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Electrochemical determination of levofloxacin with a Cu–metal–organic framework derivative electrode

  • Jie Zhou
  • , Jun Liu*
  • , Peng Pan*
  • , Tong Li
  • , Zhengchun Yang
  • , Jun Wei
  • , Peng Li
  • , Guanying Liu
  • , Haodong Shen
  • , Xiaodong Zhang
  • *Corresponding author for this work
  • Tianjin University of Technology
  • Harbin Institute of Technology

Research output: Contribution to journalArticlepeer-review

Abstract

Levofloxacin (LEV) is used in pharmaceuticals to treat bacterial infections, but is rarely metabolized by the human body, and hence, largely excreted. This leads to its accumulation in sewage, posing hazards to human health and the environment. Considering the drawbacks of existing methods to detect LEV, including a high cost, significant analysis time, and complex sample processing, the aim of this study was to devise an optimal detection method for LEV. A modified screen-printed electrode (SPE) using a Cu–metal–organic framework (MOF) derivative was proposed as an electrochemical sensor for LEV detection. They were characterized by transmission electron microscopy (TEM) and X-ray diffraction (XRD). The prepared Cu-MOF derivative offered a large specific surface area and highly dispersed active sites, which facilitated full contact with LEV. The electrochemical behavior of LEV was evaluated using cyclic voltammetry (CV) in the potential range of − 0.2 to 1 V. The linear response range was 0.1–100 μM, sensitivity was 1855 μA.mM−1.cm−2, and detection limit was 0.016 μM. The detection limit and sensitivity of differential pulse voltammetry (DPV) were 0.17 μM and 183 μA.mM−1.cm−2, respectively. The detection limit and sensitivity of chronoamperometry (CA) were 0.037 μM and 825 μA.mM−1.cm−2, respectively. The method exhibited significant selectivity and stability. The use of this electrochemical sensor containing the Cu-MOF derivative constitutes a simple and rapid method for determining LEV in medicine and the food industry.

Original languageEnglish
Pages (from-to)9941-9950
Number of pages10
JournalJournal of Materials Science: Materials in Electronics
Volume33
Issue number13
DOIs
StatePublished - May 2022
Externally publishedYes

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

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