Article citationsMore>>

Al-Mashat, L., Shin, K., Kalantar-Zadeh, K., Plessis, D.J., Han, H.S., Kojima, R.W., Kaner, R.B., Li, D., Gou, X., Ippolito, S.J. and Wlodarski, W. (2010) Graphene/Polyaniline Nanocomposite for Hydrogen Sensing. The Journal of Physical Chemistry C, 114, 16168-16173.
https://doi.org/10.1021/jp103134u

has been cited by the following article:

• TITLE: Effect of Carbon Fillers in Ultrahigh Molecular Weight Polyethylene Matrix Prepared by Twin-Screw Extrusion

  AUTHORS: Luiz Felipe M. Rocha, Suellem B. Cordeiro, Leonardo C. Ferreira, Flávio James H. Ramos, Maria de Fátima Marques

  KEYWORDS: Polyolefin, Blend, Oxidized Graphite, Expanded Graphite, Polyethylene Composites

  JOURNAL NAME: Materials Sciences and Applications, Vol.7 No.12, December 14, 2016

  ABSTRACT: Oxidized (GO) and expanded (G-Exp) graphite were employed to prepare composites with ultrahigh molecular weight polyethylene (UHMWPE) matrix using masterbatches of polyethylene with different compositions. The materials and a blend of UHMWPE/HDPE were prepared by extrusion and their properties were evaluated. The effect of carbon fillers on the crystalline structure, thermo dynamic-mechanical (DMTA) and thermal properties (melting and crystallization temperatures) of the composites were discussed. The thermogravimetric analysis (TGA), differential scanning calorimetry (DSC) and wide-angle X-ray diffraction (WAXD) measurements showed that the addition of masterbatch with GO and G-Exp significantly increased the crystallite size of composites, increasing the temperatures of melting, degradation, glass transition and the degree of crystallinity of polyethylene. DMTA analysis indicated the storage and loss moduli of composites in relation to neat UHMWPE, the blend and UHMWPE/composites. SEM micrographs showed a flatter, continuous and uniform surface meaning a compact lamellar structure. The present work resulted in interesting findings on the effects of GO on the crystalline structures, mechanical and thermal properties of UHMWPE, which can lead to generalizations useful for future work.