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The effect of various ingredients – nanoclay (NC), azodicarbonamaide (ADCA), paraloeid K-400 and calcium stearate (Ca.St) – on thermal behavior of melt blended poly (vinyl chloride)/NC nanocomposites was investigated. Combinations of two artificial intelligence algorithms were performed for modeling of the systems. The formulation ingredients affect the thermal features of the compounds. Upon increasing the effect of various ingredients, i.e. NC, ADCA, K-400 and Ca.St, an increase in ash content was observed, hence, the thermal stability increased. The effect of ingredients on initial degradation temperature (T5%) and half degradation temperature (T50%) was not obvious. The artificial neural network (model) and the clonal selection algorithm (optimizer) were performed for proper modeling of the systems. These models were used to determine the role of T5%, T50% and char based on the contents of ingredients. The result successfully modeled the process parameters.

Fusion behavior of poly(vinyl chloride) (PVC) compounds plays an important role in the development of physical properties of processed material. The fusion characteristics in PVC processing are governed by material variables that affect the fusion with some interactions. In this research, the aim was to characterize the effects of formulation ingredients on fusion characteristics of PVC. Four material parameters, including the contents of nanoclay (NC), azodicarbonamide, calcium stearate, and processing aid, are proposed as affecting variables. The fusion time (FT) as well as fusion factor (FF) are considered fusion indicators and are experimentally determined in some different levels of affecting parameters. The multivariable regression analysis (MRA) and the Artificial Neural Network (ANN) modeling are considered as two analytical methods. The regression analysis result for the FT denotes, in part, significant linear and quadratic effects of NC and also its significant interactions with azodicarbonamide and calcium stearate, whereas that of FF indicates only a linear effect of NC. ANN modeling is performed with a three‐layer (input, hidden, and output) neural network. The results of the comparison of the MRA and ANN predictions with experimental values are reported as the correlation coefficient (R2), mean‐square error, and mean absolute percentage error for both FF and FT parameters. The obtained values clearly denote that the ANN results are more precise and especially more general than those of MRA. However, in the case of FT, improvement of the ANN modeling is much greater than that of FF. J. VINYL ADDIT. TECHNOL., 21:147–155, 2015. © 2014 Society of Plastics Engineers

Polyelectrolyte membrane (PEM) is an important part of PEM fuel cell. Nafion is a commercially known membrane which gives the satisfactory result in PEM fuel cell operating at low temperature. Present research paper includes functionalization of Poly(ether ether ketone) (PEEK) polymer with phosphonic acid group. The functionalization was done with the help of nickel-based catalyst. Further, the polymer was characterized by the FTIR, EDAX, DSC, TGA, and 1H NMR, and it was found that PEEK polymer was functionalized with phosphonic acid group with good thermal stability in comparison to virgin PEEK. Finally, the thin films of functionalized polymer were prepared by solution casting method, and proton conductivity of film samples was measured by impedance spectra whose value was found satisfactory with good thermal stability in comparison to commercially available Nafion membrane.

The crystallization behavior of semi-crystalline plastics plays a vital role in the development of properties of plastics. The present study examines the effect of addition of 1-5% nano talc filler particles on the nucleation behavior and crystal morphology. Differential Scanning Calorimetry was used to study the dynamic crystallization kinetics of PEEK with different loadings of nano talc filler. The crystalline morphology and non-isothermal kinetics were investigated. Crystallization behaviour was studied using Avrami equation. It is found that the addition of nano-talc enhances the rate of nucleation; however, the growth rate of the crystals reduces.