Equilibrium study of the binary mixture of cadmium–zinc ions biosorption by the Sargassum filipendula species using adsorption isotherms models and neural network

In this work, experiments have been carried out in the batch reactor to obtain equilibrium data of the individual biosorption and the mixture of cadmium and zinc ions by the biomass of the Sargassum filipendula species pre-treated with 0.5 mol/L calcium chloride. The experiments have been performed for the chosen temperature of 30 °C and operational conditions such as constant agitation and pH 5.0. Six adsorption isotherms models of the Langmuir type have been tested to represent the equilibrium data of the binary system. The artificial neural nets technique was used to fit the equilibrium experimental data. Different types of the net architecture have been tested varying the neurons number of the entrance and the hidden layer. The equilibrium concentrations of the fluid phase were used as input variables and the equilibrium concentrations of the biosorbent were used as output variable. The obtained simulation results have shown that the applied technique of artificial neural network has better adjusted the equilibrium data of the binary system when compared with the conventional biosorption isotherm models.