Comparative study of malachite green adsorption onto activated carbon prepared from Ziziphus wood and ZnO nanoparticles loaded AC: artificial neural network modeling and optimization

In this study activated carbon prepared from Ziziphus wood was modified by ZnO nanoparticles loaded on activated carbon (ZnO-NPs-AC) and checking its applicability for malachite green (MG) removal. The properties of ZnO-NPs-AC were identified by X-ray diffraction, transmission electron microscopy, field emission scanning electron microscopy, and Brunauer-Emmett-Teller. Response surface methodology and artificial neural network (ANN) model learned with Levenberg-Marquardt algorithm are used for modeling of MG adsorption onto present support. The mean squared error and coefficient of determination (R-2) for the optimal ANN model with eight neurons at hidden layer were 0.9999 and 0.00116 by AC and 0.9970 and 0.01789 by ZnO-NPs-AC for testing data, respectively. The optimum conditions were set as 0.02 and 0.015 g for ZnO-NPs-AC and AC are applicable for successful removal of MG (97.38% and 71.35%) in reasonable time (5 min for ZnO-NP-AC and 4.65 min for AC). The adsorption isotherm is efficiently explained by Temkin and Langmuir for AC and ZnO-NPs-AC adsorbent. The adsorption kinetics of MG excellently follows the pseudo-second-order kinetic model.