Issue 29, 2019

Non-enzymatic colorimetric sensor strip based on melamine-functionalized gold nanoparticles assembled on polyamide nanofiber membranes for the detection of metronidazole

Abstract

Metronidazole (MTZ) is an antibiotic that is hazardous to the health of humans as well as animals, and which can cause a severe pathological state. Colorimetric strategies to facilitate and accelerate portable detection of MTZ are needed. Here, the surface of gold nanoparticles (GNPs) was functionalized with melamine (MA) to provide a non-enzymatic sensing colorimetric probe. Then, the resulting MA-functionalized GNPs (MA@GNPs) were immobilized on polyamide 6 nanofiber membranes (PA6 NFMs). The constructed NFMs demonstrated a colorimetric response towards MTZ, due to interaction between MA and MTZ, which leads to aggregation of GNPs. The colorimetric strips displayed good sensitivity with a low naked-eye limit of detection (2 nM at S/N = 3), a rapid detection time (2.5 min), a linear response in the 2 to 100 nM MTZ concentration range and high selectivity, which are attributed to the high surface area of NFMs. The comparison between the limit of detection using visual detection and spectrophotometric detection was studied systematically, and showed that the RGB (red, green, blue) color difference (ΔC) enhanced the limit of detection. These colorimetric strips are capable of being used for portable recognition using uncomplicated smartphone cameras to obtain low limits of detection.

Graphical abstract: Non-enzymatic colorimetric sensor strip based on melamine-functionalized gold nanoparticles assembled on polyamide nanofiber membranes for the detection of metronidazole

Supplementary files

Article information

Article type
Paper
Submitted
27 May 2019
Accepted
27 Jun 2019
First published
01 Jul 2019

Anal. Methods, 2019,11, 3706-3713

Non-enzymatic colorimetric sensor strip based on melamine-functionalized gold nanoparticles assembled on polyamide nanofiber membranes for the detection of metronidazole

M. A. Abedalwafa, Y. Li, C. Ni, G. Yang and L. Wang, Anal. Methods, 2019, 11, 3706 DOI: 10.1039/C9AY01114E

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