Neethipathi, D. K., Beniwal, A. , Bass, A. , Scott, M. and Dahiya, R. (2023) MoS2 modified screen printed carbon electrode based flexible electrochemical sensor for detection of copper ions in water. IEEE Sensors Journal, 23(8), pp. 8146-8153. (doi: 10.1109/JSEN.2023.3257188)
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Abstract
Heavy metal ions such as Cu 2+ are harmful to the environment and our health. Such ions are typically measured using glassy carbon electrode (GCE) based electrochemical sensors developed on rigid substrates. However, several emerging applications require such sensors on flexible, and even disposable, substrates. Herein, we present a MoS 2 -modified screen-printed carbon electrode (SPCE) based flexible electrochemical sensor for the detection of copper ions in the water. The sensor exhibits excellent response with a limit of detection (LOD) of 5.43 μM for Cu ions in the range of 5 μM to 5 mM. The developed sensor is compared with MoS 2 -modified conventional glassy carbon electrode using electrochemical impedance spectroscopy (EIS). The comparative studies show better linearity (R 2 value ~ 0.99) for SPCE-based sensor and underlines how easily they can detect Cu ions. The interference study, i.e., detection of copper ions in presence of other heavy metal ion-based analytes, also show the excellent response of SPCE based flexible electrochemical sensor – thus demonstrating their practical application is the detection of Cu in water.
| Item Type: | Articles |
|---|---|
| Additional Information: | This work was supported by European Commission through the Innovative Training Network AQUASENSE (H2020-MSCA-ITN-2018-813680). |
| Status: | Published |
| Refereed: | Yes |
| Glasgow Author(s) Enlighten ID: | Neethipathi, Mr Deepan and Dahiya, Professor Ravinder and Bass, Dr Adrian and Beniwal, Dr Ajay and Scott, Professor Marian |
| Authors: | Neethipathi, D. K., Beniwal, A., Bass, A., Scott, M., and Dahiya, R. |
| College/School: | College of Science and Engineering > School of Engineering > Electronics and Nanoscale Engineering College of Science and Engineering > School of Geographical and Earth Sciences College of Science and Engineering > School of Mathematics and Statistics > Statistics |
| Journal Name: | IEEE Sensors Journal |
| Publisher: | IEEE |
| ISSN: | 1530-437X |
| ISSN (Online): | 1558-1748 |
| Published Online: | 20 March 2023 |
| Copyright Holders: | Copyright © 2023 IEEE |
| First Published: | First published in IEEE Sensors Journal 23(8): 8146-8153 |
| Publisher Policy: | Reproduced in accordance with the publisher copyright policy |
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