Issue 4, 2017

An electrochemical sensor for highly sensitive detection of copper ions based on a new molecular probe Pi-A decorated on graphene

Abstract

In this paper, a new electrochemical sensor based on a new fluorescent probe N-(2-(1-(p-tolyl)-1H-phenanthro[9,10-d]imidazol-2-yl)phenyl)picolinamide (Pi-A) decorated reduced graphene oxide (RGO) nanocomposite modified glassy carbon electrode (GCE) was developed for highly selective detection of copper ions using the electrochemical method. The fluorescent probe Pi-A was immobilized on the reduced graphene oxide surface (Pi-A/RGO) via π–π stacking interactions and the Pi-A/RGO was able to selectively capture copper ions with high sensitivity. Under the optimal conditions, the stripping peak current increased with the concentration of copper ions, and the linear range was 5–300 μg L−1 with a detection limit (S/N = 3) of 0.67 μg L−1. Most importantly, the sensor based on the Pi-A/RGO modified electrode shows good selectivity owing to the presence of Pi-A and it has been successfully applied in the detection of copper ions in tap water, river water, and mountain spring samples. The present work provides a methodology for the construction of electrochemical sensors for the specific detection of Cu2+ combining the specific recognition properties of molecular probes and the good conductivity and large surface area of RGO. Moreover, the combination of molecular probes with RGO will expand the application of fluorescent probes in biological and electrochemical sensing areas.

Graphical abstract: An electrochemical sensor for highly sensitive detection of copper ions based on a new molecular probe Pi-A decorated on graphene

Supplementary files

Article information

Article type
Paper
Submitted
03 Nov 2016
Accepted
07 Dec 2016
First published
08 Dec 2016

Anal. Methods, 2017,9, 618-624

An electrochemical sensor for highly sensitive detection of copper ions based on a new molecular probe Pi-A decorated on graphene

L. Yang, N. Huang, L. Huang, M. Liu, H. Li, Y. Zhang and S. Yao, Anal. Methods, 2017, 9, 618 DOI: 10.1039/C6AY03006H

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