Adsorption and desorption properties of Li+ on PVC-H1.6Mn1.6O4 lithium ion-sieve membrane

• PVC-Li1.6Mn1.6O4 precursor membranes were prepared by the solvent exchange method.
• The lithium ion-sieve membrane has high selectivity for Li+ with coexisting ions.
• It exhibits high stability after eight repeated adsorption–desorption cycles.
• The thickness of membrane effects on adsorption capacity and mechanical strength.

A series of PVC-Li1.6Mn1.6O4 precursor membranes were prepared by the solvent exchange method using spinel-type lithium manganese oxide powder (Li1.6Mn1.6O4) as the precursor, poly(vinyl chloride) (PVC) as the binder, and N,N-dimethyl acetamide (DMAc) as solvent. The Li+ of the precursor membrane was extracted by treated with HCl solution to obtain PVC-H1.6Mn1.6O4 lithium ion-sieve membrane adsorbent. The preparation conditions were investigated by changing the concentration of PVC and Li1.6Mn1.6O4, and the thickness of liquid film. The structure, morphology and adsorption properties of PVC-H1.6Mn1.6O4 lithium ion-sieve membrane were carried out by scanning electron microscope and atomic absorption spectrophotometer. The adsorption capacity depended on the preparation conditions. The membrane prepared with concentration of 10 wt% PVC and 15 wt% Li1.6Mn1.6O4 in DMAc and liquid film thickness of 0.30 mm is optimum for the adsorption of Li+ from aqueous solution. The thickness of membrane prepared under above conditions is about 0.1 mm. Repeated adsorption–desorption test indicates that the PVC-H1.6Mn1.6O4 lithium ion-sieve membrane can be effectively regenerated with HCl solution and reused for Li+ adsorption without significant loss in the adsorption capacity. Li+ adsorption experiments confirm that the PVC-H1.6Mn1.6O4 lithium ion-sieve membrane possesses high selectivity for Li+ in the presence of Na+, K+, Ca2+ and Mg2+. According to the coefficients, the isothermal data correlated with the Langmuir model better than the Freundlich model, and the adsorption process follows a pseudo-second-order kinetic model.

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