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Biological recognition element anchored 2D graphene materials for the electrochemical detection of hazardous pollutants

Authors
Venkatesan, ManjuVusa, Chiranjeevi Srinivasa RaoKoyappayil, AneeshChavan, Sachin GanpatLee, Min-Ho
Issue Date
Aug-2024
Publisher
Elsevier Ltd
Keywords
2D materials; Bio-recognition; Electrochemical; Graphene; Graphene oxide; Hazardous pollutants; Reduced graphene oxide
Citation
Electrochimica Acta, v.494
Journal Title
Electrochimica Acta
Volume
494
URI
https://scholarworks.bwise.kr/cau/handle/2019.sw.cau/74208
DOI
10.1016/j.electacta.2024.144413
ISSN
0013-4686
1873-3859
Abstract
The detection of hazardous pollutants in environmental and industrial settings is of critical importance for safeguarding human health and the ecosystem. Recent years witnessed significant progress and development in novel sensing platforms. The combination of biological recognition elements with two-dimensional (2D) materials enhanced the selectivity and sensitivity of pollutant detection. This review focuses on the integration of biological recognition elements, such as antibodies, nucleic acids, enzymes, aptamers, and proteins with 2D graphene for electrochemical detection of hazardous pollutants. The unique properties of graphene include high electrocatalytic activity, high surface area, and excellent conductivity, combined with the specificity and affinity of biological recognition elements, enabling selective and sensitive detection of hazardous pollutants. The synergistic coupling between 2D graphene and biological recognition elements offers several advantages, including improved sensor performance, rapid response, and potential for multi-analyte detection. Furthermore, the immobilization strategies, surface modifications, and fabrication techniques employed to anchor biological recognition elements onto graphene are discussed. The application of these bio-functionalized 2D material-based sensors for the detection of various hazardous pollutants, such as heavy metals, organic compounds, and environmental toxins, is highlighted. Moreover, the challenges and future perspectives in this field are addressed, including sensor stability, scalability, and the integration of advanced technologies, such as nanotechnology and artificial intelligence, for real-time monitoring and data analysis. © 2024 Elsevier Ltd
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