Optimal synthesis and operation of low-cost polyvinyl chloride/bentonite ultrafiltration membranes for the purification of oilfield produced water

被引:77
作者
Ahmad, Tausif [1 ]
Guria, Chandan [1 ]
Mandal, Ajay [1 ]
机构
[1] Indian Sch Mines, Dept Petr Engn, Indian Inst Technol, Dhanbad 826004, Bihar, India
关键词
Ultrafiltration; Poly (vinyl chloride); Bentonite nanoclay; Salt coagulation bath; Multi-objective optimization; RESPONSE-SURFACE METHODOLOGY; WASTE-WATER; IN-WATER; TREATMENT OPTIMIZATION; ANTIFOULING PROPERTIES; EFFICIENT SEPARATION; COMPOSITE MEMBRANE; OIL/WATER EMULSION; PERFORMANCE; NANOPARTICLES;
D O I
10.1016/j.memsci.2018.07.093
中图分类号
TQ [化学工业];
学科分类号
0817 ;
摘要
The low-cost PVC/bentonite ultrafiltration membranes are prepared by phase inversion method using different coagulation baths involving de-mineralized water and aqueous saturated solution of NH4Cl, NaCl, KCl, MgCl2 and CaCl2. Effect of coagulation bath on membrane performance is investigated by evaluating ternary-phase diagram, membrane morphology, hydrophilicity, porosity, mean pore size, pore density, pure water flux and antifouling behavior using oilfield produced water. Better performing membrane with 5% bentonite loading is obtained from KCl-coagulation bath with pure water permeance-467.5 Lm(-2) h(-1) atm(-1). Response surface method based on central composite design is employed to enhance the ultrafiltration membrane performance using the optimum design of experiments through maximizing permeate flux as well as oil rejection separately considering following decision variables: PVC and bentonite loading in casting solution, membrane thickness, pH and trans-membrane pressure (TMP). The maximum permeation flux of 421.3 Lm(-2) h(-1) is achieved using PVC-loading-15.01 g, bentonite-loading-1.37 g, membrane thickness-100 mu m, pH-9 and TMP-250 kPa, while maximum oil rejection is 98.6% at PVC-loading-18.0 g, bentonite-loading-0.0 g, membrane thickness-250 mu m, pH-5.1 and TMP-54.4 kPa. Due to conflicting nature of permeation and oil rejection, a multi-objective optimization problem is formulated and solved using an elitist non-dominated sorting genetic algorithm (NSGA-II), resulting the Pareto-optimal solution.
引用
收藏
页码:859 / 877
页数:19
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