4.7 Article

In situ self-assembled cationic lanthanide metal organic framework membrane sensor for effective MnO4- and ascorbic acid detection

Journal

ANALYTICA CHIMICA ACTA
Volume 1142, Issue -, Pages 211-220

Publisher

ELSEVIER
DOI: 10.1016/j.aca.2020.10.062

Keywords

Cationic metal organic framework; Luminescence membrane sensor; On-off-on mode; MnO4- detection; Ascorbic acid detection

Funding

  1. National Natural Science Foundation of China [21873025, 22072034, 22001050]

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Developing a novel membrane sensor for accurate detection of ascorbic acid (AA) with high sensitivity and simple operation has been successful. The membrane sensor shows stable performance in experiments and meets the requirements for precise detection in real biological samples.
Developing portable membrane sensors to accurately detect the biomolecule ascorbic acid (AA) is extremely important for food safety and human health. Herein, we successfully design and synthesize a novel cationic metal organic framework (Eu-pbmc, Hpbmc = 2-(pyridine-2-yl)-1H-benzimidazole-5carboxylic acid) and assemble polyacrylonitrile/Eu-pbmc membrane (PEM) by an in-situ growth strategy. Benefiting from the appreciable loading of Eu-pbmc nanoparticles and high water permeation flux, PEM possesses effective detection for MnO4- with a limit of detection (LOD) of 17 nM. Utilizing the cationic porous framework, we load MnO4- into PEM and construct a on-off-on system for effective AA detection. The oxidative MnO4- can be reduced by AA and the resulting turn-on luminescence can reflect the concentration of AA. Compared with pure Eu-pbmc crystals, PEM exhibits improved AA detection performance with LOD of 48 nM and detection time of 1 min via a concise detection operation. The stable membrane sensor realizes an accurate detection in real biological samples, meeting the practical requirement. Moreover, an IMP logic gate is helpful to analyze MnO4- and AA in water. The proposed novel luminescence platform as well as reasonable on-off-on luminescence mode provide a promising method for AA detection. (C) 2020 Elsevier B.V. All rights reserved.

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