investigating the influence of nanoclosite particles on the mechanical properties of polystyrene using artificial neural networks

the synthesized polystyrene has weaknesses in terms of mechanical, physical and thermal properties which limit the use of this polymer. therefore, the use of the mixtures of polymers can improve these properties. different parameters like the mixing speed can affect the quality of the properties of the polymer being prepared from the mixture of several polymers. in this study, different percentages of nanocomposites in different stirring speeds have been added to polystyrene. different tests have been performed on the prepared polymer and investigating the tests shows that in different stirring speeds the values of the tensile strength and impact resistance of the prepared polymer can be increased while the values of the vicat softening temperature (vicat) and melt flow index (mfi) test numbers remain constant. the obtained results from the laboratory data have been simulated by artificial neural networks (anns) in order to predict the results for the points which have not been tested and the simulated results show that the laboratory data covered the simulated data perfectly. the results of tests show that by increasing nanoparticles, the resistance of the polymer against impacts will be increased and in addition, increasing the rate of the stirrer causes all other values of tests to increase.