Thermoplastic vulcanizate nanocomposites based on thermoplastic polyurethane and millable polyurethane blends reinforced with organoclay prepared by melt intercalation technique: Optimization of processing parameters via statistical methods

Abstract

Statistical approaches including Taguchi design of experiments (DOE), analysis of variance (ANOVA), and multiple linear regression analysis were employed to determine optimum processing conditions for successful preparation of a thermoplastic vulcanizate nanocomposite (TPVNC) based on thermoplastic polyurethane (TPU)/millable polyurethane (MPU) blend reinforced with an organoclay (TPU/MPU/organoclay = 50/50/3 wt/wt/wt) using an internal mixer. Total numbers of mixing layouts were designed by the application of Taguchi's orthogonal array (OA) methodology based on three parameters and three levels in the L9 selector matrix model. Mechanical properties of all runs were measured and fitted into the statistical software to determine signal to noise (S/N) ratio. Ranks of the parameters were determined based on the delta statistics of the larger is better case of the S/N ratio. The ANOVA parameters were analyzed and percentage contribution of each factor, along with the correlation coefficient of each variable, was measured. The multiple linear regression models for each property were correlated with the parameters through mathematical equations. Fourier transform infrared (FTIR) analysis was performed to examine any interfacial interactions between polyurethane matrix and organoclay. X-ray diffraction (XRD) analysis and field emission transmission electron microscope (FETEM) were employed to analyze the dispersion of organoclays in the polymer matrix. Field emission scanning electron microscope (FESEM) was employed to observe cryo-fractured morphology. Dynamic mechanical analysis (DMA) and dynamic shear rheometer (DSR) were used to investigate dynamic mechanical properties and rheological properties of the trials, respectively. Based on all of these characterizations, an optimum processing condition was determined. (c) 2012 Wiley Periodicals, Inc. J. Appl. Polym. Sci., 2013