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Research Article | Open Access | Just Accepted

Polyoxometalate-incorporated metal–organic frameworks as electrochemical sensors for ascorbic acid, dopamine and uric acid

Shuang Liu1, Li-Ping Wang1, Jia-Jia Li1, Xiang-Jie Bo1, Dong-Ying Du1( ), Zhong-Min Su2

1 National & Local United Engineering Laboratory for Power Battery, Department of Chemistry, Northeast Normal University, Changchun 130024, China

2 State Key Laboratory of Supramolecular Structure and Materials, Institute of Theoretical Chemistry, College of Chemistry, Jilin University, Changchun 130021, China

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Abstract

Real-time analysis of small-molecule metabolites such as ascorbic acid (AA), dopamine (DA), and uric acid (UA) is valuable for investigating biological systems and supporting disease diagnosis. As a representative metal-organic framework (MOF), MIL-101(Cr) combines strong chemical stability with a large specific surface area, demonstrating considerable potential in numerous fields. Herein, we demonstrated a series of polyoxometalate (POM)-incorporated bimetallic MOF composites, MIL-101(Cr2Fe)-POM-T (POM = SiW12 or PW12, T = 180 or 220), which were evaluated as electrochemical sensors for measuring AA, DA, and UA. Among them, MIL-101(Cr2Fe)-PW12-220 delivered the strongest electrochemical sensing response in 0.1 M PBS (pH = 7.0). After optimization, MIL-101(Cr2Fe)-PW12-220 demonstrated a broad linear detection range (412−6550, 1−160, and 2−160 μM) and low limits of detection (51.1, 0.385, and 0.644 μM, S/N = 3) when AA, DA, and UA were measured individually. In addition, MIL-101(Cr2Fe)-PW12-220 also enabled AA, DA, and UA analysis in human serum samples, supported by its broad linear range, low detection limits, selectivity, and stability.

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Cite this article:
Liu S, Wang L-P, Li J-J, et al. Polyoxometalate-incorporated metal–organic frameworks as electrochemical sensors for ascorbic acid, dopamine and uric acid. Polyoxometalates, 2026, https://doi.org/10.26599/POM.2026.9140168

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Received: 31 July 2026
Revised: 09 October 2026
Accepted: 15 October 2026
Available online: 16 October 2026

© The Author(s) 2026. Published by Tsinghua University Press.

Open Access This article is licensed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits use, sharing, distribution and reproduction in any medium, provided the original work is properly cited.