No. 3 (2017)
DOI https://doi.org/10.18799/24056529/2017/3/147
Synthesis and characterization of novel activated carbon from Medlar seed for chromium removal: Experimental analysis and modeling with artificial neural network and support vector regression
In this study, for the first time the activated carbon has been produced from medlar seed (Mespilus ger- manica) via chemical activation with KOH. The carbonization process was carried out at different tem- peratures of 450, 550, 650 and 750 °C. The Nitrogen adsorption-desorption, Fourier transform infrared spectroscopy (FTIR) and Field Emission Scanning Electron Microscope (FESEM) analyses were carried out on the adsorbents. The effect of operating parameters, such as pH, initial concentration of Cr(VI), adsor- bent dosage and contact time were investigated. The experimental data showed better agreement with the Langmuir model and the maximum adsorption capacity was evaluated to be 200 mg/g. Kinetic studies indicated that the adsorption process follows the pseudo second-order model and the chemical reaction is the rate-limiting step. Thermodynamic parameters showed that the adsorption process could be con- sidered a spontaneous ( G < 0), endothermic ( H > 0) process which leads to an increase in entropy ( S > 0). The application of support vector machine combined with genetic algorithm (SVM-GA) and ar- tificial neural network (ANN) was investigated to predict the percentage of chromium removal from aque- ous solution using synthesized activated carbon. The comparison of correlation coefficient (R 2 ) related to ANN and the SVR-GA models with experimental data proved that both models were able to predict the percentage of chromium removal, by synthetic activated carbon while the SVR-GA model prediction was more accurate.
Keywords:
Activated carbon, Chromium removal, Medlar seed, Artificial neural network, Support vector regression