Issue 47, 2018

A new electrochemiluminescence biosensor for the detection of glucose based on polypyrrole/polyluminol/Ni(OH)2–C3N4/glucose oxidase-modified graphite electrode

Abstract

A new electrochemiluminescence (ECL) glucose biosensor based on polypyrrole/polyluminol/C3N4–Ni(OH)2/glucose oxidase (Ppy/Plu/C3N4–Ni(OH)2/GOx) was fabricated by the electropolymerization of pyrrole and luminol in acidic medium for glucose detection. Nanoparticles with an average diameter of about 43–48 nm were decorated on the surface of a layer by layer polymer. The glucose oxidase enzyme could be fixed firmly in the polymer film and C3N4-functionalized Ni(OH)2 nanosheets to form a nanohybrid and provide excellent electrocatalytic activity toward the oxidation of glucose, which liberated hydrogen peroxide (H2O2) in the enzymatic reaction. H2O2 then reacted with the luminol radicals and enhanced the luminol ECL, thus providing sensitive determination of glucose. After applying the optimized effective factors, a linear region of ECL intensity from 0.5 μmol L−1 to 500 μmol L−1 (R2 = 0.982) with a detection limit (S/N = 3) of 0.04 μmol L−1 was obtained for the glucose detection. This biosensor was also evaluated by determining its capability in detecting the glucose concentration in saliva and human blood serum. The results showed that the as-fabricated ECL biosensor presented good characteristics, including high sensitivity and suitable reproducibility for glucose determination, with potential applicability in practical analysis.

Graphical abstract: A new electrochemiluminescence biosensor for the detection of glucose based on polypyrrole/polyluminol/Ni(OH)2–C3N4/glucose oxidase-modified graphite electrode

Supplementary files

Article information

Article type
Paper
Submitted
21 авг 2018
Accepted
01 ноя 2018
First published
06 ноя 2018

Anal. Methods, 2018,10, 5723-5730

A new electrochemiluminescence biosensor for the detection of glucose based on polypyrrole/polyluminol/Ni(OH)2–C3N4/glucose oxidase-modified graphite electrode

M. Hamtak, M. Hosseini, L. Fotouhi and M. Aghazadeh, Anal. Methods, 2018, 10, 5723 DOI: 10.1039/C8AY01849A

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