화학공학소재연구정보센터
Desalination, Vol.157, No.1-3, 137-144, 2003
Using atomic force microscopy towards improvement in nanofiltration membranes properties for desalination pre-treatment: a review
Seawater is characterised by having high degree of hardness, varying turbidity and bacterial contents and high TDS. These properties give rise to major problems such as scaling, fouling, high-energy requirements and the requirement of high quality construction materials. To solve seawater desalination problems and to minimise their effect on productivity and water cost of conventional plants, a new approach using nanofiltration as pre-treatment to both RO and thermal processes has been shown to enhance the production of desalted water and reduce the cost, yet it is environmentally friendly process. Nanofiltration pre-treatment of seawater feed to RO/thermal processes prevents scaling by removal of scale forming hardness ions, prevents membrane fouling in RO processes by removal of turbidity and bacteria and is expected to lower the required pressure to operate RO plant by reducing seawater feed TDS. This will depend on the type of NF membrane and operating conditions. In this paper, we will present a brief review on the potential use of state-of-the-art technique Atomic Force Microscopy (AFM), as a method for surface characterization, to understand the membrane characteristics toward significant improvement in NF membrane properties. AFM as a tool for surface characterization can be used to basically (i) quantify NF membrane properties such as pore size distribution and surface morphology, (ii) obtaining surface electrical properties, (iii) surface adhesion-membrane fouling behaviour and (vi) correlating membrane characteristics with process behaviour. Information obtained from these studies can be used, in conjunction with mathematical models and permeation data, to develop a novel approach in the prediction of optimised membrane properties for desalination pre-treatment as well as towards improved model for process performance prediction.