. Players observe their immediate neighbors' behavior only, but communicate over time the repeated game's history truthfully throughout the network. The Folk Theorem extends to this setup, although for a range of discount factors strictly below 1, the set of sequential equilibria and the corresponding payoff set may be reduced. A general class of games is analyzed without imposing restrictions on the dimensionality of the payoff space. This and the bilateral communication structure allow for limited results under strategic communication only. As a by-product this model produces a network result; namely, the level of cooperation in this setup depends on the network's diameter, and not on its clustering coefficient as in other models.

A nonlinear threshold model for the dependence of extremes of stationary sequences

One of the main implications of the efficient market hypothesis (EMH) is that expected future returns on financial assets are not predictable if investors are risk neutral. In this paper we argue that financial time series offer more information than that this hypothesis seems to supply. In particular we postulate that runs of very large returns can be predictable for small time periods. In order to prove this we propose a TAR(3,1)-GARCH(1,1) model that is able to describe two different types of extreme events: a first type generated by large uncertainty regimes where runs of extremes are not predictable and a second type where extremes come from isolated dread/joy events. This model is new in the literature in nonlinear processes. Its novelty resides on two features of the model that make it different from previous TAR methodologies. The regimes are motivated by the occurrence of extreme values and the threshold variable is defined by the shock affecting the process in the preceding period. In this way this model is able to uncover dependence and clustering of extremes in high as well as in low volatility periods. This model is tested with data from General Motors stocks prices corresponding to two crises that had a substantial impact in financial markets worldwide; the Black Monday of October 1987 and September 11th, 2001. By analyzing the periods around these crises we find evidence of statistical significance of our model and thereby of predictability of extremes for September 11th but not for Black Monday. These findings support the hypotheses of a big negative event producing runs of negative returns in the first case, and of the burst of a worldwide stock market bubble in the second example. JEL classification: C12; C15; C22; C51 Keywords and Phrases: asymmetries, crises, extreme values, hypothesis testing, leverage effect, nonlinearities, threshold models