화학공학소재연구정보센터
Separation and Purification Technology, Vol.179, 94-103, 2017
High-capacity, nanofiber-based ion-exchange membranes for the selective recovery of heavy metals from impaired waters
This contribution describes the development, performance evaluation and modeling of polyelectrolyte-modified nanofiber membranes for heavy metal recovery from impaired water. High-capacity membranes were prepared by grafting poly(acrylic acid) (PAA) and poly(itaconic acid) (PIA) to cellulose nano fiber mats. The success of polymer grafting was confirmed by attenuated total reflectance Fourier transform infrared spectroscopy. Membrane permeabilities for a series of polymer grafted nanofiber membranes were measured by direct-flow filtration. Single-component ion-exchange isotherms were measured at constant pH for cadmium, nickel, and calcium ions. The higher metal-polymer complex stability of Cd-PIA over Cd-PM was found to be an impact factor for achieving high Cd binding capacities. Single-component ion-exchange isotherms were well described by the Langmuir model, with maximum capacities of PIA-modified membranes that exceeded 220 mg Cd/g, comparable to traditional resin-based ion-exchange media. Moreover, membranes were selective for Cd over Ni and Ca because of different hydration energies and ionization potentials. Competitive ion-exchange measurements were made using environmentally relevant concentrations of these ions to determine the selectivity of the membranes for cadmium ion. Experimental isotherms for Cd-Ca and Cd-Ni were compared to model predictions from the competitive Langmuir model with Langmuir parameters obtained by fitting single-component isotherms. The competitive Langmuir model well describes the experimental isotherms at low metal ion concentrations. However, at high concentrations, the model underestimates experimental uptake values. This work shows that nanofiber membranes offer a high-capacity and high-productivity platform for selective removal of heavy metals, especially Cd, from impaired waters. (C) 2017 Elsevier B.V. All rights reserved.