Magnetic nanocomposite based on polyacrylic acid and carboxylated cellulose nanocrystal for the removal of cationic dye

基于聚丙烯酸和羧化纤维素纳米晶体的磁性纳米复合材料用于去除阳离子染料

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Abstract

The development of safe and cost-effective methods for the treatment of dye polluted wastewater has been a great concern among researchers. Herein, we developed a nanocomposite (M3D-PAA-CCN) based on polyacrylic acid (PAA) crosslinked with magnetic 3D crosslinkers (M3D) and carboxylated cellulose nanocrystals (CCN), for the removal of cationic dyes from aqueous solutions. Acrylic-functionalized Fe(3)O(4) nanoparticles were covalently linked to the polymer chains via the form of the 3D crosslinker to introduce magnetic properties into the as-synthesized nanocomposite. The addition of highly dispersive CCN reduced the gel-like properties of the nanocomposite and instead incorporated a diffusive nature, which was more desirable for adsorbents. The surface morphology of the nanocomposite was analyzed by FESEM and the size of the nanocomposite particles was found to be in the range of 60-90 nm. The chemical functionalities and compositions were determined by XPS, FTIR, and EDX analyses whereas TGA confirmed the thermal stability of M3D-PAA-CCN. The maximum adsorption capacity of the M3D-PAA-CCN (332 mg g(-1)) was measured higher than that of M3D-PAA (114 mg g(-1)) to a cationic methylene blue (MB) dye indicating the significant contribution of CCN. The adsorption capacity of the as-synthesized M3D-PAA-CCN was found to be highly pH-dependent and the adsorption capacity increased with the increase of pH owing to the greater negative charge as indicated by the higher zeta potential. The adsorption kinetics of MB on the composites was found to follow the pseudo-second-order model. The adsorption capacity was also investigated as a function of concentration to figure out the adsorption mechanism using Langmuir and Freundlich isotherm models. The Langmuir model fitted the adsorption process better as suggested by the relatively smaller nonlinear chi-square value obtained from the fitting parameters.

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