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Removal of 4-Nitrophenol from Aqueous Solution by Using Polyphenylsulfone-Based Blend Membranes: Characterization and Performance

Ali Amer YahyaMembrane Technology Research Unit, Chemical Engineering Department, University of Technology, Alsinaa Street 52, Baghdad 10066, IraqKhalid T. RashidMembrane Technology Research Unit, Chemical Engineering Department, University of Technology, Alsinaa Street 52, Baghdad 10066, IraqMaryam Y. GhadhbanMembrane Technology Research Unit, Chemical Engineering Department, University of Technology, Alsinaa Street 52, Baghdad 10066, IraqNoor Edin MousaMembrane Technology Research Unit, Chemical Engineering Department, University of Technology, Alsinaa Street 52, Baghdad 10066, IraqHasan Sh. MajdiDepartment of Chemical Engineering and Petroleum Industries, AlMustaqbal University College, Babylon 51001, IraqIssam K. SalihDepartment of Chemical Engineering and Petroleum Industries, AlMustaqbal University College, Babylon 51001, IraqQusay F. AlsalhyMembrane Technology Research Unit, Chemical Engineering Department, University of Technology, Alsinaa Street 52, Baghdad 10066, Iraq
2021en
ABI

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Among many contaminants in wastewater, organic phenol compounds presented a major concern to endanger the water resources safety. In the present study, blend nanofiltration (NF) membranes comprising polyphenylsulfone (PPSU) and polyethersulfone (PES) were prepared via the non-induced phase separation and their performance was examined against 4-Nitrophenol (4-NP). The PES ratio in the dope solution was varied from 6 to 9 wt.% to probe the impact of PES on the retention and permeation characteristics of the final membranes. A series of experimental tools were employed to estimate the characteristics of the membranes, including surface and cross-section, hydrophilicity, pore size and pore size distribution. Performance evaluation of the NF membranes was conducted considering two operational variables; pH and initial feed solution. About 99% removal of 4-NP along with 6.2 L/m2·h·bar was achieved at the optimum operating conditions as revealed by optimization and mathematical modelling.

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