Zr-based metal-organic frameworks (MOFs) are typically employed in heterogeneous catalysis due to their porosity, chemical and thermal stability, and well-defined active sites. Density functional theory (DFT) is the workhorse to compute their electronic structure; however, it becomes very costly when dealing with reaction mechanisms involving large unit cells and vast configurational spaces. Semiempirical quantum mechanical (SQM) methods appear as an alternative approach to simulate such chemical systems at low computational cost, but their feasibility to model catalysis with MOFs is still unexplored. Thus, here we present a benchmark study on UiO-66 to evaluate the performance of SQM methods (PM6, PM7, GFN1-xTB, GFN2-xTB) against hybrid DFT (M06). We evaluate defective nodes, ligand exchange reactions, barrier heights, and host–guest interactions with metal nanoclusters. Despite some caveats, GFN1-xTB on properly constrained models is the best SQM method across all studied properties. Under proper supervision, this protocol holds promise for application in exploratory high-throughput screenings of Zr-based MOF catalysts, subject to further refinement with more accurate methods.This work has been funded by MICIU/AEI/10.13039/501100011033 and FSE+ (RYC2022-035453-I, PID2020-119116RA-I00), Xunta Distinguished Researcher program (ED431H 2020/21), the Xunta de Galicia (Centro de Investigación do Sistema Universitario de Galicia accreditation 2023-2027, ED431G 2023/03), and the European Union (European Regional Development Fund─ERDF). The authors acknowledge CESGA (“Centro de Supercomputación de Galicia”) for providing generous computational resources
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