Efficiency of Artificial Neural Networks for Modeling of Malachite Green Adsorption by Tea Waste and Adsorption Isotherm Study

Nowadays water pollution is one of the most important problems in different societies. This problem increases with the development of countries. Existence of various dyes in waters is one of these important pollutions so adsorption can be used as an important method to eliminate dyes from waters. In this research, the adsorption of Malachite Green on odorant Do Ghazal tea waste was studied. The study of this issue was performed in laboratory’s temperature, with variation of different parameters like pH, adsorption time, amount of adsorbent and dye concentration. The results of the experiments show that the adsorption efficiency increases with more adsorbent addition, higher pH levels and time enhancement. Also the reduction of dye concentration causes better adsorption efficiencies. Moreover the study on isotherms of adsorption process confirmed that the adsorption obeys the Freundlich model. The results of this study show that the efficiency of Malachite Green elimination in aqueous solutions on odorant Do Ghazal tea waste was higher than 95%. An artificial neural networks (ANN) model was developed to predict the performance of the decolorization efficiency by the adsorption process based on the experimental data. A comparison between the predicted results of the designed ANN model and experimental data was also conducted. The ANN model yielded a determination coefficient of R2=0.9981. The model can describe the decolorization efficiency under different conditions. Odorant Do Ghazal tea can be used as a low cost and available adsorbent to removal of organic pollutants from contaminated waters. Artificial neural networks can be employed as an appropriate method for adsorption process modeling too.