Tailored Fluorescent Metal–Organic Frameworks Hybrid Membrane Sensor Arrays: Simultaneous and Selective Quantification of Multiple Antibiotics

作者：Tongtong Ma, Qiao Huang, Lei Yuan, Shugang Yan, Yalin Mo, Yibin Ying, Yingchun Fu, Jinming Pan · 发表于：Advanced Science · 年份：2025 · DOI：10.1002/advs.202502452 · 被引用次数：13 · 研究领域：Advanced biosensing and bioanalysis techniques、Molecular Sensors and Ion Detection、Metal-Organic Frameworks: Synthesis and Applications

Sensor array offers significant potential for rapid, high-throughput antibiotic detection. However, cross-reactivity-based sensor arrays often lack accuracy, despite comprehensive data analysis; while traditional high-affinity-based sensors based on antibodies/aptamers frequently suffer from complicated design and poor robustness. Here, a filterable paper-based fluorescent metal-organic frameworks (MOFs) sensor array is developed for one-to-one recognition and quantification of multiple antibiotics. Three representative MOFs are designed to exceptional affinity and specificity for the target antibiotic. A filtration-assisted detection enhances sensitivity, achieving parts-per-billion (ppb)-level detection in mixed solutions. The proposed approach integrates recognition and signal generation, streamlined 10-min process. The robustness of the MOFs also enables direct detection in raw samples containing organic solvents, which is not achievable by conventional methods. Notably, the sensor array can be easily incorporated into a smartphone-based portable device, coupled with a user-friendly image analysis applet for one-step extraction and quantitative detection in chicken samples. Leveraging MOFs' versatility, this method can be extended to simultaneously detect a broad range of antibiotics, offering the potential for universal, high-throughput accurate detection of various chemical targets.