فهرست نشریات علمی دسترسی آزاد ایران

The present work study focusing on the incorporation of PVP-GO (polyvinylpyrrolidone- graphene oxide) nano-fillers into thin-film nanocomposite (TFN) membranes to enhance their performance in oily wastewater treatment. This study demonstrates advancements in membrane technology by integrating nanofillers and optimizing operational parameters through statistical modeling. The study utilized Central Composite Design (CCD) and Response Surface Methodology (RSM) to optimize the separation process parameters and assess the performance of the membrane. This kind of study is indicative of efforts to push the boundaries of membrane technology by optimizing both the material properties (through nano-filler incorporation) and the operational conditions (through statistical methods like CCD and RSM) to achieve superior separation performance in complex wastewater treatment scenarios. Three models correlating the independent parameters including, feed solution concentration (1000-2000 ppm), draw solution concentration (1-3 M) and flowrate (200-400 mL/min) with the responses including, permeate flux (Jw), reverse salt flux (Js) and Js/Jw selectivity were developed based on the experimental data. The optimum parameters for achieving the highest separation performances were obtained at feed solution concentration of 1999.994 ppm, draw solution concentration of 2.893 M and flowrate of 390.997 ml/min, which resulted in water permeability of 59.658 LMH, 1.630 gMH and Js/Jw selectivity of 0.023 g/L. The deviation of the corresponding experimental data was found to be in an acceptable range, confirming the suitability of RSM for predicting the membrane performance and consequently optimizing the separation process variables.