Two-step preparation of amidoxime-functionalized natural zeolites hybrids for the removal of Pb2+ ions in aqueous environment

Amidoxime-functionalized natural zeolites hybrids were prepared through two-step method including gamma-irradiation for the grafting polymerization of polyacrylonitrile (PAN) and chemical transformations of nitrile groups (-R-C N) to amidoxime groups (-R-C(NH2) = NOH). This study aims to combine the good mechanical properties of low-cost inorganic matrices, i.e. natural zeolites, with strong chelating ability, which is potential for adsorbing toxic metal cations, especially Pb2+. The grafting polymerization of PAN depended on the y-irradiation dose and dose rate. The optimized condition for the highest degree of grafting (20%) and maintained zeolites structure lies at the irradiation dose of 100 kGy at a dose rate of 2 kGy h(-1). It was indicated that the grafting polymerization of PAN also occurred inside the micropores since the micropore volumes cannot be detected by N-2 adsorption-desorption isotherms after grafting polymerization and chemical transformations. Moreover, the grafted PAN probably formed a chemical bonding with the zeolites since they exhibited the peaks of Si-O-center dot and Si-center dot sites in the ESR spectra of zeolites after gamma-irradiation. The amidoxime-functionalization was confirmed by FTIR spectroscopy which showed the transformation of CaeaN band into C = N, C-N and N-OH bands and SEM-EDX which exhibited the morphology alteration and the enhancement of C and N atoms percentage. The two-step preparation appeared to not alter the structure of zeolites as shown by XRD and Al-27 MAS NMR spectroscopy. The amidoxime-functionalized natural zeolites hybrids exhibited maximum adsorption capacity of 72 mg g(-1) towards Pb2+ in the aqueous environment which was comparable and, even, higher than several previous reports. The adsorption process followed the Langmuir model with favorable adsorption based on the separation factor values, while the adsorption kinetics are based on pseudo second order model.