High-throughput screening of bimetallic metal–organic frameworks for efficient generation of reactive oxygen species

Abstract Currently, the issue of bacterial drug resistance is becoming increasingly severe. Metal–organic frameworks (MOFs) are considered ideal catalysts for reactive oxygen species (ROS) generation and antibacterial applications due to their superior properties, though efficient screening of high-performance MOFs remains challenging. This study employs a dual-track high-throughput screening strategy combining density functional theory (DFT) and machine learning (ML) to predict and evaluate the ROS generation performance of MOFs. Key screening criteria include structural stability, pore size, adsorption capacity, open metal sites, O₂ activation potential, and reaction pathway free energy simulations. Bimetallic MOFs underwent DFT-ML dual-track screening, identifying Cu–Ag-4,4′-bipyridine (Cu–Ag–MOF, Cu:Ag = 1:2) and Cu–Zn-2,5-dihydroxyterephthalic acid (Cu–Zn–MOF, Cu:Zn = 1:3) as optimal candidates. Experimental results demonstrate superior performance of Cu–Ag–MOF, achieving H₂O₂ yields of 7.79 mmol g⁻¹ under light (60 min) and 3.03 mmol g⁻¹ in darkness. Antibacterial tests showed 99.9% sterilization rate after 30 min illumination and 55.4% efficiency in darkness after 60 min. The enhanced performance originates from bimetallic synergy that improves antibacterial capability and stability, enabling persistent ROS generation and continuous sterilization. This study advances understanding of MOFs catalytic mechanisms and establishes a transferable framework for designing multifunctional biomimetic catalytic materials.