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Sun Z, Ji X, Lu S, Du J. Shining a light on environmental science: Recent advances in SERS technology for rapid detection of persistent toxic substances. J Environ Sci (China) 2025; 153:251-263. [PMID: 39855797 DOI: 10.1016/j.jes.2024.08.022] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2024] [Revised: 08/06/2024] [Accepted: 08/18/2024] [Indexed: 01/27/2025]
Abstract
Persistent toxic substances (PTS) represent a paramount environmental issue in the 21st century. Understanding the concentrations and forms of PTS in the environment is crucial for accurately assessing their environmental health impacts. This article presents a concise overview of the components of PTS, pertinent environmental regulations, and conventional detection methodologies. Additionally, we offer an in-depth review of the principles, development, and practical applications of surface-enhanced Raman scattering (SERS) in environmental monitoring, emphasizing the advancements in detecting trace amounts of PTS in complex environmental matrices. Recent progress in enhancing SERS sensitivity, improving selectivity, and practical implementations are detailed, showcasing innovative materials and methods. Integrating SERS with advanced algorithms are highlighted as pivotal areas for future research.
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Affiliation(s)
- Zhenli Sun
- MOE Key Laboratory of Resources and Environmental System Optimization, College of Environmental Science and Engineering, North China Electric Power University, Beijing 102206, China
| | - Xunlong Ji
- MOE Key Laboratory of Resources and Environmental System Optimization, College of Environmental Science and Engineering, North China Electric Power University, Beijing 102206, China
| | - Shaoyu Lu
- University of Chinese Academy of Sciences, Beijing 100190, China
| | - Jingjing Du
- State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China; University of Chinese Academy of Sciences, Beijing 100190, China.
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Jini AR, Simiyon GG, Vergheese TM. Selective Identification and Quantification of Microplastics Using Solid Fluorescent Green Carbon Dots (SFGCDs) - A Novel, Naked Eye Sensing Fluoroprobe. J Fluoresc 2025:10.1007/s10895-025-04152-x. [PMID: 40014203 DOI: 10.1007/s10895-025-04152-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2024] [Accepted: 01/22/2025] [Indexed: 02/28/2025]
Abstract
The current work presents a Novel, Carbon Dot fluoroprobe to selectively identify and quantify Microplastics (MPs) released from Surgical facemask and Cosmetic Personal Cleansers. Solid Fluorescent Green Carbon Dots (SFGCDs) are synthesized for the first time from a high carbon source natural resin, obtained from Araucaria araucana (Monkey puzzle tree). The increased carbon content is responsible for the green colour of the CDs. SFGCDs function as a TURN OFF fluoroprobe on detection of MPs through dynamic quenching mechanism, which is confirmed from Stern Volmer Plot with an R2 value of. The minimum LOD being 0.0063 g/l for ≥ 6 μm diameter MPs. The agglomeration of microplastics released from surgical mask and cosmetic cleansers on functions as an insulator on the surface of SFGCDs, forbidding ease of electron- hole transfer between the donor- SFGCDs and acceptor-MPs. The release of MPs from the donor surface results in reappearance of fluorescence obeying FRET mechanism. The detection of MPs/ microfibres released by disposable surgical mask is studied by the degradation of the surgical face mask for a period of 50 days, followed by detection. Turn- OFF in fluorescence of SFGCDs observed in presence of micro fibre Turns On, as remediation of MPs is done by a simple filtration technique. The results demonstrate the potential of the fluoroprobe towards real time detection of MPs and simple remediation of MPs to conserve the ecosystem. The SFGCDs is stable and can be reused for nearly 3 cycles for the detection of MPs. A single PL peak obtained on detection of MPs in presence of monovalent, divalent trivalent ions and biomolecules authenticates the selectivity and stability of SFGCDs to function as an efficient fluoroprobe towards sensing of MPs.
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Affiliation(s)
- Ayun R Jini
- Department of Chemistry, Madras Christian College, Chennai, 600059, Tamil Nadu, India
| | - G Gnanamani Simiyon
- Department of Chemistry, Madras Christian College, Chennai, 600059, Tamil Nadu, India
| | - T Mary Vergheese
- Department of Chemistry, Madras Christian College, Chennai, 600059, Tamil Nadu, India.
