Peripherally modified poly (acrylic acid)/ ZnO nanocomposite hydrogel with selective superadsorption properties

In this study, removal of three toxic chemical pollutants, such as crystal violet (CV) dye, tetracycline (TC) drug, and phenol (PH) using sodium alginate-g-poly (acrylicacid-co-sodium, 4-ethenylbenzenesulfonate, hydrate)/Zinc oxide, and SA-g-poly(AC-co-EBS)/ZnO hydrogel composite was prepared by co-polymerization method by addition of free radicals. The hydrogel composite was characterized by TEM, FESEM, and XRD. Removal of laboratory sample aqueous pollutants (dyes, drugs, and phenol) using hydrogel composite to give low absorbance (0.0001) utilizing UV-Vis spectrophotometer for at a chosen wavelength for 2 h. Comparative between ((SA-g-(PAAc-co-EBS)/ZnO, (SA-g-(PAAc-co-EBS), and ZnO NPs) surfaces as adsorbents. The best results of the percentage of removal (E%) of three pollutants arrange in order increasing (SA-g-(PAAC-co-EBS)/ZnO NPs > SA-g-(PAAC-co-EBS) > ZnO NPs), the good results of the percentage removal (E%) of hydrogel composite, (92, 451%, 87.56%, and 82.56%) for CV, TC, and PH, respectively. Likewise, comparative between the amount of Zinc oxide nanoparticles (ZnO NPs) decorated of (SA-g-(PAAC-co-EBS) using (0.05, 0.08, 0.1, and 0.15 g). The good results of the percentage of removal (E%) of three pollutants about 0.1 g ZnO NPs. Re-cyclability and desorption studies indicated the best re-cycling performance of the prepared composite. Based on the results, the prepared hydrogel composites can be useful as a promising, ecological, cost-effective, and efficient material for dyes decontamination. Studies was carry out using several desorption agents at concentration (0.01 N) like HNO3, NaOH, H3PO4, H2SO4, HCl, and water. The hydrogel composite, was regeneration with 100% can be desorbed in diluted hydrochloric acid (0.01 N). The isotherm Freundlich and Langmuir models are also introduced, it has been found that all results follow the Freundlich model in the presence of three pollutants; this nonlinearity is higher when using the Freundlich model.