High-Throughput Screening Assisted Discovery of Robust Metal-Organic Frameworks for Efficient Ambient NO₂ Removal

Nitrogen dioxide (NO₂) is a hazardous air pollutant that poses severe threats to sustainable air pollution control, yet its efficient ambient capture remains a major challenge. Here, we integrate a NO₂-specific high-throughput computational screening (HTCS) of over 15,000 metal-organic frameworks (MOFs) from the CoRE database with targeted experimental validation to identify robust aluminum-based MOFs for selective NO₂ capture. Guided by the physicochemical characteristics of NO₂ and synthetic feasibility principles, four optimized Al-MOFs, i.e., KMF-1, CAU-23, MIL-160, and MOF-303, incorporating distinct heteroatom functional sites (-NH, -S, -O, and -N-NH, respectively), were investigated to probe the structure-adsorption correlations. Among them, MOF-303 exhibited an exceptional dynamic NO₂ capacity of 5.31 mmol·g^-1, surpassing most reported porous adsorbents. Spectroscopic analyses and DFT calculations revealed that synergistic dipole interactions and hydrogen bonding at unique -N-NH bifunctional sites governed adsorption behavior. Such site-specific interactions endowed MOF-303 with long-term stability and regenerability, also validating the physicochemical descriptor-guided screening rationale and confirming its reliability under realistic conditions. Together, these results connect theoretical prediction with experimental verification, establishing a transferable paradigm for targeted environmental remediation and next-generation materials screening.