化学
多路复用
指纹(计算)
鉴定(生物学)
组分(热力学)
传感器阵列
对偶(语法数字)
化学传感器
纳米技术
色谱法
计算机安全
热力学
生物
计算机科学
材料科学
物理化学
电极
文学类
数学
物理
植物
统计
生物信息学
艺术
作者
Jie Chi,Yingxi Qin,Yan‐Yan Song,Liang Feng
标识
DOI:10.1021/acs.analchem.5c03414
摘要
The pervasive, multicomponent contamination of environmental matrices by antibiotics─and the persistent accumulation of their residues─poses serious threats to ecosystems and human health. Consequently, there is an urgent need for analytical strategies that can simultaneously detect and differentiate multiple classes of antibiotic residues. In this study, we designed a dual-emissive Eu-doped Zr metal-organic framework (ZrEu-MOF) that acted as a single cross-reactive element yet delivered a multidimensional fluorescence response for antibiotics. Benefiting from the distinct sensing mechanisms and differential binding affinities between the MOF and various antibiotics, the sensor array generated unique fluorescent fingerprint patterns for each antibiotic. By integrating multidimensional fluorescence data (intensity and emission wavelength) with multivariate statistical analysis, the system achieved precise pattern recognition. This single-element-based sensor array effectively distinguished 12 antibiotics and exhibited robust quantitative performance for individual compounds. Notably, it also demonstrated outstanding discrimination capability for multicomponent mixtures and enabled accurate identification of antibiotics in real environmental samples. This work establishes single-element dual-emission MOFs as practical platforms for high-throughput, pattern-recognition-based monitoring of multiclass antibiotic contaminants in real environments.
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