The aim of this study is to evaluate the applicability of Ho-CaWO4 nanoparticles prepared using the hydrothermal method for the removal of Methylene Blue (MB) from aqueous solution using adsorption process. The effects of contact time, Ho-CaWO4 nanoparticles dose and initial MB concentration on the removal of MB were studied using the central composite design (CCD) method. Response Surface Methodology (RSM) and Artificial Neural Network (ANN) modeling techniques were applied to model the process and their performance and predictive capabilities of the response (removal efficiency) was also examined. The adsorption process was optimized using the RSM and the optimum conditions were determined. The process was also modelled using the adsorption isotherm and kinetic models. The ANN and RSM model showed adequate prediction of the response, with absolute average deviation (AAD) of 0.001 and 0.320 and root mean squared error (RMSE) of 0.119 and 0.993, respectively. The RSM model was found to be more acceptable since it has the lowest RMSE and AAD compared to the ANN model. Optimum MB removal of 71.17% was obtained at pH of 2.03, contact time of 15.16 min, Ho-CaWO4 nanoparticles dose of 1.91 g/L, and MB concentration of 100.65 mg/L. Maximum adsorption capacity (qm ) of 103.09 mg/g was obtained. The experimental data of MB adsorption on Ho-CaWO4 nanoparticles followed the Freundlich isotherm and pseudo-second-order kinetic models than the other models. It could be concluded that the prepared Ho-CaWO4 nanoparticles can be used efficiently for the removal of MB and also, the process can be optimized to maximize the removal of MB. •Synthesis and characterization of Ho-CaWO4 nanoparticles.•Modelling and optimization of Methylene Blue removal onto Ho-CaWO4 using Response Surface Methodology (RSM) and Artificial neural network (ANN).•Evaluation of the isotherm and kinetic parameters of the adsorption process.

In the current work, neodymium oxide (Nd₂O₃) nanoparticles were synthesized and characterized by means of X-ray diffraction (XRD), Fourier-transform infrared spectroscopy (FTIR), and scanning electron microscopy (SEM). The major aim/investigation of this research was to fit/model and optimize the removal of Acid Blue 92 (AB92) dye from synthetic effluents (aqueous solutions) using the adsorption process based on neodymium oxide (Nd₂O₃) nanoparticles. To optimize the adsorption conditions, central composite design (CCD) based on response surface methodology (RSM) was applied. The effects of pH (3–9), adsorbent dosage (0.1–1 g/L), initial concentration of AB92 (100–300 mg/L), and contact time (10–100 min) on the adsorption process were investigated. Apart from equilibrium and kinetic experiments, thermodynamic evaluation of the adsorption process was also undertaken. The adsorption process was found to have the best fitting to Langmuir isotherm model and pseudo-second-order kinetic equation. Also, the process was found to be spontaneous and favorable with increased temperature. The optimal conditions found were: pH = 3.15, AB92 concentration equal to 138.5 mg/L, dosage of nanoadsorbent equal to 0.83 g/L, and 50 min as contact time, which resulted in 90.70% AB92 removal. High values for the coefficient of determination, R² (0.9596) and adjusted R² (0.9220) indicated that the removal of AB92 dye using adsorption can be explained and modeled by RSM. The Fisher’s F-value (25.4683) denotes that the developed model was significant for AB92 adsorption at a 95% confidence level.

In the present study, the adsorptive potential of modified bentonite in a batch system for the removal of aniline and phenol from aqueous solutions was investigated. The effect of various parameters including contact time (10–120 min), pH (2–10), adsorbent dosage (0.4–1.5 g/L) and initial concentration of aniline and phenol (50–200 mg/L) was investigated in this experimental laboratory study. Maximum removal of aniline and phenol was achieved at contact time of 30 and 45 min for aniline and phenol, respectively, and at the lowest studied initial concentration of 50 mg/L. Optimum bentonite dosage of 1 and 0.4 g/L was obtained for phenol and aniline, respectively. The adsorption process was better at the pH of 6 for aniline and pH of 4 for phenol. It was found that the equilibrium data was best followed by the Langmuir and Freundlich isotherms. Also, the pseudo-second-order kinetic model was best applicable for phenol and aniline adsorption. It was defined that bentonite not only was an inexpensive absorbent, but also a quite effective adsorbent for the removal of aniline and phenol from water and wastewater.

The release of dye containing effluent is a great threat to the world today. The purpose of this study is to optimize the removal of Reactive Blue 19 (RB19) dye from aqueous solutions using advanced oxidation process (AOP). Magnesium oxide nanoparticles (MgO NPs) and hydrogen peroxide (H₂O₂) were used as the catalyst and oxidizer, respectively. Central composite design (CCD) based on response surface methodology (RSM) was applied for optimization of the AOP process. The effects of pH (3–7), molar H₂O₂/MgO NPs ratio (1–3), initial concentration of RB19 (20–80 mg/L), and contact time (30–90 min) were investigated on the oxidation process. The CCD was applied to determine the interactive effects of the process parameters and their optimum conditions. One-way analysis of variance (ANOVA) was applied for statistical data analysis. A quadratic model was generated by the CCD to represent the AOP on RB19 degradation. The experimental values obtained for percentage RB19 decolorization were found to be very close to the predicted response values. Based on the design, optimum conditions of pH 3, contact time of 60 min, RB19 concentration of 80 mg/L and H₂O₂/MgO NPs molar ratio of 3 were obtained which resulted in 93.77% RB19 removal. High value for the coefficient of determination, R² (0.912) and adjusted R² (0.805) showed that the removal of RB19 dye using AOP can be described by the RSM. The ANOVA results showed that the quadratic model developed from the RSM was statistically significant for RB19 decolorization. From the study, it could be concluded that the RSM can be a useful tool for optimization and moderation of the process parameters to maximize RB19 dye removal from aqueous solutions and the advanced H₂O₂/MgO NPs oxidation process.