ali akbari

Curdled milk, as a novel nano biosorbent, was utilized for ultrasound-assisted removal of eosin blue and aniline blue from aqueous solutions. Curdled milk was characterized by Fouriertransform infrared spectroscopy, Brunauer–Emmett–Teller isotherm, and scanning electron microscopy-energy-dispersive X-ray spectroscopy techniques. The main factors of pH, sonication time, amount of biosorbent, temperature, and initial dye concentrations were investigated. Maximum adsorption capacities of 147.1 and 131.6 mg g–1 were acquired for eosin blue and aniline blue respectively at optimum conditions including pH of 3–4, biosorbent amount of 10 mg, the temperature of 25°C, time of 5 min, and initial dye concentration of 10–30 mg L–1. Hybrid artificial neural network- genetic algorithm and shuffled frog leaping algorithm (SFLA) were employed for prediction and optimization of the process respectively. The results revealed that SFLA had the high capability for the optimization of the process. The biosorption data ideally fitted to the Langmuir model. Adsorption of aniline blue and eosin blue on to the curdled milk follows the pseudo-second-order kinetic model. Thermodynamic studies presented the negative values of ΔH° in which indicated the exothermic nature of the adsorption process and negative values of ΔG° showed the favorability and spontaneously occurrence of the adsorption process.