In this study, for recycling polyethylene terephthalate, a blend of recycled polyethylene terephthalate (RPET) and high-density polyethylene (HDPE) with maleic anhydride polyethylene (MAPE) and maleic anhydride-grafted styrene-ethylene/butylene-styrene (SEBS-g-MA) were used. The effect of compatibilizers in RPET was investigated by mechanical test (tensile and flexural tests), thermal test (differential scanning calorimetry (DSC)), and melt flow index test. The morphology of fracture surface of samples was investigated by scanning electron microscopy (SEM). The mechanical tests showed that elongation at break point and the fracture energy of samples with composition of RPET (70 wt%)/HDPE (15 wt%)/MAPE (15 wt%) and RPET (75 wt%)/HDPE (10 wt%)/SEBS-g-MA (15 wt%) increased significantly. Results of DSC test and SEM photography showed that ternary blend of RPET/HDPE/MAPE has better compatibility compared with RPET/ HDPE/SEBS-g-MA. SEM images showed that MAPE provides better bonding between RPET and HDPE compared with SEBS-g-MA. MAPE was dispersed in RPET better than SEBS-g-MA.
This paper presents a methodology for determination of the optimal material and processing parameters (i.e., nanoclay content, melt temperature, feeding rate, and screw speed) to maximize simultaneously tensile modulus and tensile strength of injection-molded PA-6/clay nanocomposites through coupling response surface method and genetic algorithm. The tensile tests on PA-6/clay nanocomposites are conducted to obtain tensile modulus and tensile strength values, and then analysis of variance is performed. The predicted models for tensile modulus and tensile strength are created by response surface method, and then the functions are optimized by a genetic algorithm code implemented in MATLAB. Acceptable agreement has been observed between the values of the process parameters predicted by the response surface method and genetic algorithm and those of the process parameters obtained through experimental measurements. This study shows that the response surface method coupled with the GA can be utilized effectively to find the optimum process variables in tensile test of PA-6/NC nanocomposites.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.