New insights into the application of fungal biomass for Chromium(VI) bioremoval from aqueous solutions using Design of Experiments and Differential Evolution based Neural Network approaches

Abstract

New investigations were carried out to demonstrate the ability of Trichoderma viride dead biomass for the bioremoval of Cr(VI) from aqueous solutions. The gathered experimental data were initially modelled considering both adsorption and reduction kinetic models, followed by equilibrium models. In the next step, Design of Experiments method (DoE) and a Differential Evolution (DE) algorithm were applied for determining the optimal Response Surface Methodology and Artificial Neural Network (ANN) models which are able to correlate the process efficiency with the experimental conditions. In addition, DE (in combination with the previously determined ANN) was used to obtain the optimal working conditions for maximum process efficiency. These optimization procedures allow setting various process parameters and working conditions which ensure the maximum bioremoval efficiency. DoE highlighted that all the study parameters have statistically significant individual influence on Cr(VI) bioremoval efficiency and, for example, at pH 2 and a temperature of 50 °C, 100% of Cr(VI) is bioremoved if the biosorbent dosage is 10 g/L, considering a minimum contact time of 2 h and given a maximum initial concentration of 122.5 mg/L. According to the ANN model, a contact time set at 24 h yields optimal values for Cr(VI) bioremoval by dead biomass considering pH 1.00, 3 g/L biosorbent dosage, 23 mg/L metallic ion concentration and a temperature of 50 °C. pHpzc, FT-IR and SEM-EDX analyses were included for biomass characterization and to underline the bioremoval mechanism of Cr(VI). Our results are providing a solid basis for the development of technologies for detoxification of contaminated effluents.