AI Article Synopsis

  • A chitosan magnetic membrane was developed to enhance cation removal from water and was compared with a standard chitosan membrane regarding stability, structure, and cation adsorption capacity.
  • The membrane containing nickel showed the best thermal stability and had a rough, porous surface, indicating successful fabrication as confirmed by various analytical methods.
  • Adsorption experiments demonstrated that the magnetic membrane (CHNiF-G) had a significantly higher capacity for copper cations compared to the standard chitosan membrane, with the adsorption following pseudo-second order kinetics and fitting best to the Temkin isotherm model.

Article Abstract

A chitosan magnetic membrane was prepared in order to confer magnetic properties to the membrane, which could be used for the removal of cations from aqueous solution. The crosslinked magnetic membrane was compared with pristine chitosan membrane in term of stability, morphology and cation adsorption capacity. The fabricated magnetic materials are thermally stable as shown by thermogravimetric curves. The membrane containing nickel magnetic particles (CHNiF-G) shows high thermal stability compared to the other membranes. The Fourier transform infrared spectroscopy showed successful preparation of chitosan magnetic membrane. Scanning electron microscopy micrographs showed the rough surface of the membrane with increased porosity. The prepared chitosan membranes were applied to cations of copper, nickel and lead in dilute aqueous solution. The chitosan membrane showed the following adsorption order for metallic cations: Cu > Ni > Pb, while CHNiF-G showed higher capacity, 3.51 mmol g for copper, reflecting the improvement in adsorption capacity, since the amount of copper on pristine chitosan gave 1.40 mmol g. The time required for adsorption to reach to the equilibrium was 6 h for the selected cations using different chitosan membranes. The kinetic study showed that adsorption followed pseudo-second order kinetics. The most commonly used isotherm models, Freundlich, Langmuir and Temkin, were applied to experimental data using linear regression technique. However, The Temkin model fits better to experimental data.

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Source
http://dx.doi.org/10.2166/wst.2017.078DOI Listing

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