Optimization of covalently cross-linked graphene oxide-infused polyamide thin film nanocomposite membrane for treating wastewater containing heavy metallic ions

Abstract

The Nanofiltration technology is widely used wastewater treatment to reduce the salt concentration of toxic heavy metallic ions present in drinking waters and acid mine drainage systems containing impurities emanating from commercial and industrial discharge of effluents comprised of heavy metals such as Cobalt, Iron, Sodium, Magnesium, Nickel, and Manganese for reusable application. The best techniques for removing heavy metals from wastewater have been researched using a broad range of strategies comprising membrane separation processes, ion exchange resins, coagulation, and chemical precipitation. The rate of water consumption nationally has led research into considering advanced water treatment technologies into providing safer water treatment technologies which can provide safe water supply in a more energy productive and sustainable manner environmentally. To achieve continual improvement, different methods have been established for removal of the heavy metals present in wastewaters such as adsorption, chemical precipitation, membrane filtration and ion exchange processes. This study discussed the treatment of heavy metallic ions composed of different concentrations in acid mine wastewater using a thin film nanocomposite (TFN) membrane. This study focused on fabrication of thin film nanocomposite (TFNs) which were utilised for the adsorption of heavy metals and membrane performance was evaluated using different operating parameters which include rejection, flux, and recovery. Response surface methodology (RSM) technique was used to develop mathematical models for the optimization of the nanofiltration separation process by finding the optimum operating conditions of the membrane. The performance of the Graphene Oxide/Polyethersulphone (PES) nanocomposite membranes composed of different PES-GO ratios was measured against permeability and selectivity. However, some of the disadvantages associated with GO membranes are their extremely hydrophobic nature causing them to become unstable in water, and the weak interaction between GO sheets also leads to low mechanical strength of the GO membranes. To resolve the above-mentioned challenges, chemical bonding can be induced between GO sheets to improve the mechanical strength properties and prevent dispersion in water. In this study, the chemical crosslinking of the GO sheets involved the comparison of three dicarboxylic acids in Glutaric acid, Pimelic acid and hexanedioic acid. The aim of using the three different carbon chain dicarboxylic acids as crosslinking solutions was to evaluate the effect which the increasing chain length will have on the intersheet spacing, permeation flux, membrane selectivity, and elastic moduli of the GO PES membrane. The objective of this research study was to fabricate and improve the efficiency of a PES/GO nanocomposite membrane for the removal of heavy metals from wastewater. Three different types of PES/GO membranes were constructed based on different functional groups added onto the GO material and were analyzed for their membrane composition, characteristics as well as performance in the removal of the Iron, Manganese, Sodium, Magnesium, Nickel, and Cobalt and was compared to the primary PES commercial membrane. The ideal membrane suitable for the above-mentioned quality standards was found to be the one composed of PES membrane infused with Pimelic acid. The fabricated TFN membrane could separate inorganic pollutants without undergoing severe fouling or clogging during membrane operation and was found to be chemically stable, physically durable, and chemically resistant. The PES GO-Pimelic acid functionalized membrane performed better when compared to the other two TFN membranes synthesized utilizing glutaric and adipic dicarboxylic acids. The membrane surface morphologies of the three different membranes were vastly altered with the addition of different crosslinkers and such observations was caused by the different functional groups added onto the GO surface. The effective crosslinking reactions between the polyamide layers formed onto the TFC composite membrane and GO functionalised with different dicarboxylic acids was instrumental in formulating adequate stability between the charges, spacing of GO sheets and functionality when dispersed within the water environment to such an extent that the TFN membrane was found to be physically durable in overcoming GO leaching during the separation process. The Glutaric and Adipic functionalised GO material was faced with the challenge of unbonded GO layers which contributed to achieving low nanofiltration performance targets in removal heavy metals and that compromised the accuracy of the models used in fitting the experimental data to obtain the optimal solution from their respective experiments. In most research studies conducted regarding the optimization for preparation conditions was not done, and therefore such research gap was filled within this research study. The optimization of concentration of crosslinker, reaction time as well as temperature was conducted for pimelic acid functionalised infused PES thin film membrane and the reaction time was reduced from 48 hours to 30 minutes. The performance for the PES membrane and Pimelic functionalised GO-PES infused membranes was studied, and the commercial PES membrane revealed great permeability of 65.74 L/m2.hr as well as mean rejection of low concentration of heavy metals at 96 % removal rate. The GO-PES membrane functionalised with pimelic acid was studied for its heavy metal removal rate at low concentrations using synthetic acid mine drainage, and it showed a rejection rate of 98% with decreased flux of 43.41 L/m2.hr. The input variables responsible for changing the nanofiltration process were limited to operating pressure as driving force which had great potential in affecting process performance at different stipulated operating times, with the synthesized TFN membrane responsible for adsorbing the heavy metals. Subsequently, it can be concluded that a well designed RSM predictive model using Design Expert 12 can be utilised as a feasible tool for the prediction of nanocomposite membrane at different operational conditions. The membranes used in this study showed excellent permeate fluxes and rejection factors like those obtained by other researchers in this field using the same carbon nanostructures in GO embedded into polymer matrix.