6 resultados para Implication and aggregation functions properties

em CiencIPCA - Instituto Politécnico do Cávado e do Ave, Portugal


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Composites of styrene–butadiene–styrene (SBS) block copolymer with multiwall carbon nanotubes were processed by solution casting to investigate the influence of filler content, the different ratios of styrene/butadiene in the copolymer and the architecture of the SBS matrix on the electrical, mechanical and electro-mechanical properties of the composites. It was found that filler content and elastomer matrix architecture influence the percolation threshold and consequently the overall composite electrical conductivity. Themechanical properties aremainly affected by the styrene and filler content. Hopping between nearest fillers is proposed as the main mechanism for the composite conduction. The variation of the electrical resistivity is linear with the deformation. This fact, together with the gauge factor values in the range of 2–18, results in appropriate composites to be used as (large) deformation sensors.

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Composites of styrene–butadiene–styrene (SBS) block copolymer with multiwall carbon nanotubes were processed by solution casting to investigate the influence of filler content, the different ratios of styrene/butadiene in the copolymer and the architecture of the SBS matrix on the electrical, mechanical and electro-mechanical properties of the composites. It was found that filler content and elastomer matrix architecture influence the percolation threshold and consequently the overall composite electrical conductivity. The mechanical properties are mainly affected by the styrene and filler content. Hopping between nearest fillers is proposed as the main mechanism for the composite conduction. The variation of the electrical resistivity is linear with the deformation. This fact, together with the gauge factor values in the range of 2–18, results in appropriate composites to be used as (large) deformation sensors.

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This study is focused on the establishment of relationships between the injection moulding processing conditions, the applied thermomechanical environment (TME) and the tensile properties of talc-filled polypropylene,adopting a new extended concept of thermomechanical indices (TMI). In this approach, TMI are calculated from computational simulations of the moulding process that characterise the TME during processing, which are then related to the mechanical properties of the mouldings. In this study, this concept is extended to both the filling and the packing phases, with new TMI defined related to the morphology developed during these phases. A design of experiments approach based on Taguchi orthogonal arrays was adopted to vary the injection moulding parameters (injection flow rate, injection temperature, mould wall temperature and holding pressure), and thus, the TME. Results from analysis of variance for injection-moulded tensile specimens have shown that among the considered processing conditions, the flow rate is the most significant parameter for the Young’s modulus; the flow rate and melt temperature are the most significant for the strain at break; and the holding pressure and flow rate are the most significant for the stress at yield. The yield stress and Young’s modulus were found to be governed mostly by the thermostress index (TSI, related to the orientation of the skin layer), whilst the strain at break depends on both the TSI and the cooling index (CI, associated to the crystallinity degree of the core region). The proposed TMI approach provides predictive capabilities of the mechanical response of injection-moulded components, which is a valuable input during their design stage.

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This work reports on the effect of carbon nanotube aggregation on the electrical conductivity and other network properties of polymer/carbon nanotube composites by modeling the carbon nanotubes as hard-core cylinders. It is shown that the conductivity decreases for increasing filler aggregation, and that this effect is more significant for higher cylinder volume fractions. It is also demonstrated, for volume fractions at which the giant component is present, that increasing the fraction of cylinders within clusters leads to a break of the giant component and the formation of a set of finite clusters. The decrease of the giant component with the increase of the fraction of cylinders within the cluster can be related to a decrease of the spanning probability due to a decrease of the number of cylinders between the clusters. Finally, it is demonstrated that the effect of aggregation can be understood by employing the network theory.

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The objective of this paper is to provide empirical evidence on the determinants of gender wage inequality in the Portuguese tourism industry. Relying on firm level wage equations and production functions, gender wage and productivity differentials are estimated and then compared in order to infer whether observed gender disparities are justifiable on the grounds that women are relatively less productive than men, or instead disparities are due to gender wage discrimination. This approach is applied to tourism industry data gathered in the matched employer-employee data set Quadros de Pessoal (Employee Records). The main findings indicate that female employees in the tourism industry in Portugal are less productive than their male colleagues and that gender differences in wages are fully explained by gender differences in productivity.

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Tourism represents a major economic activity in Portugal, with an enormous wealth and employment growth potential. A significant proportion of jobs in the industry tourism are occupied by women, given that this industry is characterized by a relatively higher percentage of female employees. Despite the evidence of female progress with regard to their role in the Portuguese labor market, women continue to earn less than their male counterparts. This is clearly the case of the tourism industry, where statistics reveal a persistent gender wage gap. The objective of this paper is to provide empirical evidence on the determinants of gender wage inequality in the tourism industry in northern Portugal. Relying on firm-level wage equations and production functions, gender wage and productivity differentials are estimated and then compared. The comparison of these differentials allows inferring whether observed wage disparities are attributable to relatively lower female productivity, or instead disparities are due to gender wage discrimination. This approach is applied to tourism industry data gathered in the matched employer-employee data set Quadros de Pessoal (Employee Records). The main findings indicate that female employees in the tourism industry in northern Portugal are less productive than their male colleagues and that gender differences in wages are fully explained by gender differences in productivity.