ORIGINAL ABSTRACT

The increasingly severe glyphosate pollution poses a serious threat to human and environmental safety, and Metal-organic frameworks (MOFs) are regarded as promising adsorbents due to their unique structure properties. Molecular simulation studies provide a rapid method for identifying candidate materials and elucidating the interaction mechanisms between adsorbents and target compounds at the molecular level. In this study, Grand Canonical Monte Carlo (GCMC), Molecular Dynamics (MD), and Density Functional Theory (DFT) were employed to evaluate the adsorption capacity and diffusion behavior of glyphosate in six MOFs, including MIL-101(Cr), MIL-100(Cr), Cu-BTC, DUT-23(Cu), UiO-66 and IRMOF-3. The simulation results indicate that MIL-101(Cr) exhibits the highest adsorption capability and diffusion coefficient for glyphosate, while UiO-66 shows the lowest adsorption capability. DFT analysis further demonstrated that the most stable binding configuration involves the formation of stable complexes between glyphosate and the chromium (Cr) metal center, which significantly enhances adsorption efficiency. To optimize performance, MIL-101(Cr) was modified by substituting Cr with aluminum (Al), iron (Fe), and vanadium(V). Results indicate that altering the metal cation in MIL-101(M) directly influences glyphosate adsorption and diffusion properties, with MIL-101(Al) emerging as the most effective adsorbent. This study provides a novel molecular simulation-based strategy for screening high-performance glyphosate adsorbents, offering critical insights for future adsorbent design.