The biosorption of reactive red dye onto orange peel waste: a study on the isotherm and kinetic processes and sensitivity analysis using the artificial neural network approach.

The agricultural waste of orange peels (OPs) was utilized as a cheap biosorbent and then tested for its ability to treat the reactive red (RR) dye wastewater. Several experiments were done to get the equilibrium isotherm and kinetic-relevant data. In addition, several experimental factors such as solution pH, temperature, contact time, and initial RR dye concentration were studied, in light of their impact on the biosorption process. The utilized isotherm and kinetic models were evaluated by using the chi-square test and coefficient of determination parameters for their representation of real data. In addition, the obtained data of their biosorption capacities, at different conditions, were modeled by the artificial neural network (ANN) approach. The results of the isotherm study revealed that the experimental data can be best accounted by both the Langmuir and Temkin models, demonstrating that the RR molecules were sorbed to two or more different types of biosorption sites of OP. The kinetic study for determining the characteristics of the rate of diffusion demonstrated that the intraparticle diffusion process was not the sole rate-limiting step in the biosorption of the RR dye-OP couple. Furthermore, the biosorption process was chemisorption in nature, as the pseudo-second-order reaction proved to be the best representative model for the kinetic data. The outcome of modeling also assumed that using the ANN tool was useful to reproduce the data again and foretell the manner in which biosorption behaved. According to the results of the Langmuir model, it was found that the maximum OP uptake for the biosorption of the RR dye was up to 82 mg/g, observed at optimized values of the experimental parameters. Such prior results highlight that OP is an effective agent of biosorption in the elimination of RR dyes from polluted solutions, moreover, in a cost-effective manner.