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Solution growth of 3D MnO 2 mesh comprising 1D nanofibres as a novel sensor for selective and sensitive detection of biomolecules.
- Source :
-
Biosensors & bioelectronics [Biosens Bioelectron] 2018 Oct 15; Vol. 117, pp. 852-859. Date of Electronic Publication: 2018 Jun 28. - Publication Year :
- 2018
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Abstract
- This work is the first report describing the solution grown 3D manganese oxide nanofibrous (MnO <subscript>2</subscript> NFs) mesh and its potential for the simultaneous detection of biomolecules such as ascorbic acid and uric acid. The mesh is synthesized by a facile, one-pot, and cost-effective hydrothermal approach without using any template or structure directing compound. The morphology consists of randomly placed nanofibres possessing a diameter in the range of 10-25 nm, and length of several micron; constituting a highly porous and flexible material. The electrochemical potential was examined by recording cyclic voltammetry signals towards ascorbic acid and uric acid. The special mesh morphology offers a large surface area to promote enhanced electrochemical activity, and also provided a macroporous network that supported efficient mass transport. Additionally, the strong electronic cloud and roughness of MnO <subscript>2</subscript> NFs mesh facilitated the fast oxidation of species at very low potential. The lower detection limit was found to be 1.33 µM (S/N = 3) and 1.03 µM (S/N = 3) for ascorbic acid and uric acid, respectively. The MnO <subscript>2</subscript> NFs mesh modified electrodes can robustly differentiate both of them by giving well separate signals (Δ = 500 mV) indicating capability of the material towards selective detection. The sensor has been successfully applied to human blood and urine samples and the recoveries were found statistically significant. These results demonstrate the practical feasibility of 3D mesh to develop sensors for the accurate diagnosis of clinically important molecules.<br /> (Copyright © 2018 Elsevier B.V. All rights reserved.)
Details
- Language :
- English
- ISSN :
- 1873-4235
- Volume :
- 117
- Database :
- MEDLINE
- Journal :
- Biosensors & bioelectronics
- Publication Type :
- Academic Journal
- Accession number :
- 30096740
- Full Text :
- https://doi.org/10.1016/j.bios.2018.06.061