Issue 52, 2020, Issue in Progress

A dual-mode resonance Rayleigh scattering and colorimetric alkaline phosphatase assay based on in situ ascorbic acid-induced signal generation from manganese dioxide nanosheets

Abstract

Multimode sensing has attracted extensive attention because they provide more than one transduction channel, thus improving accuracy and sensitivity. Due to the structural diversity, MnO2 nanosheets and nanoneedles were successively obtained via one-step redox reaction and different self-assembly methods. MnO2 nanosheets possess outstanding optical properties including extremely strong resonance Rayleigh scattering (RRS) and absorbance signal, and were selected as a dual-mode sensing material. Inspired by the selectivity of alkaline phosphatase (ALP) towards dephosphorylate ascorbic acid 2-phosphate (AAP) to generate ascorbic acid (AA), which has the ability to decompose MnO2 nanosheets along with optical signals and colour change, a dual-mode optical ALP sensing platform has been designed. Therefore, MnO2 nanosheets can serve as colorimetric probes by directly visualizing the colour variation with bare eyes. Moreover, the detection limit obtained by the RRS sensing mode can be as low as 0.17 mU L−1, which is far superior to that obtained by previously reported methods. The strategy not only has good feasibility and sensitivity, but also shows good prospects for a series of ALP-extended sensing applications.

Graphical abstract: A dual-mode resonance Rayleigh scattering and colorimetric alkaline phosphatase assay based on in situ ascorbic acid-induced signal generation from manganese dioxide nanosheets

Supplementary files

Article information

Article type
Paper
Submitted
01 Jul 2020
Accepted
07 Aug 2020
First published
26 Aug 2020
This article is Open Access
Creative Commons BY-NC license

RSC Adv., 2020,10, 31527-31534

A dual-mode resonance Rayleigh scattering and colorimetric alkaline phosphatase assay based on in situ ascorbic acid-induced signal generation from manganese dioxide nanosheets

S. Liu, X. Song, J. Li, J. Zhou, W. Na and D. Deng, RSC Adv., 2020, 10, 31527 DOI: 10.1039/D0RA05741J

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