Removal of Cs+ from aqueous solutions by perlite

Isotherm, Kinetic, and Selectivity Studies for the Removal of 133Ba and 137Cs from Aqueous Solution Using Turkish Perlite

The efficiency of 133Ba and 137Cs removal from aqueous solution is vital to mitigate ecological concerns over spreading these radionuclides in the environment. The present work focused on the use of Turkish perlite for the sorptive removal of 133Ba and 137Cs from aqueous solution by the radioindicator method. Perlite was characterized by XRF, XRD, FTIR, SEM−EDX, and BET analyses. The maximum percentage removals of 88.2% and 78.7% were obtained for 133Ba and 137Cs at pH 6 and pH 9, respectively. For both ions, the sorption equilibrium was attained relatively rapidly. Experimental kinetic data were well described with pseudo-second-order and intraparticle diffusion models. The uptake of both ions increased with the increase in metal concentration (1 × 10−5 to 5 × 10−2 mol/L) in solution. The maximum uptake capacities of 133Ba and 137Cs were found to be 1.96 and 2.11 mmol/g, respectively. The effect of competing ions decreased in the order of Ca2+>K+>Ni2+>Na+ for 133Ba sorption, whereas for 137Cs sorption, the order was determined as Ca2+>Ni2+>K+>Na+. Selectivity studies pointed out that sorption of 133Ba onto perlite is preferable to 137Cs. Therefore, Turkish perlite is a promising, cost-effective, and efficient natural material for the removal of 133Ba and 137Cs from relatively diluted aqueous solution.

A green rust-coated expanded perlite particle electrode-based adsorption coupling with the three-dimensional electrokinetics that enhances hexavalent chromium removal

A green rust-coated expanded perlite (GR-coated Exp-p) microelectrode was synthesized and incorporated into a column-mode three-dimensional electrokinetic (3D-EK) platform to effectively pursue a continuous Cr(VI) removal from the aqueous solution. Brucite-like layers of GR were decorated onto the Exp-p material. The molar ratio of Fe(II) to Fe(III) played a most vital role among the three synthesis factors in influencing the performance of the particle electrode. For the equilibrium adsorption experiments, the target maximum adsorption capacity of 122 mg/g was predicted by a target optimizer and desirability function at the conditions following the pH of 4.7, the initial concentration of 172.4 mg/L, the dosage of 0.28 g/L, and the temperature of 28.96 °C, respectively. SO₄^2-, Cl^-, and NO₃^- fiercely competed with Cr(VI) anions in the acidic conditions for the locally positive sites. A low concentration and a slow flow were favored in the column-mode 3D-EK platform. The pseudo-first-order and Langmuir models were suitable for describing the kinetics and isotherms of the adsorption process, respectively. Cr(VI) anions were electrostatically attracted to the silanol groups and GR surface of the adsorbent, subsequently reduced in both heterogeneity and homogeneity, and finally immobilized by coordinating with silanediol groups and silanetriol groups.

Statistical techniques for the optimization of cesium removal from aqueous solutions onto iron-based nanoparticle-zeolite composites

Statistical optimization of performance determining factors is essential for the development of a cesium removal system from aqueous solutions. Therefore, factorial experimental design and multiple regression techniques were employed to assess the primary and interaction effects of the pH, initial concentration, and contact time in the cesium removal process using nanoscale zero-valent iron-zeolite (nZVI-Z) and nano-Fe/Cu-zeolite (nFe/Cu-Z) as an adsorbent. The optimum region of cesium removal was identified by constructing a contour plot. The study revealed that initial concentration was the most significant factor followed by contact time. The study also suggested that maximum cesium removal occurred at pH, initial concentration, and contact time of 6, 200 mg/L, and 30 min, respectively. Moreover, the statistically significant interaction effect was observed between contact time and initial concentration. The experimental data were also fitted with Tόth, Langmuir, Dubinin-Astakhov (D-A), Freundlich, and Hill models and found that the Tόth model fitted better compared with the other four models based on Akaike information criterion (AIC) and root-mean-square deviation (RMSD). The findings of this paper can undoubtedly contribute to constructing the optimum statistical process of removing hazardous pollutants from the water, which significantly impacts on human health and the environment. Graphical abstract.