Layered ammonium vanadate nanobelt as efficient adsorbents for removal of Sr2+ and Cs+ from contaminated water

In this study, a layered ammonium vanadate (NH4V4O10) nanobelt adsorbent was synthesized by a facile hydrothermal method to remove Sr2+ and Cs+ from contaminated water. The NH4V4O10 nanobelt was texturally and morphologically characterized by scanning electron microscopy (SEM), high-resolution transmission electron microscopy (HRTEM), X-ray diffraction (XRD), Fourier-transform infrared spectroscopy (FTIR), Raman, thermogravimetric differential thermal analyzer (TG-DSC), Brunauer- Emmett-Teller (BET), and X-ray photoelectron spectroscopy (XPS) both before and after adsorbing Sr2+ and Cs+. The results showed that the NH4V4O10 nanobelt exhibited the optimal morphological structure with a 2:1 ratio of NH4VO3:dipropylamine. In the lattice of the adsorbent, the horizontal distance between oxygen atoms was 0.55 nm, the vertical distance between vanadium was 0.35 nm, and the layer distance of the adsorbent was 0.931 nm. The structure characterization indicated the VO6 octahedron formed a basic framework through sharing connected vertices. Adsorption mechanism studies indicated that ion exchange was the main adsorption mechanism for removing Sr2+ and Cs+. Batch experiments revealed that the adsorption capacity for Sr2+ was 192.52 mg/g under a pH of 2. Similarly, the adsorption capacity for Cs+ was 251.09 mg/g when the pH was 5. The adsorption kinetics and adsorption isotherms data were in accordance with the pseudo-second-order kinetic model and Langmuir model, respectively. Adsorption isotherms results also indicated that the adsorption of Sr2+ and Cs+ was endothermic (ΔHSr0 = 3.6 kJ/mol, ΔHCs0 = 29.1 kJ/mol) and increased entropy (ΔSSr0 = 29.15 J/molK, ΔSCs0 = 160.38 J/molK). Finally, the structure of the adsorbent, the adsorption performance and mechanism, and the interpretation of selective adsorption were also calculated by DFT method at the molecular level and the results were consistent with the experimental data.