The reinforcement mechanism of carbon nanotubes (CNT) on styrene butadiene rubber is studied through dynamic and swelling tests. Compounds containing carbon black (CB) and an unfilled one were prepared for comparison purposes. The dynamic properties are interpreted through the Maier-Göritz model to distinguish the contributions of stable and unstable crosslinks to the storage modulus, finding that the unstable ones become more relevant in samples containing a CNT concentration higher than 5 phr. In addition, the crosslinks density estimated by swelling and the stable contribution obtained with dynamical properties present the same tendency with the CNT amount. The former presents lower values, which can be explained considering that only stable crosslinks remain in the equilibrium-swollen state, while in the second one both stable and unstable are considered. In addition, differences in the filler-polymer interaction mechanisms are observed according to the morphology and aspect ratio of CNT in contrast to CB.
The study of the reinforcement network in elastomer compounds is one of the most relevant issues for the application of these materials because their properties are strongly dependent on the obtained morphology. To this regard, the viscoelastic and dielectric behavior of vulcanized styrene butadiene rubber (SBR) reinforced with different amounts of carbon nanotubes (CNT) have been investigated and compared with the vulcanized unfilled SBR and the vulcanized SBR samples reinforced with a conventional amount of carbon black (40 phr). Differential scanning calorimetry (DSC) measurements have been carried out to highlight possible differences of the glass transition temperatures for all the reinforced compounds. The percolation threshold value of the nanocomposite samples has been estimated by dielectric analysis. Finally, dynamic mechanical analysis (DMA) measurements have been performed in tensile mode in the temperature range of −60 to 80 °C to obtain both E′ and E′′. From these experimental data, the master curve for each sample has been estimated by using the time–temperature superposition principle in combination with the vertical shift approach. From the analysis of this latter, the activation energy, associated to the thermal movement of the reinforcement network, has been calculated to better elucidate the reinforcement mechanism in the nanocomposites.
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