عنوان مقاله [English]
Addition of nanoparticles to a polymeric matrix leads to enhance the performance of membrane gas separation. In this study, the aim is to find the optimum operative point of polymeric membrane modified by adding nanoparticles in gas separation. The assessed factors are type of nanoparticle, percentage of added nanoparticle, and cross membrane pressure. Nanoparticles of AL2O3, ZnO, and TiO2 were used. Further, the ranges of nanoparticle concentration and operative cross membrane pressure were 2.5 to 15% and 2 to 25 bar, respectively. To optimize a process, developing a robust model is necessary. So, First, a powerful model based on artificial neural network was developed that was able to predict the values of permeability of oxygen, nitrogen, methane, and carbon dioxide. Neural networks model were developed with R2 greater than 0.9. Next, the optimum operative conditions for assessed gases were found using methodology based on genetic algorithm and considering four strategies. The results of optimization show that the maximum values of permeability for oxygen, nitrogen, methane, and carbon dioxide are 334.7, 779.9, 902.7, and 270.4, respectively.