Activated spent tea (AST) was prepared and characterized by using different techniques such as BET, FTIR and SEM. It is used for methylene blue (MB) dye removal from aqueous solution in a batch system. Experimental results showed that natural basic pH, increased initial dye concentration, and high temperature favored the adsorption. Analysis based on the artificial neural network (ANN) indicated that the adsorbent dose and time with the relative importance of 30.03 and 35.44%, respectively, appeared to be the most influential parameters in the MB adsorption. The adsorption of MB was relatively fast and the Avrami fractional order and pseudo-second-order kinetic models showed satisfactory fit with the experimental data. The equilibrium data were well fitted by the Langmuir and Liu isotherm models, with a maximum sorption capacity of 104.2mg/g. Also, the obtained values of thermodynamic parameters showed that the adsorption of MB onto AST is endothermic and spontaneous. The results of this study indicated that AST was a reliable adsorbent for removing cationic dyes from wastewater.
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Babaei, A.A., Khataee, A., Ahmadpour, E. et al. Optimization of cationic dye adsorption on activated spent tea: Equilibrium, kinetics, thermodynamic and artificial neural network modeling. Korean J. Chem. Eng. 33, 1352–1361 (2016). https://doi.org/10.1007/s11814-014-0334-6
- Activated Spent Tea
- Methylene Blue
- Artificial Neural Network