RESUMO
S-doped and Cu- and Co-doped TiO2 was synthesized by a sol-gel method and characterized by FE-SEM, XRD, EDX and FTIR. The Co/Cu/S-TiO2 nanocomposite loaded on the activated carbon as new nanoadsorbent was used for simultaneous removal of methylene blue (MB) and sunset yellow (SY) from aqueous solution by ultrasonic-assisted adsorption method. In this work, central composite design (CCD) and adaptive neuro-fuzzy inference system (ANFIS) as a support tool for examining data and making prediction are used to recognize and predict the removal percentage in MB and SY dye solution of different concentrations. The predictive capabilities of CCD and ANFIS are compared in terms of square correlation coefficient (R2), root mean square error (RMSE), mean absolute error (MAE) and absolute average deviation (AAD) against the empirical data. It is found that the ANFIS model shows the better prediction accuracy than the CCD model. In addition to, the optimization of ultrasound-assisted simultaneous removal of methylene blue (MB) and sunset yellow (SY) on the Co/Cu/S-TiO2/AC nanocomposite by response surface methodology (RSM) for the optimization of the process variables, such as MB and SY concentrations, Co/Cu/S-TiO2/AC nanocomposite dose and sonication time, was investigated. Various isotherm and kinetic models were used in the experimental data. The results revealed that the langmuir isotherm and pseudo-second-order model had a better correlation than the other models.
