2026-10-13T08:50:28Z https://api.figshare.com/v2/oai

oai:figshare.com:article/33763943 2026-09-14T22:05:33Z category_1 category_146 category_7 category_8 category_12 category_14 category_21 category_272 category_873 category_734 category_931 portal_63 item_type_3 month_year_09_2026

Heterometallic Eu/Cd-MOF Dual-Channel Fluorescent Sensor Array for Hierarchical Antibiotic Discrimination: From Cross-Class to Intra-Class Resolution Jing Li (10611) Xinyi Sun (4599382) Xu Xu (210339) Lei Zhang (38117) Biophysics Space Science Medicine Microbiology Cell Biology Molecular Biology Biotechnology Environmental Sciences not elsewhere classified Chemical Sciences not elsewhere classified Biological Sciences not elsewhere classified Information Systems not elsewhere classified specific differential modulation machine learning integration induced signal variations four antibiotic classes enabling robust identification electrospun fibrous membranes complex food matrices channel sensor array based rgb imaging 73 – 99 material multichannel sensing hierarchical antibiotic discrimination simultaneously achieve cross effectively mitigating concentration 3 +</ sup 2 +</ sup independent discrimination enables concentration effectively resolving chemical sensing system simplicity persistent challenge molecular weight molecular recognition longstanding trade including egg generalizable strategy blind samples analytical dimensionality accurate classification 64 %. 612 nm 450 nm 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. 2026-09-14T00:00:00Z Dataset Dataset 10.1021/acs.analchem.6c03993.s001 https://figshare.com/articles/dataset/Heterometallic_Eu_Cd-MOF_Dual-Channel_Fluorescent_Sensor_Array_for_Hierarchical_Antibiotic_Discrimination_From_Cross-Class_to_Intra-Class_Resolution/33763943 CC BY-NC 4.0