Effective Removal of Methylene Blue from Wastewater Using Magnetite/Geopolymer Composite: Synthesis, Characterization and Column Adsorption Study

[Display omitted] •Rising trend in new research toward the utilization of costless reactive materials of various structures.•Geopolymer-based adsorbents have recently gained great interest.•Precipitating or coating the surface of the employed adsorbent with nanoparticles was one of the most effective methods.•Efficiently synthesis of magnetite.•Present the impact of geopolymer modification by precipitating nano-magnetite in boosting the adsorption capacity of contaminants. In this work magnetite/geopolymer composite (MGP) was synthesized using a chemical co-precipitation technique. The synthesized materials were characterized using several techniques such as: “X-ray diffraction (XRD), Fourier- transform infrared spectroscopy (FTIR), vibrating sample- magnetometer (VSM), field-emission scanning electron microscopy (FESEM), energy dispersive X-ray spectroscopy (EDS), Brunauer–Emmett–Teller (BET) and Barrentt-Joyner-Halenda(BJH)” to analysis the structure and morphology of the geopolymer and the obtained composite. The analysis indicated that metal oxide predominantly appeared at the shape of the spinel structure of magnetite, and that the presence of nano-magnetite had a substantial impact on the surface area and pore structure of the geopolymer. Methylene blue adsorption on the MGC was investigated. The specific surface area of the geopolymer and Fe3O4/geopolymer composite was determined to be 26.604 m2/g and 69.04 m2/g, respectively. It was revealed that a mixture of Fe3O4 and geopolymer with percent 10% magnetite to geopolymer had high adsorption performance on MB, with a removal rate of over 95%, which was much greater than that of separate mesoporous geopolymers. The synthesized nanocomposites as promising adsorbents have a potential application in the removal of dyes from aqueous solution. Langmuir and Frendulich isotherm models were used to analyze the equilibrium data, the Frendulich model revealing a strong correlation coefficient. The kinetic process's results were in accordance with the pseudo-second-order model. Fluidization of mass was used to demonstrate dye breakthrough curves under the influence of various operating conditions, and the actual results fitted with the predicted data produced using an artificial neural network(ANN).