A two step optimization approach for maximizing biosorption of hexavalent chromium ions (Cr (VI)) using alginate immobilized Sargassum sp in a packed bed column

Taguchi method for optimization of Cr(VI) removal, isotherm, kinetic and thermodynamic studies

In this study, Taguchi optimization method was applied to determine the optimum operating conditions for batch adsorption of Cr(VI) from aqueous solution. Initial pH of solution, adsorbent dose, initial hexavalent chromium concentration, contact time and adsorbent type were selected as the variables, and the removal efficiency of Cr(VI) was chosen for the designated response. L18(35) orthogonal array, signal-to-noise (S/N) ratio and analysis of variance statistical procedures were applied to identify the effect of each operating parameter on the removal of Cr(VI) from aqueous solution. The signal-to-noise (S/N) ratio results showed that the optimal combination for Cr(VI) removal was at pH 1.0, adsorbent dose of 3.6 g.L-1, Cr(VI) concentration of 30 mg.L-1, contact time of 95 min and olive leaves as adsorbent type. A removal of 95.09% was obtained at these optimum conditions. The analysis of variance of the data revealed that initial pH of solution was the most dominant parameter affecting Cr(VI) removal efficiency, followed by adsorbent type, adsorbent dose, contact time and initial metal concentration. Under optimal conditions, adsorption kinetic of Cr(VI) was studied and modeled using the pseudo first-order, pseudo-second-order and intraparticle diffusion models. It was found that the pseudo-second-order model fitted the adsorption data most with the highest determination coefficient (R2 = 0.996). Freundlich isotherm model, with regression coefficient R2 of 0.953, fit well with the equilibrium isotherm data. The Langmuir maximum adsorption capacity was found to be 62.5 mg.g-1. The experimental values of ΔH°, ΔG° and ΔS° revealed that the adsorption process was spontaneous and endothermic.

Response surface optimization and modeling in heavy metal removal from wastewater-a critical review

The existence of hazardous heavy metals in aquatic settings causes health risks to humans, prompting researchers to devise effective methods for removing these pollutants from drinking water and wastewater. To obtain optimum removal efficiencies and sorption capacities of the contaminants on the sorbent materials, it is normally necessary to optimize the purification technology to attain the optimum value of the independent process variables. This review discusses the most current advancements in using various adsorbents for heavy metal remediation, as well as the modeling and optimization of the adsorption process independent factors by response surface methodology. The remarkable efficiency of the response surface methodology for the extraction of the various heavy metal ions from aqueous systems by various types of adsorbents is confirmed in this critical review. For the first time, this review also identifies several gaps in the optimization of adsorption process factors that need to be addressed. The comprehensive analysis and conclusions in this review should also be useful to industry players, engineers, environmentalists, scientists, and other motivated researchers interested in the use of the various adsorbents and optimization methods or tools in environmental pollution cleanup.

Comparison of green bio-based cerium/alginate vs. copper/alginate beads: a study of vibrational and thermal properties using experimental and theoretical methods

Herein, bio-based alginates (Alg) containing metallic beads (Ce and Cu) were synthesized via an alginate cross-linking method, and their properties were studied using experimental techniques combined with theoretical simulations. Materials were characterized through Fourier transform infrared spectroscopy (FTIR), thermogravimetric analysis (TGA), and scanning electron microscope (SEM) images, to determine the cross-linking structural features, thermal stability, and surface morphology of alginates. Besides, density functional theory (DFT) methods were employed to calculate global reactivity parameters such as HOMO-LUMO gap energies (ΔE_H-L), electronegativity (χ), hardness (η), and electrophilic and nucleophilic indicators, using both gas and aqueous media for the study of the complexation process. Among other features, characterization of the thermal properties showed that Alg@Ce and Alg@Cu alginate beads behave differently as a function of the temperature. This behavior was also predicted by the conformation energy differences between Alg@Ce and Alg@Cu, which were found out theoretically and explained with the combined study of the vibrational modes between the carboxylate group with either Ce or Cu. Overall, the reactivity of the Alg@Ce alginate bead was higher than that of the Alg@Cu counterpart, results could be used as a cornerstone to employed the materials here studied in a wide range of applications.

Application of neural network in metal adsorption using biomaterials (BMs): a review

ANN models for predicting wastewater treatment efficacy of biomaterial adsorbents.