| description abstract | For the first time, a comprehensive study of 35 multiparameter isotherm models was conducted to describe the dynamics of the adsorption of acridine orange (AO) dye on an abundantly available agricultural waste, i.e., overripe Abelmoschus esculentus seedpods. The purpose of this work is to assess the most reliable model for the design and development of an effective batch adsorber system. Analysis of experimental isotherm data was done by scrutinizing one-, two-, three-, four-, and five-parameter models at three different temperatures to understand specific parameters for the design process. Detailed error analysis is carried out to check the accuracy and adequacy of the best fitting isotherm model for experimental data. The isotherm data are in good agreement with the Fritz-Schlunder-V model. Later, experimental data are extensively investigated for dye-biosorbent/dye interactions through Fowler-Guggenheim, Flory-Huggins, Kiselev, Frumkin, Hill-de Boer, and El-Awady isotherm modeling. As a result, the adsorption phenomenon that provides evidence of a multilayer formation shows an attractive interaction between the adsorbed species and the adsorbent surface. Most importantly, an artificial neural network (ANN)-based empirical model was developed to illustrate the dye sequestration process. The ANN-predicted and experimentally observed results were compared (R2=0.9964) to test the accuracy of the model. | |
