The influence of matrix mediated hopping conductivity, filler concentration, aspect ratio and orientation on the electrical response of carbon nanotube/polymer nanocomposites

A model to simulate the conductivity of carbon nanotube/polymer nanocomposites is presented. The proposed model is based on hopping between the fillers. A parameter related to the influence of the matrix in the overall composite conductivity is defined. It is demonstrated that increasing the aspect ratio of the fillers will increase the conductivity. Finally, it is demonstrated that the alignment of the filler rods parallel to the measurement direction results in higher conductivity values, in agreement with results from recent experimental work.

The influence of the dispersion method on the electrical properties of vapor-grown carbon nanofiber/epoxy composites

The influence of the dispersion of vapor-grown carbon nanofibers (VGCNF) on the electrical properties of VGCNF/ Epoxy composites has been studied. A homogenous dispersion of the VGCNF does not imply better electrical properties. In fact, it is demonstrated that the most simple of the tested dispersion methods results in higher conductivity, since the presence of well-distributed nanofiber clusters appears to be a key factor for increasing composite conductivity.

Energy harvesting performance of piezoelectric electrospun polymer fibers and polymer/ceramic composites

The energy harvesting efficiency of electrospun poly(vinylidene fluoride), its copolymer vinylidene fluoride-trifluoroethylene and composites of the later with piezoelectric BaTiOon interdigitated electrodes has been investigated. Further, a study of the influence of the electrospinning processing parameters on the size and distribution of the composites fibers has been performed. It is found that the best energy harvesting performance is obtained for the pure poly(vinylidene fluoride) fibers, with power outputs up to 0.03 W and 25 W under low and high mechanical deformation. The copolymer and the composites show reduced power output due to increased mechanical stiffness. The obtained values, among the largest found in the literature, the easy processing and the low cost and robustness of the polymer, demonstrate the applicability of the developed system.

Carbon Nanofiber Type and Content Dependence of the Physical Properties of Carbon Nanofiber Reinforced Polypropylene Composites

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.

Multiple centroid method to evaluate the adaptability of alfalfa genotypes

This study aimed to evaluate the efficiency of multiple centroids to study the adaptability of alfalfa genotypes (Medicago sativa L.). In this method, the genotypes are compared with ideotypes defined by the bissegmented regression model, according to the researcher's interest. Thus, genotype classification is carried out as determined by the objective of the researcher and the proposed recommendation strategy. Despite the great potential of the method, it needs to be evaluated under the biological context (with real data). In this context, we used data on the evaluation of dry matter production of 92 alfalfa cultivars, with 20 cuttings, from an experiment in randomized blocks with two repetitions carried out from November 2004 to June 2006. The multiple centroid method proved efficient for classifying alfalfa genotypes. Moreover, it showed no unambiguous indications and provided that ideotypes were defined according to the researcher's interest, facilitating data interpretation.