Application of chitosan/graphene and chitosan/graphene oxide composites for removal of Cu and Pb
Abdel Salam El-Sheikh, Nabil S. Abdelaziz, Khaled S. Amin, Hanan Elhaes, Medhat Ibrahim
Abstract
Water pollution caused by heavy metals such as lead (Pb) and copper (Cu) represent a critical global challenge due to their toxicity and adverse impacts on both human health and the environment. Among several remediation methods, adsorption using polymer-based sorbents like chitosan (Cs) has emerged as a promising approach. In this study, chitosan interacted with graphene (Gr) and graphene oxide (GrO) to enhance its possible interaction with di-hydrated Pb and Cu. The electronic properties of Cs/Gr and Cs/GrO composites were studied using density functional theory (DFT) at the B3LYP/LANL2DZ level of theory. Physical parameters, including total dipole moment (TDM), HOMO-LUMO energy gap (∆E), and global reactivity descriptors, were calculated. Additionally, molecular electrostatic potential (MESP), density of states (DOS), and frontier molecular orbitals (FMO) were analyzed. The results demonstrated significant improvements in electronic properties, with increased total dipole moment (TDM) values (7.300 Debye for Cs/Gr and 6.311 Debye for Cs/GrO) and reduced ∆E (3.671 eV for Cs/Gr and 2.701 eV for Cs/GrO), indicating enhanced reactivity. Adsorption energies (Ea) for interactions with di-hydrated Pb and Cu were also evaluated, showing proper binding where Ea values of – 13.869 eV for Cs/Gr/di-hydrated Pb, – 13.689 eV for Cs/Gr/di-hydrated Cu, – 12.975 eV for Cs/GrO/di-hydrated Pb, and − 14.211 eV for Cs/GrO/di-hydrated Cu. Quantum Theory of Atoms in Molecules (QTAIM) analysis confirmed Ea findings. Cs/GrO composites were synthesized and FTIR spectra were measured and compared to computed vibrational frequencies. This study combines DFT and QTAIM to provide a comprehensive understanding of the selective adsorption behavior of Cs/Gr and Cs/GrO composites for di-hydrated Pb and Cu, supported by FTIR validation of the computational models.