JOURNAL ARTICLE

A Magnesium Organic Framework Fluorescent Sensor for Selective Detection of Nitrofuran Antibiotics and Inorganic Pollutants.

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

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Zhao, Xiangyu; Yao, Xiaoyan; Lv, Xueyi; Zhang, Xishuo; Sun, Hanlei; Wang, Hongzhi; Li, Yuhan; Yao, Shuo; Liu, Licheng 3 of 3

Abstract

A novel 3D magnesium‐based metal organic framework (Mg‐MOF) has been solvothermally synthesized using 5‐(pyridin‐4‐yl)isophthalic acid. The ligand has demonstrated to preserve two types of coordination modes depending on the connection mode of the pyridine group. The uncoordinated pyridine groups provide Lewis base sites (LBSs), whereas the coordinated ones promote to form a rarely reported eight‐connected tetranuclear Mg clusters. Benefiting from the multinuclearity with high number of connections, the framework keeps good performance of high thermal stability until 500°C. Furthermore, the framework exhibits potential open metal sites (OMSs) benefiting from the terminal coordinated water groups of the metal clusters. Owing to the abundant active sites, the Mg‐MOF exhibits good sensitivity to nitrofuran antibiotics and Cr2O72−, with high KSV (at 104 M−1 level) and low limit of detection (LOD) values (∼10−6 M). Density functional theory (DFT) investigation reveals that the interchange of the HOMO–LUMO energy levels of the framework and antibiotics is responsible for the sensing activity. In addition, the Mg‐MOF is greatly recyclable in five cycles while maintaining the structural rigidity and sensing activity, making it a promising luminescence probe material. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:Applied Organometallic Chemistry. 2025/01, Vol. 39, Issue 1, p1
  • Document Type:Article
  • Subject Area:Chemistry
  • Publication Date:2025
  • ISSN:0268-2605
  • DOI:10.1002/aoc.7786
  • Accession Number:181921738
  • 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.)

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