Abstract
Recent progresses in metallocene/post-metallocene catalysts technology have been led to high-performance polymers with outstanding tailor-made microstructure. After successful examples of such experimental studies, it seems now the turn of modeling strategies to predict and even optimize such catalytic systems. The current research deals with proposing a strategy to predict microstructure of such advanced polymers based on the implementation of a kinetic approach as well as a metaheuristic algorithm called the imperialist competitive algorithm, which is used as an advanced optimization technique to find kinetic constants of the model. With the aim of prediction of molecular weight distribution, a deconvolution analysis was performed to determine the probable number of required site types to obtain reasonable conformity between the model and experimental data, where it was found four active site types is sufficient. Among these four sites, one site is dedicated to predict the molecular weight distribution of ultrahigh molecular weight region while other sites are generally responsible for high-density polyethylene region (i.e., medium weight-average molecular weights). To validate the predictability of the model, the weight-average molecular weight results were compared to experimental data where the average absolute relative deviation was 6.31%, illustrating good performance of the model for prediction purposes. Besides, the performance of the model to predict the fraction of ultrahigh molecular weight in the resulted polymer was examined, of which the results confirmed excellent performance of the model where average absolute relative deviation was only 3.5%. Finally, a reverse model was developed in which the catalyst composition is predicted for producing polyethylene with a specified fraction of ultrahigh molecular weight. The results of the reverse model illustrate excellent agreement with their corresponding data of kinetic model, which the average absolute relative deviation was 0.16%. All the results of the study confirm the efficiency of the proposed strategy, promising and interesting approach for this type of catalysts.
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