The novel green bioadsorbent, Centaurea stem, was utilized for crystal violet removal from aqueous solutions. SEM and FT-IR were used for characterization of Centaurea stem. The effects of the pH, time, temperature, bioadsorbent amount, and initial dye concentration were investigated. Response surface methodology was used to depict the experimental design and the optimized data of pH 12.57, time 19.661, temperature 38.94 °C, amount of bioadsorbent 12.218 mg, and initial dye concentration 36.62 mg L-1 were achieved. Moreover, artificial neural network (ANN) and simulated annealing (SA) were applied for prediction and optimization of the process respectively. The SA acquired optimum conditions of 10.114, 7.892 min, 25.127 °C, 64.405 mg L-1, 14.54 mg for pH, time, temperature, initial dye concentration, and bioadsorbent amount, respectively which were more close to the experimental results and indicated higher ability of SA-ANN in prediction and optimization of the process. The adsorption isotherms confirm the experimental data were appropriately fitted to the Langmuir model with high adsorption capacity of 476.190 mg g-1. The thermodynamic parameters were evaluated. The positive ΔH° and ΔS° values described endothermic nature of adsorption. The adsorption of crystal violet followed the pseudo-second order kinetic model.
Keywords: Artificial neural network; Centaurea stem; Dye removal; Green bioadsorbent; Response surface methodology; Simulated annealing.
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