Simultaneous extraction of Cu2+ and Cd2+ ions in water, wastewater, and food samples using solvent-terminated dispersive liquid-liquid microextraction: optimization by multiobjective evolutionary algorithm based on decomposition

Modeling of malachite green adsorption onto novel polyurethane/SrFe12O19/clinoptilolite nanocomposite using response surface methodology and biogeography-based optimization-assisted multilayer neural network

This research studied the modeling of malachite green (MG) adsorption onto novel polyurethane/SrFe₁₂O₁₉/clinoptilolite (PU/SrM/CLP) nanocomposite from aqueous solutions by the application of biogeography-based optimization (BBO) algorithm-assisted multilayer neural networks (MNN-BBO) as a new evolutionary algorithm in environmental science. The PU/SrM/CLP nanocomposite was successfully fabricated and characterized by some spectroscopic analyses. Four variables influencing the removal efficiency were modeled by MNN-BBO and response surface methodology (RSM). The MNN-BBO model gave higher percentage removal (99.6%) about 7.6% compared to the RSM technique. Under optimal conditions obtained by MNN-BBO, the four independent variables including pH, shaking rate, initial concentration, and adsorbent dosage were 6.5, 255 rpm, 50 mg.L^-1, and 0.08 g, respectively. Under these conditions, the results were fitted well to the Langmuir isotherm with a monolayer maximum amount of sorbate uptake (q_max) of 68.49 mg.g^-1 and the pseudo-first-order kinetic pattern with the rate constant (K₁) of 0.01 min^-1 with the R² values of 0.9248 and 0.9980, respectively. The results of thermodynamics demonstrated that the MG uptake was not spontaneous due to the positive value of the adsorption ΔG. In addition, the positive values of ΔS (0.079 kJ/mol K) and ΔH (30.816 kJ/mol) indicated the feasible operation and endothermic approach, respectively. Besides, the wastewater investigations showed that the nanocomposite could be used as a new promising sorbent for efficient removal of MG (R% > 72) and magnetically separable from the real samples.

Preparation of melon peel biochar/CoFe2O4 as a new adsorbent for the separation and preconcentration of Cu(II), Cd(II), and Pb(II) ions by solid-phase extraction in water and vegetable samples

The present research describes the successful preparation of melon peel biochar modified with CoFe₂O₄ (MPBC/CoFe₂O₄) followed by its usage as a new sorbent to separate, preconcentrate, and determine the toxic heavy metal ions by magnetic solid-phase extraction. The metal ion desorption was performed by 0.1 M HCl solution with a volume of 5.0 mL. Flame atomic absorption spectrometry (FAAS) was utilized for detection of the analyte levels. SEM-EDX, TEM, XRD, and FTIR techniques were carried out to illuminate the structure of MPBC/CoFe₂O₄. The fundamental variables affecting the adsorption and elution efficiencies of the analyte ions including solution pH, MPBC/CoFe₂O₄ amount, type and concentration of eluent, adsorption and desorption equilibrium time, and sample volume were optimized. The detection limits were calculated as 0.41, 1.82, and 3.16 µg L^-1 for Cu²⁺, Cd²⁺, and Pb²⁺ ions, respectively, with the relative standard deviation of lower than 4.2%. There were no substantial interference effects on the analyte ion recovery due to the presence of foreign ions at high levels. Five minutes of contact time was adequate to attain the adsorption equilibrium. The adsorption capacity of MPBC/CoFe₂O₄ was obtained as 106.4, 65.4, and 188.7 mg g^-1 for Cu²⁺, Cd²⁺, and Pb²⁺ ions, respectively, by utilizing Langmuir isotherm model. The pseudo-second order model is favorable to identify the adsorption kinetics. The method was validated by spike/recovery test, and then, it was successfully implemented to determine the aforementioned analyte levels in sea and stream water, pepper, black cabbage, eggplant, and tomato samples.