The aim of this work is to characterize and evaluate the retention of Cu²⁺ and Ni²⁺ from single and binary systems by alginate-Moroccan clay bio-composite with the utilization of calcium chloride as a cross-linking agent, using the ionotropic gelation method. The bio-nanocomposite was characterized by using a variety of techniques (SEM, EDX, XRD, and pH_PZC). The efficiency of the adsorbent was investigated under different experimental conditions by varying parameters such as pH, initial concentration, and contact time. To demonstrate the adsorption kinetics, various kinetic models were tried and assessed, including pseudo-first-order, pseudo-second-order, intraparticle diffusion, and Elovich models. The research results show that the adsorption process of Cu²⁺ and Ni²⁺ metal ions follows a pseudo-second-order kinetic model, and the corresponding rate constants were identified. To evaluate the parameters related to the adsorption process in both single and binary systems, different mathematical models of isotherms, such as Langmuir, Freundlich, Temkin, and Dubinin-Radushkevich, were investigated. The correlation coefficients obtained showed that the most suitable isotherm for describing this adsorption process is the Langmuir model. The process is considered to be physical and endothermic, as suggested by the positive values of ΔH° and ΔS°, indicating increased randomness at the solid/liquid interface during Cu²⁺ and Ni²⁺ adsorption. Furthermore, the spontaneity of the process is confirmed by the negative values of ∆G°. The bio-nanocomposite beads demonstrated a maximum adsorption capacity of 370.37 mg/g for Ni²⁺ and 454.54 mg/g for Cu²⁺ in the single system. In the binary system, the maximum adsorption capacities were observed to be 357.14 mg/g for Ni²⁺ and 370.37 mg/g for Cu²⁺. There is significant evidence for the use of alginate-Moroccan clay bio-nanocomposite as a cost-effective alternative adsorbent for the efficient removal of metal ions in single and binary systems.

The aim of this work is to synthesize and characterize alginate–Moroccan clay bio-composite in order to improve our understanding of the adsorption of inorganic pollutants found in textile effluents. Characterization of the bio-composite used was carried out using a variety of techniques (IR-TF, SEM, DRX, and pH_ZPC). The influence of the medium’s physico-chemical parameters (temperature, pH, initial concentration, etc.) on the retention of inorganic pollutants was also studied. Studies of adsorption and inorganic pollutants such as orthophosphate (H₂PO₄⁻ and HPO₄²⁻) and nitrate (NO₃⁻) ions were carried out, using simple solutions from the laboratory, in a batch system. This study explored the impact of adsorbent dose, contact time, solution pH, and temperature on the adsorption process. Various kinetic models, including pseudo-first-order, pseudo-second-order, intra-particle diffusion, and Elovich models, were tested and evaluated, to illustrate the adsorption kinetics. This study’s findings demonstrated that the adsorption process follows second-order kinetics, with associated rate constants successfully determined. The correlation coefficient for the pseudo-second-order kinetic model is nearly equal to 1 (>0.98), and the value of theoretical adsorption capacity (q_e,the) is comparable to the experimental one (q_e,the = 58.14 mg/g for H₂PO₄⁻, q_e,the = 54.64 mg/g for HPO₄²⁻, and q_e,the = 52.63 mg/g for NO₃⁻). Additionally, the adsorption equilibrium was investigated through the application of various mathematical models, including the Langmuir, Freundlich, Temkin, and Dubinin–Radushkevich isotherm models, to assess the mechanistic parameters associated with the adsorption process. Among these models, the Langmuir isotherm emerged as the most suitable one for characterizing the adsorption of H₂PO₄⁻, HPO₄²⁻, and NO₃⁻ ions using bio-nanocomposite beads. The maximum adsorbed amounts of metal ions by the bio-nanocomposite used were 625 mg/g for H₂PO₄⁻, 909.09 mg/g for HPO₄²⁻, and 588.23 mg/g for NO₃⁻ from the batch system. The endothermic and physical nature of the adsorption is suggested by the positive values of ΔH°, which is consistent with experimental findings. The adsorption process is spontaneous, as evidenced by the negative ΔG° values. Positive ΔS° values indicate increased randomness at the solid/liquid interface during adsorption of ion-organic ions onto the engineered bio-nanocomposite. The obtained results demonstrated that, from a scientific perspective, alginate–Moroccan clay bio-nanocomposites exhibit a highly significant adsorption capability for the removal of oxyanions in aqueous environments.

This research aims to synthesize a novel hydrogel bio-composite based on natural clay, sodium alginate (Na-AL), and iota-carrageenan as adsorbents to remove phosphate ions from aqueous solutions. The adsorbents were characterized by a variety of techniques, such as Fourier-transform infrared (FTIR) spectroscopy, scanning electron microscopy coupled with energy dispersive X-rays (SEM-EDX), and the determination of point zero charge (PZC). This research investigated how the adsorption process is influenced by parameters such as adsorbent dose, contact time, solution pH, and temperature. In this study, we used four isotherms and four kinetic models to investigate phosphate ion removal on the prepared bio-composite. The results showed that the second-order kinetic (PSO) model is the best model for describing the adsorption process. The findings demonstrate that the R² values are highly significant in both the Langmuir and Freundlich models (very close to 1). This suggests that Langmuir and Freundlich models, with a diversity of adsorption sites, promote the adsorption of phosphate ions. The maximum adsorbed amounts of phosphate ions by the bio-composite used were 140.84 mg/g for H₂PO₄⁻ ions and 105.26 mg/g for HPO₄²⁻ ions from the batch system. The positive ∆H° confirms the endothermic and physical nature of adsorption, in agreement with experimental results. Negative ∆G° values indicate spontaneity, while the positive ∆S° reflects increased disorder at the solid–liquid interface during phosphate uptake. The main parameters, including adsorbent dosage (mg), contact time (min), and initial concentration (mg/L), were tuned using the Box–Behnken design of the response surface methodology (BBD-RSM) to achieve the optimum conditions. The reliability of the constructed models is demonstrated by their high correlation coefficients (R²). An R² value of 0.9714 suggests that the model explains 97.14% of the variability in adsorption efficiency (%), which reflects its strong predictive capability and reliability. Finally, the adsorption behavior of phosphate ions on the prepared bio-composite beads was analyzed using an artificial neural network (ANN) to predict the process efficiency. The ANN model accurately predicted the adsorption of phosphate ions onto the bio-composite, with a strong correlation (R² = 0.974) between the predicted and experimental results.

In this study, the modelling and optimization studies of the carcinogenic acid dye sorption from aqueous solutions were carried out using the Factor Design Methodology. This methodology provides a predictive model of the response in the range of variables studied and determines the optimum conditions for the best performance. The sorption of acid dye AB113 on Moroccan prickly pear cactus peel (MPPCP) was chosen as a case study of a typical removal process. Minitab17 software was used to study the effects of adsorption parameters, including initial dye concentration, solution pH, adsorbent dose, contact time, and temperature. Analysis of variance (ANOVA) was used to evaluate the experimental results obtained. The studied parameters at two levels (-1 and +1) were coded as X₁, X₂, X₃, X₄ and X₅, consecutively. The optimum conditions obtained for the adsorption of AB113 dye were: 1 g for the mass of MPPCP, 6 for the initial solution pH, 180 min for the contact time and 20 mg/L for the initial dye concentration. The results show that the model is well adapted to the experimental data, indicating the suitability of the model and the success of the factorial design methodology in optimizing the adsorption conditions.