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A new enzyme-free biosensor based on nitrogen-doped graphene with high sensing performance for electrochemical detection of glucose at biological pH value

Title
A new enzyme-free biosensor based on nitrogen-doped graphene with high sensing performance for electrochemical detection of glucose at biological pH value
Author(s)
Rahsepar, MansourForoughi, FaranakKim, Hasuck
Issued Date
2019-03
Citation
Sensors and Actuators B: Chemical, v.282, pp.322 - 330
Type
Article
Author Keywords
DiabetesSugar monitoringEnzymatic-free sensorN-doped grapheneBlood serum
Keywords
MULTIWALLED CARBON NANOTUBEIMPREGNATION METHODCERIUM OXIDEGOLDNANOPARTICLESCOCATALYSTELECTRODESCATALYSTCARBIDEFACILE
ISSN
0925-4005
Abstract
A new enzyme-free glucose biosensor with high sensing performance was developed based on N-doped graphene for glucose detection at biological pH value. The impact of various N functionalities on glucose sensing performance was investigated. In this regard, three N-doped graphene specimens with various amounts of pyridinic, pyrrolic and quaternary nitrogen functionalities were synthesized and thoroughly characterized for enzyme-free glucose detection. Accordingly, the microwave-treated N-doped sample with large pyridinic nitrogen content exhibited the best glucose sensing performance in terms of a proper limit of detection of 0.13 μM and a high sensitivity of 774.23 μA mM−1 cm−2 in a wide linear range of glucose concentration from 0.13 μM to 14 mM at pH 13. Also, it provided a superior sensitivity of 122.336 μA mM−1 cm−2, an appropriate detection limit of 14.52 μM and a fast linear response within the concentration range of 14.52 μM to 10 mM at biological pH (7.4) value. In addition, no interference was observed with addition of dopamine, ascorbic acid, uric acid, maltose, sucrose and fructose. The results of XPS analysis indicate that the pyridinic N dopants activate the electrocatalytic sites of graphene particles for glucose oxidation reaction. © 2018 Elsevier B.V.
URI
http://hdl.handle.net/20.500.11750/9488
DOI
10.1016/j.snb.2018.11.078
Publisher
Elsevier BV
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