Tools
Tools
Minta, Daria, González, Zoraida, Melendi-Espina, Sonia 
ORCID: https://orcid.org/0000-0002-1083-3896 and Gryglewicz, Grażyna
(2022)
Highly efficient and stable PANI/TRGO nanocomposites as active materials for electrochemical detection of dopamine.
Surfaces and Interfaces, 28.
ISSN 2468-0230
Preview |
PDF (Accepted_Manuscript)
- Accepted Version
Available under License Creative Commons Attribution Non-commercial No Derivatives. Download (1MB) | Preview |
Abstract
Thermally reduced graphene oxides (TRGOs), produced at 400 and 700°C, and polyaniline (PANI) were used for one-pot facile hydrothermal synthesis of binary nanocomposites (PANI/TRGO). The morphology and chemical composition of these materials were thoroughly characterized by means of scanning electron microscopy, nitrogen sorption at 77 K, elemental analysis, X-ray photoelectron spectroscopy, X-ray diffraction, and sheet resistance measurements. Cyclic voltammetry, differential pulse voltammetry and electrochemical impedance spectroscopy were used for electrochemical characterization. The scanning electron microscopy (SEM) observation revealed that the morphology of TRGOs has a crucial impact on the distribution of PANI in the composites. A more homogenous distribution of PANI was achieved for PANI/TRGO-700 due to the higher degree of exfoliation of the starting material TRGO-700. The synthesized composites were investigated as modifiers of glassy carbon electrodes (GCEs) for the electrochemical sensing of dopamine. Both, the PANI distribution and an appropriate oxygen content are key for DA sensing. Thus, the better performance of PANI/TRGO-700 as an active material was revealed, achieving a LOD of 430 nM, an excellent sensitivity (6.7 µA µM−1) and stability after 30 days.
| Item Type: | Article |
|---|---|
| Faculty \ School: | Faculty of Science > School of Engineering (former - to 2024) |
| UEA Research Groups: | Faculty of Science > Research Groups > Sustainable Energy Faculty of Science > Research Groups > Materials, Manufacturing & Process Modelling |
| Related URLs: | |
| Depositing User: | LivePure Connector |
| Date Deposited: | 24 Nov 2021 03:15 |
| Last Modified: | 17 Dec 2024 01:34 |
| URI: | https://ueaeprints.uea.ac.uk/id/eprint/82299 |
| DOI: | 10.1016/j.surfin.2021.101606 |
Downloads
Downloads per month over past year
Actions (login required)
 |
View Item |