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The right selection of the type and the number of driver nodes, play an important role in improving the controllability and the performance of the dynamical networks. In this paper the controllability and the performance of a network has been studied when a new approach for selecting the driver nodes, based on the three main node centrality criteria, has been proposed. For each criterion, the percentage of the least number of driver nodes to achieve the desired performance has been calculated for several network model structures. The results for pure random networks show that for the ‘’betweenness centrality criterion’’ the number of driver nodes is minimal. Similar results hold for Small World networks subject to the fact that for dense, the number of driver nodes increases. It is shown that the ‘’closseness centrality criterion’’ is the proper choice for the State Free networks especially when the network is dense. Another important result is that in Small World networks, increasing the nearest neighborhood coefficient, decrease the number of driver nodes for a desired performance. Similar results hold for Scale Free networks where increasing the heterogeneity coefficient improves the network pinning controllability.

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The aim of present work is the investigation of polypropylene/graphene oxide nanocamposies. In this work, the reinforcing effects of the graphene oxide nanoparticles on the mechanical and thermal properties of the nonpolar polypropylene are examined. There is two main challenges to improve the properties of polypropylene by graphene oxide nanoparticles. First, the nanoparticles have not suitable dispersion in polymer matrix. Furthermore, there is not sufficient adhesion between nanoparticle and polymer chains. In this study, the graphene oxide (GO) surface is modified by a linear alkyl chain via a bimolecular nucleophilic substitution reaction between the oxygen groups of GO and reactants to promote the homogeneous dispersion of GO in the organic solvent and increasing the interfacial adhesion between the graphene oxide and polymer matrix. The presence of the alkyl groups on the surface of graphene oxide nanoparticles is characterized by FT-IR. To prevent the AGO aggregation in the polypropylene, the solution-blending method is used to prepare the nanocomposites with 0.1, 0.3, 0.5 wt% AGO. The SEM images confirmed the appropriate dispersion of the graphene oxide in the composites. The stress-strain analysis, dynamic-mechanical thermal analysis (DMTA), and thermal gravimetric analysis (TGA) are performed to investigate the mechanical and thermal properties of nanocomposites. The results demonstrated that the Young’s modulus of the polymer are improved by 20, 30 and 34% with adding 0.1, 0.3 and 0.5% AGO, respectively. Also the 10% mass loss temperature for 0.1, 0.3 and 0.5% AGO nanocomposites compared to neat polypropylene increased by 2, 8, 12 C0, respectively.