| Literature DB >> 33334052 |
Ali Dawood Salman1,2, Tatjána Juzsakova1, Moayed G Jalhoom3, Cuong Le Phuoc4, Saja Mohsen5, Thamer Adnan Abdullah1, Balázs Zsirka1, Igor Cretescu6, Endre Domokos1, Catalina Daniela Stan7.
Abstract
The aim of this study was to prepare novel supramolecular hybrid nanoparticles (HNPs) that can selectively separate and recover scandium metal ions, Sc(III), from an aqueous phase based on molecular recognition technology (MRT). Moreover, this approach is fully compatible with green chemistry principles. In this work, natural amorphous silica (SiO2) nanoparticles were prepared by a precipitation method from Iraqi rice husk (RH) followed by surface modification with 3-amino-propyl triethoxysilane (APTES) as coupling agent and Kryptofix 2.2.2 (K2.2.2) as polycyclic ligand. To evaluate the potential of the hybrid nanoparticles, the prepared HNPs were used for the solid-liquid extraction of scandium, Sc(III), ions from model solutions due to the fact that K2.2.2 are polycyclic molecules. These polycyclic molecules are able to encapsulate cations according to the corresponding cavity size with the ionic radius of metal by providing a higher protection due their cage-like structures. Moreover, the authors set the objectives to design a high-technology process using these HNPs and to develop a Sc recovery method from the aqueous model solution prior to employing it in industrial applications, e.g., for Sc recovery from red mud leachate. The concentrations of Sc model solutions were investigated using the UV-Vis spectrophotometer technique. Different characterization techniques were used including scanning electron microscope (SEM), atomic force microscopy (AFM), Brunauer-Emmett-Teller (BET), X-ray diffraction (XRD), X-ray fluorescence (XRF), and Fourier transform infrared (FTIR). The extraction efficiency of Sc varied from 81.3% to 96.7%. Moreover, the complexed Sc ions were efficiently recovered by HCl with 0.1 mol/L concentration. The stripping ratios of Sc obtained ranged from 93.1% to 97.8%.Entities:
Keywords: K2.2.2; molecular recognition; rice husk; scandium; silica nanoparticles
Year: 2020 PMID: 33334052 DOI: 10.3390/ma13245727
Source DB: PubMed Journal: Materials (Basel) ISSN: 1996-1944 Impact factor: 3.623