摘要
A L463^5 Box-Behnken design was used for developing a model to predict and optimize the molecular weight （Mw ） of polypropylene （PP） ; a second-order polynomial regression equation was derived to predict responses. The significance of variables and their interactions were tested by means of the ANOVA with 95% confidence limits; the standardized effects were investigated by Pareto chart, the optimum values of the selected variables were obtained by analyzing the response surface contour plots. The optimized Mw value of 1. 217 × 10^5 g/mol was very close to the industrial value （ （ 1.22 ±0. 004） ×10^6 g/tool） at the optimum values.
A L463^5 Box-Behnken design was used for developing a model to predict and optimize the molecular weight （Mw ） of polypropylene （PP） ; a second-order polynomial regression equation was derived to predict responses. The significance of variables and their interactions were tested by means of the ANOVA with 95% confidence limits; the standardized effects were investigated by Pareto chart, the optimum values of the selected variables were obtained by analyzing the response surface contour plots. The optimized Mw value of 1. 217 × 10^5 g/mol was very close to the industrial value （ （ 1.22 ±0. 004） ×10^6 g/tool） at the optimum values.
基金
Supported by the R&D Program of Catalyst Company,SINOPEC(G8101-11-ZS-0016*)
