Computational investigation and mechanistic study of Nano-TiO2 particles compared with the TiO2 molecular crystal for wastewater treatment through DFT and Monte Carlo simulation

Abstract The optimization of TiO 2 using density functional theory (DFT) and Monte Carlo simulations reveals its structural and electronic properties, thereby enhancing its photocatalytic and adsorption properties for wastewater treatment. This study examines the photocatalytic behavior of TiO 2 in both molecular and nanoparticle phases using the GGA-PBE and GGA-RPBE functionals. Band gap analysis, DOS, and PDOS indicate that TiO 2 molecules exhibit a lower band gap (1.626 eV, GGA-PBE), enabling superior visible-light absorption compared to TiO 2 nanoparticles (2.322 eV and 2.357 eV for GGA-PBE and GGA-RPBE). GGA-RPBE accurately predicts the TiO 2 molecular-phase band gap (1.753 eV vs. 1.76 eV exp., 0.4% error), thereby justifying its selection for reliable DFT studies of related crystal structures. The effective mass of TiO 2 nanoparticles (0.43) is more favorable than that of molecules (0.57), indicating greater charge-carrier efficiency. TiO 2 nanoparticles also demonstrate superior adsorption for pollutants, such as Methylene Blue (MB), SO 3 , Cr 6+ , CO 2 , and Pb, due to their high surface area, small particle size, and abundant active sites. Monte Carlo simulations using the Absorption Locator confirm that nanoparticles exhibit higher adsorption energy and stronger pollutant binding affinities than TiO 2 molecules. These results highlight the potential of nanoparticles for efficient removal of toxic dyes, heavy metals, and acidifying compounds. Ultimately, this study underscores the complementary strengths of TiO 2 : nanoparticles excel in adsorption-driven wastewater treatment, while molecular TiO 2 is more effective for visible-light photocatalysis. These insights contribute to optimizing TiO 2 -based pollutant removal strategies using nanoparticles for environmental applications.