Methylene blue (MB) is the cationic dye that is widely used for coloring cotton, wool, and silk. Since MB is harmful to human beings and toxic to microorganisms, there is the need to find cheap and efficient methods for removal of MB from wastewater prior to disposal into natural waters. In the present study, MB adsorption potential of MgO/AC prepared using a sol–gel-thermal deep-coating method was compared with the activated carbon (AC). The central composite design (CCD) as a method of the response surface methodology (RSM) was applied to minimize the number of runs and process optimization. The characterization of the microporous MgO/AC composite showed that the magnesium oxide nanoparticles were successfully coated on the AC and the BET specific surface area of AC and MgO/AC were 1,540 and 1,246 m2/g, respectively. The MB removal efficiency and the maximum adsorption capacity of AC and MgO/AC were 89.6, 97.5% and 571.7, 642.3 mg/g, respectively under optimum operational conditions of initial dye concentration of 100.9 mg/L, the adsorbent dosage of 69.4 mg/100 mL, pH of 10.2 and contact time of 149.1 min. According to an analysis of variance (ANOVA), the initial dye concentration and its interaction with the other effective factors have a large impact on adsorption efficiency. Furthermore, the mechanism of adsorption followed the Langmuir isotherm (R2 = 0.9935, Δqe = 2.9%) and adsorption kinetics fitted by the pseudo-second-order model (R2 = 0.9967, Δqe = 6.6%). Finally, our results suggest that the prepared MgO/AC is an efficient and promising material for dye wastewater treatment.


  • MgO/AC composite (BET = 1,246 m2/g) prepared with the MB removal efficiency and the maximum adsorption capacity of 97.5% and 642 mg/g, respectively.

  • The optimum operating conditions were determined with low error by the RSM.

  • The CCD revealed that predicted data were in agreement with observed ones (R2 = 0.9969).

  • The data of this adsorption fits greatest to the isotherm model of Langmuir and pseudo-second-order kinetic model.

Graphical Abstract

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