Artificial neural network modelling for biodecolorization of Basic Violet 03 from aqueous solution by biochar derived from agro-bio waste of groundnut hull: Kinetics and thermodynamics

Abstract

In this study, Levenberg Marquardt back propagation algorithm was used to train the Artificial Neural Network (ANN) and to predict the adsorptive removal of cationic dye Basic Violet 03 (BV03) by biochar derived from biowaste of groundnut hull. The experimental conditions such as solution pH, biochar dose, initial dye concentration, contact time and temperature were used as input variables and BV03 percentage removal as target. The hidden and the output layer of the network was trained by tangent sigmoid and liner transfer functions. The feasibility of the adsorption process is evaluated by the kinetic studies and it exhibited that pseudo-second order kinetic models fit well with experimental data. The adsorbent stability and adsorption mechanism has been discoursed by the thermodynamic characteristics and sorption free energy. The predicted target values were compared with the experiment resulted in a better correlation coefficient of 0.9920. Thus, the results attained from this ANN model was found to be effective in predicting the percentage removal of BV03 dye at any given operating condition.