Computational investigation and mechanistic study of Nano-TiO2 particles compared with the TiO2 molecular crystal for wastewater treatment through DFT and Monte Carlo simulation
摘要
The optimization of TiO2 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 TiO2 in both molecular and nanoparticle phases using the GGA-PBE and GGA-RPBE functionals. Band gap analysis, DOS, and PDOS indicate that TiO2 molecules exhibit a lower band gap (1.626 eV, GGA-PBE), enabling superior visible-light absorption compared to TiO2 nanoparticles (2.322 eV and 2.357 eV for GGA-PBE and GGA-RPBE). GGA-RPBE accurately predicts the TiO2 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 TiO2 nanoparticles (0.43) is more favorable than that of molecules (0.57), indicating greater charge-carrier efficiency. TiO2 nanoparticles also demonstrate superior adsorption for pollutants, such as Methylene Blue (MB), SO3, Cr6+, CO2, 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 TiO2 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 TiO2: nanoparticles excel in adsorption-driven wastewater treatment, while molecular TiO2 is more effective for visible-light photocatalysis. These insights contribute to optimizing TiO2-based pollutant removal strategies using nanoparticles for environmental applications.