Preparation of Fe3O4Nanoparticles and Removal of Methylene Blue through Adsorption

Characterization of Fe3O4 Nanoparticles for Applications in Catalytic Activity in the Adsorption/Degradation of Methylene Blue and Esterification

The aim of this study is to evaluate the applicability of the catalytic activity (CA) of the Fe₃O₄ magnetic system in the adsorption/degradation of methylene blue and esterification. The thermal decomposition method allowed the preparation of Fe₃O₄ nanoparticles. The crystallites of the Fe₃O₄ structural phase present an acicular form confirmed by X-ray diffraction. Transmission electron microscopy results identified the acicular shape and agglomeration of the nanoparticles. Mössbauer spectroscopy showed that the spectrum is composed of five components at room temperature, a hyperfine magnetic field distribution (HMFD), two sextets, a doublet, and a singlet. The presence of the HMFD means that a particle size distribution is present. Fluorescence spectroscopy studied the CA of the nanoparticles with methylene blue and found adsorption/degradation properties of the dye. The catalytic activity of the nanoparticles was evaluated in the esterification reaction by comparing the results in the presence and absence of catalyst for the reaction with isobutanol and octanol, where it is observed that the selectivity for the products MIBP and MNOP is favored in the first three hours of reaction.

Effective adsorption of zinc on magnetic nanocomposite of Fe3O4/zeolite/cellulose nanofibers: kinetic, equilibrium, and thermodynamic study

In this paper, the adsorption behavior of zinc onto magnetic zeolite/cellulose nanofibers (MZNF) was studied. The prepared adsorbent was characterized by SEM, FTIR, and VSM analyses. The mass ratio of adsorbent in composite, pH, contact time, adsorbent dosage, initial Zn⁺² concentration, temperature, and agitation speed were investigated in batch experiments. The results showed that zeolite played an important role in the prepared nanocomposite due to its great surface area. pH 7 exhibited the highest Zn⁺² removal efficiency. Rapid adsorption at the first 30 min of the reaction is one of the advantages of the prepared adsorbents. Moreover, increase at temperature led to higher efficiency and maximum efficiency was attained at 30 °C. Under optimum conditions, MZNF showed removal efficiency of 96% and maximum adsorption capacity of 9.45 mg/g. The presence of the competing ions did not reduce the efficiency of the process and adsorption efficiency was higher than 93%. The calculated RSD of 1.42% exhibits the suitability of the process. Equilibrium data were examined by various isotherms and kinetics equations. It was concluded that Pseudo second-order model and Langmuir models described the adsorption process well. Based on these results, MZNF obtained in this work can be served as a promising candidate for Zn⁺² removal in wastewater.

Modeling of adsorption of Methylene Blue dye on Ho-CaWO4 nanoparticles using Response Surface Methodology (RSM) and Artificial Neural Network (ANN) techniques

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 (q_m ) 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.