JOURNAL ARTICLE

Trinuclear Cobalt/Nickel‐Based Metal–Organic Frameworks as Fluorescent Sensor Toward Quinolone Antibiotics.

  • Published In: Applied Organometallic Chemistry, 2025, v. 39, n. 2. P. 1 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Lin, Changjiao; Lu, Tianle; Lu, Xiaomei; Chen, Zilu; Liu, Dongcheng; Hu, Huan‐Cheng 3 of 3

Abstract

The leakage of quinolone antibiotics may bring serious hazards to plants, animals, and human; thus, the detection of quinolone antibiotics is of great urgent yet remains challenging issue. Herein, two isostructural metal–organic frameworks {[(CH3)2NH2]2[M3(μ3‐O)(BPDC)3(TPP)]·xMeCN·yDMF}n (M = Co, x = 8, y = 1, NS‐13; M = Ni, x = 7, y = 1, NS‐14; H2BPDC = 4,4′‐biphenyldicarboxylic acid; TPP = 2,4,6‐tris(4‐pyridyl)pyridine), have been successfully prepared through solvothermal method. NS‐13 and NS‐14 were three‐dimensional networks built form [M3(μ3‐O)]4+ clusters. Impressively, both NS‐13 and NS‐14 displayed good fluorescence response to norfloxacin, ofloxacin, and enrofloxacin with low limit of detection (LOD) and excellent recyclability, to our best knowledge, which are superior to most of reported metal–organic frameworks. Furthermore, density functional theory (DFT) calculations and fluorescence lifetime experiments uncovered the possible fluorescence probe mechanism of NS‐13 and NS‐14 toward the above‐mentioned quinolone antibiotics. This work extends the application of cluster‐based metal–organic frameworks in the detection of antibiotics. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:Applied Organometallic Chemistry. 2025/02, Vol. 39, Issue 2, p1
  • Document Type:Article
  • Subject Area:Health and Medicine
  • Publication Date:2025
  • ISSN:0268-2605
  • DOI:10.1002/aoc.7979
  • Accession Number:183988327
  • Copyright Statement:Copyright of Applied Organometallic Chemistry is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Looking to go deeper into this topic? Look for more articles on EBSCOhost.