Issue 43, 2017, Issue in Progress

Three-dimensional N-doped carbon nanotube@carbon foam hybrid: an effective carrier of enzymes for glucose biosensors

Abstract

Development of efficient, reliable, and cost-effective biosensors for accurate and convenient detection of glucose is highly desirable in the food industry, biotechnology, and clinical diagnosis. Carbon nanotube (CNT)-based enzyme biosensors have received considerable attention due to their excellent performance. However, the performance of these sensors is limited by the drawbacks of CNTs such as low electron transfer rate and catalytic area, and poor conductivity. Herein, three-dimensional (3D) nitrogen-doped CNTs (N-CNTs) supported by a carbon foam (N-CNT@CF) hybrid is fabricated as the carrier matrix to load glucose oxidase (GOD) for constructing high-performance glucose biosensors. A one-step chemical vapor deposition method is employed for the preparation of a N-CNT@CF hybrid, where N-CNTs are densely grown on the skeleton of carbon foam using iron as a catalyst. FT-IR spectroscopy shows that the N-CNT@CF is an effective carrier of GOD without enzyme denaturation. Combined with the extraordinary properties of 3D N-CNT@CF including large active surface area, high conductivity and fast mass transport dynamics, the GOD/N-CNT@CF biosensor achieves a large linear range (0.05–15.55 mM, R = 0.996) and a low detection limit (5.0 μM, S/N = 3) for the detection of glucose. Furthermore, the glucose biosensor exhibited high selectivity, good repeatability and stability.

Graphical abstract: Three-dimensional N-doped carbon nanotube@carbon foam hybrid: an effective carrier of enzymes for glucose biosensors

Article information

Article type
Paper
Submitted
02 Mar 2017
Accepted
11 May 2017
First published
17 May 2017
This article is Open Access
Creative Commons BY license

RSC Adv., 2017,7, 26574-26582

Three-dimensional N-doped carbon nanotube@carbon foam hybrid: an effective carrier of enzymes for glucose biosensors

P. Fan, L. Liu, Q. Guo, J. Wang, J. Yang, X. Guan, S. Chen and H. Hou, RSC Adv., 2017, 7, 26574 DOI: 10.1039/C7RA02592K

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