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Li Z, Hu Y, Wang L, Liu H, Ren T, Wang C, Li D. Selective and Accurate Detection of Nitrate in Aquaculture Water with Surface-Enhanced Raman Scattering (SERS) Using Gold Nanoparticles Decorated with β-Cyclodextrins. SENSORS (BASEL, SWITZERLAND) 2024; 24:1093. [PMID: 38400251 PMCID: PMC10893249 DOI: 10.3390/s24041093] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/09/2024] [Revised: 01/31/2024] [Accepted: 02/05/2024] [Indexed: 02/25/2024]
Abstract
A surface-enhanced Raman scattering (SERS) method for measuring nitrate nitrogen in aquaculture water was developed using a substrate of β-cyclodextrin-modified gold nanoparticles (SH-β-CD@AuNPs). Addressing the issues of low sensitivity, narrow linear range, and relatively poor selectivity of single metal nanoparticles in the SERS detection of nitrate nitrogen, we combined metal nanoparticles with cyclodextrin supramolecular compounds to prepare a AuNPs substrate enveloped by cyclodextrin, which exhibits ultra-high selectivity and Raman activity. Subsequently, vanadium(III) chloride was used to convert nitrate ions into nitrite ions. The adsorption mechanism between the reaction product benzotriazole (BTAH) of o-phenylenediamine (OPD) and nitrite ions on the SH-β-CD@AuNPs substrate was studied through SERS, achieving the simultaneous detection of nitrate nitrogen and nitrite nitrogen. The experimental results show that BTAH exhibits distinct SERS characteristic peaks at 1168, 1240, 1375, and 1600 cm-1, with the lowest detection limits of 3.33 × 10-2, 5.84 × 10-2, 2.40 × 10-2, and 1.05 × 10-2 μmol/L, respectively, and a linear range of 0.1-30.0 μmol/L. The proposed method provides an effective tool for the selective and accurate online detection of nitrite and nitrate nitrogen in aquaculture water.
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Affiliation(s)
- Zhen Li
- National Innovation Center for Digital Fishery, China Agricultural University, Beijing 100083, China
- School of Integrated Circuit, Tsinghua University, Beijing 100084, China
- Key Laboratory of Smart Farming Technologies for Aquatic Animal and Livestock, Ministry of Agriculture and Rural Affairs, China Agricultural University, Beijing 100083, China
- College of Information and Electrical Engineering, China Agricultural University, Beijing 100083, China
- Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China
| | - Yang Hu
- National Innovation Center for Digital Fishery, China Agricultural University, Beijing 100083, China
- Key Laboratory of Smart Farming Technologies for Aquatic Animal and Livestock, Ministry of Agriculture and Rural Affairs, China Agricultural University, Beijing 100083, China
- College of Information and Electrical Engineering, China Agricultural University, Beijing 100083, China
| | - Liu Wang
- National Innovation Center for Digital Fishery, China Agricultural University, Beijing 100083, China
- Key Laboratory of Smart Farming Technologies for Aquatic Animal and Livestock, Ministry of Agriculture and Rural Affairs, China Agricultural University, Beijing 100083, China
- College of Information and Electrical Engineering, China Agricultural University, Beijing 100083, China
| | - Houfang Liu
- School of Integrated Circuit, Tsinghua University, Beijing 100084, China
- Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China
| | - Tianling Ren
- School of Integrated Circuit, Tsinghua University, Beijing 100084, China
- Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China
| | - Cong Wang
- National Innovation Center for Digital Fishery, China Agricultural University, Beijing 100083, China
- Key Laboratory of Smart Farming Technologies for Aquatic Animal and Livestock, Ministry of Agriculture and Rural Affairs, China Agricultural University, Beijing 100083, China
- College of Information and Electrical Engineering, China Agricultural University, Beijing 100083, China
| | - Daoliang Li
- National Innovation Center for Digital Fishery, China Agricultural University, Beijing 100083, China
- Key Laboratory of Smart Farming Technologies for Aquatic Animal and Livestock, Ministry of Agriculture and Rural Affairs, China Agricultural University, Beijing 100083, China
- College of Information and Electrical Engineering, China Agricultural University, Beijing 100083, China
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