Quantum adsorption mechanism of gelatin cellulose hydrogel for the effective removal of Cu2+ and Co2+ from wastewater using artificial neural networks

Abstract In this work, n-GCHM was used for the removal of Cu2+ and Co2+ from wastewater. The adsorbent material (n-GCHM) was characterised using SEM and TGA. The following optimum conditions were obtained: a contact time of 120 min and pH 5 for the removal of Cu2+ and Co2+. The maximum adsorption capacity of Cu2+ and Co2+ was 5.8343 mg/g using n-GCHM. The highest percentage removal of Cu2+ and Co2+ on n-GCHM at pH 5 was 80 and 80.5%, respectively. The experimental data successfully fitted to pseudo-second-order kinetic, and also fitted well to the Freundlich isotherm model. The process of adsorption was spontaneous and exothermic in nature. To obtain extensive information on the adsorption process of metal ions on the functional groups of adsorbents, the quantum adsorption mechanism was investigated using DFT. The molecular orbital approach has shown that the HOMO and LUMO were located on –NCN– and LUMO on –NCO–. The quantum adsorption mechanism has shown that the binding energies of Cu2+ and Co2+ on imine functional groups were −60,604.399 and −53649.06 eV, respectively. On the –NCO– functional group, the binding energy was −58587.608 and −51632.618 eV, respectively, for Cu2+ and Co2+. Quantum mechanical methods using the ANN approach have been demonstrated to be accurate.