Highly efficient simultaneous biosorption of Hg2+, Pb2+ and Cu2+ by Live yeast Yarrowia lipolytica 70562 following response surface methodology optimization: Kinetic and isotherm study

[Display omitted] •Novel biosorbent were identified for the biosorption of heavy metals.•FESEM-EDS and FTIR were applied to characterize the biosorbent surface.•Response surface methodology approach was used to optimize the process variables.•Effect of pH, contact time, metal concentration and temperature was investigated. In this research, biosorption of Hg2+, Pb2+ and Cu2+ from aqueous solution via Yarrowia lipolytica 70562 living mass was described. Correction and dependency of biosorption efficiency to effective variables like pH, initial Hg2+, Pb2+ and Cu2+ concentration, contact time and temperature was studied by central composite design under response surface methodology. Three responses were simultaneously studied by numerical optimization methodology. The optimum biosorption efficiency of Hg2+, Pb2+ and Cu2+ ions at 18, 22 and 25mgL−1 onto Y. lipolytica 70562 was found to be 99.26%, 101.15% and 99.74% at pH of 6.4 and 25°C after around 8h under well mixing. Finally, optimum condition for acceptable and repeatable agreement among experimental and real data was explored. The artificial neural network (ANN) model was used for predicting simultaneous ‎biosorption of Hg2+, Pb2+ and Cu2+ ions based on experimental data. It was found that ‎using ANN model with 12 neurons at hidden layer for all three ions, the R2 of 0.989 and MSE of ‎‎0.993 for Hg2+ ion were obtained. The R2 of 0.981 and MSE of ‎‎1.155 for Pb2+ ion were obtained and also for Cu2+ ion the values of the R2 and MSE were found to ‎be 0.971 and 1.589, respectively. Langmuir isotherm model was best fitted with the equilibrium experimental. The experimental kinetic data was represented well by using pseudo-second-order model and intraparticle diffusion model.