Journal article
Selective and sensitive visible-light-prompt photoelectrochemical sensor of Cu2+ based on CdS nanorods modified with Au and graphene quantum dots
Journal of Hazardous Materials, Vol.391, Art. 122248
2020
Abstract
Nowadays, increasing the risk for copper leaching into the drinking water in homes, hotels and schools has become unresolved issues all around the countries such as Canada, the United States, and Malaysia. The leaching of copper in tap water is due to a combination of acidic water, damaged pipes, and corroded plumbing fixtures. To remedy this global problem, a triple interconnected structure of CdS/Au/GQDs was designed as a photo-to-electron conversion medium for a real time and selective visible-light-prompt photoelectrochemical (PEC) sensor for Cu2+ ions in real water samples. The synergistic interaction of the CdS/Au/GQDs enabled the smooth transportation of charge carriers to the charge collector and provided a channel to inhibit the charge recombination reaction. Thus, a detection limit of 2.27 nM was obtained, which is 10,000 fold lower than that of WHO’s Guidelines for Drinking-water Quality (∼30 μM). The photocurrent reduction was negligible after 30 days of storage under ambient conditions, suggesting the high stability of photoelectrode. Moreover, the real-time monitoring of Cu2+ ions in real samples was performed with satisfactory results, confirming the capability of the investigated photoelectrode as the most practical detector for trace amounts of Cu2+ ions.
Details
- Title
- Selective and sensitive visible-light-prompt photoelectrochemical sensor of Cu2+ based on CdS nanorods modified with Au and graphene quantum dots
- Authors/Creators
- I. Ibrahim (Author/Creator) - Universiti Putra MalaysiaH.N. Lim (Author/Creator) - Universiti Putra MalaysiaN.M. Huang (Author/Creator) - Xiamen University MalaysiaZ-T Jiang (Author/Creator) - Murdoch UniversityM. Altarawneh (Author/Creator) - Murdoch University
- Publication Details
- Journal of Hazardous Materials, Vol.391, Art. 122248
- Publisher
- Elsevier BV
- Identifiers
- 991005540688207891
- Murdoch Affiliation
- School of Engineering and Information Technology
- Language
- English
- Resource Type
- Journal article
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