A Density Functional Theory Study of Na-PAC/PATS-Modified Shofirkon Bentonite as a Composite Sorbent for Heavy-metal Cations and Organic Pollutants

Abstract

Aims: To build a finite cluster model of the active fragment of Na-PAC/PATS-modified Shofirkon bentonite (MSB) and to use density functional theory (DFT) to compute the electronic, reactivity and thermodynamic descriptors that govern its adsorption and to correlate these descriptors with experimentally measured adsorption capacities towards heavy-metal cations and organic pollutants. Study Design: A combined computational (DFT cluster modelling) and experimental (batch-adsorption) was used. Methodology: A composite sorbent was prepared from Shofirkon bentonite (Bukhara region) by successive modification with a sodium-form polyaluminium chloride reagent (Na-PAC) and a polyaluminium–titanium–silicate pillaring agent (PATS), followed by calcination. The active fragment was modelled at the B3LYP/6-31G(d,p) level, with the LANL2DZ effective-core potential applied to Pb, Cd and Cu, and with implicit-water (SMD) single-point corrections. Equilibrium geometry, Mulliken charges, dipole moment, frontier orbitals (HOMO/LUMO), global reactivity descriptors and thermodynamic functions were obtained. Batch adsorption of Pb²⁺, Cu²⁺, Cd²⁺, methylene blue and phenol was measured in triplicate and fitted to the Langmuir and Freundlich isotherms. Results: The optimised cluster corresponds to a low-energy minimum with chemically reasonable Si–O, Al–O and Ti–O bonds. Electron-deficient metal centres and nucleophilic oxygen sites were identified; the dipole moment (6.42 D) indicates a polar surface, whereas the HOMO–LUMO gap (4.88 eV) indicates a stable, wide-gap framework. Computed adsorption energies decreased in the order Pb²⁺ > Cu²⁺ > Cd²⁺ > methylene blue > phenol, consistent with hard–soft acid–base theory and the experimental capacities (Pearson r ≈ 0.98). Conclusion: The Na-PAC/PATS treatment increases the density of active adsorption centres and the surface affinity towards pollutants. The descriptor-based cluster analysis reproduces the experimental selectivity trend and provides a useful interpretive tool for the design of composite sorbents from local mineral raw materials, within the acknowledged limits of a finite cluster model.