2 resultados para Highly resistive layer

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


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The variation of the physical properties of four differ- ent carbon nanofibers (CNFs), based-polymer nano- composites incorporated in the same polypropylene (PP) matrix by twin-screw extrusion process was investigated. Nanocomposites fabricated with CNFs with highly graphitic outer layer revealed electrical isolation-to-conducting behaviors as function of CNF’s content. Nanocomposites fabricated with CNFs with an outer layer consisting on a disordered pyro- litically stripped layer, in contrast, revealed better mechanical performance and enhanced thermal sta- bility. Further, CNF’s incorporation into the polymer increased the thermal stability and the degree of crystallinity of the polymer, independently on the filler content and type. In addition, dispersion of the CNFs’ clusters in PP was analyzed by transmitted light opti- cal microscopy, and grayscale analysis (GSA). The results showed a correlation between the filler concentration and the variance, a parameter which measures quantitatively the dispersion, for all composites. This method indicated a value of 1.4 vol% above which large clusters of CNFs cannot be dispersed effectively and as a consequence only slight changes in mechanical performance are observed. Finally, this study establishes that for tailoring the physical properties of CNF based-polymer nanocomposites, both adequate CNFs structure and content have to be chosen.

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Nowadays despite improvements in usability and intuitiveness users have to adapt to the proposed systems to satisfy their needs. For instance, they must learn how to achieve tasks, how to interact with the system, and fulfill system's specifications. This paper proposes an approach to improve this situation enabling graphical user interface redefinition through virtualization and computer vision with the aim of increasing the system's usability. To achieve this goal the approach is based on enriched task models, virtualization and picture-driven computing.