PES-Kaolin Mixed Matrix Membranes for Arsenic Removal from Water

• Published in: Membranes (Basel) Vol. 7; no. 4; p. 57
• Main Authors: Marino, Tiziana, Russo, Francesca, Rezzouk, Lina, Bouzid, Abderrazak, Figoli, Alberto
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 30.09.2017; MDPI
• Subjects: Adsorption; Air temperature; Arsenic; Arsenic removal; Clay; Composition effects; Contact angle; Fabrication; Kaolin; kaolin KT2; Membrane permeability; Membrane separation; Membranes; mixed matrix membranes; phase inversion; Phase separation; Pollutant removal; polyethersulfone; Polyethylene glycol; Polymers; Pore size; Porosity; Solvents; Ultrasonic testing; Water pollution; water treatment; water treatment; polyethersulfone; arsenic; phase inversion; mixed matrix membranes; kaolin KT2
• ISSN: 2077-0375; 2077-0375
• DOI: 10.3390/membranes7040057

The aim of this work was the fabrication and the characterization of mixed matrix membranes (MMMs) for arsenic (As) removal from water. Membrane separation was combined with an adsorption process by incorporating the kaolin (KT2) Algerian natural clay in polymeric membranes. The effects of casting solution composition was explored using different amounts of polyethersufone (PES) as a polymer, polyvinyl-pyrrolidone (PVP K17) and polyethylene glycol (PEG 200) as pore former agents, -methyl pyrrolidone (NMP) as a solvent, and kaolin. Membranes were prepared by coupling Non-solvent Induced Phase Separation and Vapour Induced Phase Separation (NIPS and VIPS, respectively). The influence of the exposure time to controlled humid air and temperature was also investigated. The MMMs obtained were characterized in terms of morphology, pore size, porosity, thickness, contact angle and pure water permeability. Adsorption membrane-based tests were carried out in order to assess the applicability of the membranes produced for As removal from contaminated water. Among the investigated kaolin concentrations (ranging from 0 wt % to 5 wt %), a content of 1.25 wt % led to the MMM with the most promising performance.