In the present work, ethylene-propylene block copolymer (EP90) and ethylene-propylene random copolymer (EPR) were separated from a PP/EPR in-reactor alloy. The EP90 and EPR were then blended with neat isotactic polypropylene (PP) at various proportions to obtain ternary blends. The isothermal crystallization kinetics and morphology of the ternary blends were studied and were compared with those of PP/EP90 binary blend. It is observed that the Avrami exponent increases with crystallization temperature for all the blends, but the PP/EP90/EPR ternary blends compared to the PP/EP90 binary blend exhibit larger Avrami exponents. The crystallization rate decreases as the crystallization temperature increases, as it is indicated by the increase of crystallization half-time. At the same crystallization temperature, the PP/EP90 binary blend exhibits the slowest crystallization rate. The data of crystallization kinetics were also analyzed with Hoffman-Lauritzen crystallization regime theory. It is found that all the blends crystallize in regime III. The increase in the content of EPR in the ternary blends is followed by increases in secondary nucleation constant, the free energy of the chain folding surface, and the chain folding work. The blends were etched with xylene at room temperature and at 80°C to remove EPR and EP90, respectively, and their morphology was studied with scanning electronic microscopy (SEM). The SEM results reveal that the block component EP90 is partially miscible with both PP and EPR, leading to increase in both domain number and domain size. Since both EPR and EP90 retard crystallization of PP in the PP/EPR and PP/EP90 binary blends, we speculate that the miscibility of EPR and EP90 can weaken the interference of EP90 on crystallization of neat PP.

The s tudy was conducted in the actual world-scale olefin plant with a focus on measuring the impact of identified controlled variables at the s team cracker furnace towards the propylene yield. Surface response analysis was conducted in the Minitab software version 20 using the his torical data after the clearance of both the outliers and residuals to ensure the analysis was conducted as normal data. Surface response analysis is a robus t mathematical and s tatis tical approach that is having a good potential to be sys tematically utilized in the actual large-scale olefin plant as an alternative to the expensive olefin simulation software for process monitoring. The analysis was conducted to forecas t the maximum propylene yield in the s tudied plant with careful consideration to select only significant variables, represented by a variance inflation factor (VIF) <10 and p-value <0. 05 in the analysis of variance (ANOVA) table. The final model successfully concluded that propylene yield in the s tudied plant was contributed by the factors of 0. 00496, 0. 00204, and-3. 96 of hearth burner flow, dilution s team flow, and naphtha feed flow respectively. The response optimizer also sugges ted that the propylene yield from naphtha pyrolysis cracking in the s tudied plant could be maximized at 11. 47% with the control setting at 10, 004. 36 kg/hr of hearth burner flow, 40, 960 kg/hr of dilution s team flow, and 63. 50 t/hr of naphtha feed flow