Polymer Engineering and Technology,
F. Ader; E. Sharifzadeh
Abstract
In this study, the main purpose has been to investigate the behavior of the nanoparticles with different structures and similar based materials in polymer nanocomposites. To this end, different samples, containing PS as the matrix, and layered graphene oxide (GO) and/or hollow graphene oxide nanoparticles ...
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In this study, the main purpose has been to investigate the behavior of the nanoparticles with different structures and similar based materials in polymer nanocomposites. To this end, different samples, containing PS as the matrix, and layered graphene oxide (GO) and/or hollow graphene oxide nanoparticles (HGO), were prepared via the melt mixing process and were subjected to heat conduction and tensile tests. To evaluate all features of the interaction between the polymer phase and the nanoparticles, a thermal/mechanical analytical model was proposed and the results were used to simulate the behavior of specific geometrical structures, corresponding to the real samples, under different thermal/mechanical conditions. The results showed good agreement between the obtained experimental data and simulation/analytical model interpretations. In addition, it was found that the HGO nanoparticle had such a good performance in enhancing the thermal and mechanical properties of the nanocomposite, due to its unique structure.
E. Sharifzadeh; E. Tohfegar; M. Safajou Jahankhanemlou
Abstract
In this study, a comprehensive model was proposed in order to predict the tensile strength of nanocomposites considering the effects of the random orientation of nanoparticles, interphase properties and also the inevitable aggregation/agglomeration phenomenon. The model was structured based on the nanoparticle ...
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In this study, a comprehensive model was proposed in order to predict the tensile strength of nanocomposites considering the effects of the random orientation of nanoparticles, interphase properties and also the inevitable aggregation/agglomeration phenomenon. The model was structured based on the nanoparticle shape (e. g. platelet, cylindrical and spherical) so it could perfectly demonstrate the random orientation. It was revealed that neglecting the aggregation/agglomeration of the nanoparticles ( ) drastically rises the prediction error to about 12% while considering decreased the error to about 7-9% for samples with low content of nanoparticles (< 0.5 Vol.). Moreover, the model was completely capable of characterizing the polymer/particle interphase regardless of the polymer type and the nanoparticles shape. Model verification was accomplished by comparing its predictions with the tensile test results of the prepared nanocomposite samples of different compositions (Polystyrene/Silica, Polystyrene/Graphene Oxide and Polystyrene/Carbon nano-tubes). Also, the samples were subjected to TEM in order to qualitatively evaluate the behavior of the different shaped nanoparticles in the polystyrene matrix.