化学
维数之咒
荧光
生物系统
RGB颜色模型
传感器阵列
纳米技术
分子识别
分辨率(逻辑)
同种类的
信号(编程语言)
膜
高分辨率
匹配(统计)
模式识别(心理学)
特征(语言学)
节点(物理)
光电子学
鉴定(生物学)
人工智能
化学信息学
组合化学
计算机科学
作者
Jing Li,Xinyi Sun,Xu Xu,Lei Zhang
标识
DOI:10.1021/acs.analchem.6c03993
摘要
Abstract Discriminating structurally similar antibiotics requires analytical strategies that simultaneously achieve cross-class differentiation and intra-class fine identification─a persistent challenge in chemical sensing. Herein, we report a hierarchical molecular recognition platform based on a single mixed-ligand Eu/Cd heterometallic metal–organic framework (MOF) featuring atomically homogeneous emissive centers. Precise Eu3+ substitution at Cd2+ nodes yields two spectrally distinct emission channels at 450 nm (ligand-centered) and 612 nm (Eu3+-centered), which generate characteristic fluorescence fingerprints through analyte-specific differential modulation. Configured as a dual-channel sensor array, this single-MOF platform achieves 100% accurate classification of four antibiotic classes (fluoroquinolones, tetracyclines, sulfonamides, and aminoglycosides) and precisely resolves structurally analogous fluoroquinolones (ciprofloxacin, enrofloxacin, norfloxacin) differing by <10% in molecular weight. Machine learning integration further enables concentration-independent discrimination of three fluoroquinolones, effectively mitigating concentration-induced signal variations and enabling robust identification of blind samples. When integrated with electrospun fibrous membranes and smartphone-based RGB imaging, the portable device enables sensitive detection of FQs in complex food matrices, including egg, milk, and honey, with recoveries of 95.73–99.64%. This work establishes heterometallic node engineering as a generalizable strategy for single-material multichannel sensing, effectively resolving the longstanding trade-off between analytical dimensionality and system simplicity in molecular recognition.
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