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Novel ratiometric electrochemical sensor for no-wash detection of fluorene-9-bisphenol based on combining CoN nanoarrays with molecularly imprinted polymers

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Abstract

No-wash detection of small molecules in real samples has been attracting attention in the field of sensors including electroanalytical biosensors. Based on the direct electrochemical oxidation of fluorene-9-bisphenol (BHPF) on a CoN nanoarray electrode, we developed a ratiometric molecularly imprinted polymeric electrochemical (MIP-EC) sensor to realize no-wash detection of BHPF in serum and tap water. The CoN nanoarray in situ grown on carbon cloth (CC) served as the working electrode, which could load the electroactive toluidine blue (TB) and be modified by the MIPs. As the MIP concentration on the modified electrode surface was increased, the amount of BHPF exposed on the electrode surface increased and the amount of exposed TB decreased. Thus, the values of ΔITB and ΔIBHPF decreased and increased, respectively, with an increasing amount of BHPF. Therefore, a ratiometric strategy was established by using the value of ΔITBIBHPF as the instruction response to realize detection of BHPF with high sensitivity and reliability. The developed ratiometric MIP-EC sensor showed strong anti-interference ability, good detection reproducibility and stability towards no-wash detection of BHPF as shown from tests with real samples. This work can further provide theoretical and practical guidance for the detection of other familiar small molecules.

Graphical abstract: Novel ratiometric electrochemical sensor for no-wash detection of fluorene-9-bisphenol based on combining CoN nanoarrays with molecularly imprinted polymers

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Supplementary files

Article information


Submitted
16 Feb 2020
Accepted
13 Mar 2020
First published
13 Mar 2020

Analyst, 2020, Advance Article
Article type
Paper

Novel ratiometric electrochemical sensor for no-wash detection of fluorene-9-bisphenol based on combining CoN nanoarrays with molecularly imprinted polymers

Z. Liu, Y. Zhang, B. Li, X. Ren, H. Ma and Q. Wei, Analyst, 2020, Advance Article , DOI: 10.1039/D0AN00345J

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