Institutional Repository of Key Laboratory of Coastal Zone Environmental Processes, Yantai Institute of Coastal Zone Research, Chinese Academy of Sciences (KLCEP)
Ultralow-background SERS substrates for reliable identification of organic pollutants and degradation intermediates | |
Zhang, Longfei1,2; Zhao, Rongfang2; Wu, Yanzhou2; Zhang, Zhiyang2,6,7; Chen, Yan2,4; Liu, Meichun2,4; Zhou, Na2; Wang, Yunqing2; Fu, Xiuli1; Zhuang, Xuming1; Wang, Jianping3; Chen, Lingxin2,5,6,7 | |
发表期刊 | JOURNAL OF HAZARDOUS MATERIALS |
ISSN | 0304-3894 |
2023-10-15 | |
卷号 | 460页码:9 |
关键词 | Surface-enhanced Raman scattering Surface plasmon resonance Silver nanoparticles Organic pollutants Degradation intermediates |
DOI | 10.1016/j.jhazmat.2023.132508 |
通讯作者 | Zhang, Zhiyang([email protected]) ; Chen, Lingxin([email protected]) |
英文摘要 | Chemical methods for preparing SERS substrates have the advantages of low cost and high productivity, but the strong background signals from the substrate greatly limit their applications in characterization and identification of organic compounds. Herein, we developed a one-step synthesis method to prepare silver nanoparticle substrates with ultralow SERS background using anionic ligands as stabilizing agents and applied the SERS substrate for the reliable and reproducible identification of typical organic pollutants and corresponding degradation intermediates. The synthesis method shows excellent universality to different reducing agents cooperating with different anionic ligands (Cl-, Br-, I-, SCN-). As model applications, the machine learning algorithm can realize the precise prediction of six organophosphorus pesticides and eight sulfonamide antibiotics with 100% accuracy based on SERS training data. More importantly, the ultralow-background SERS substrate enables one to detect and identify the time-dependent degradation intermediates of organophosphorus pesticides by combining them with density functional theory (DFT) calculations. All the results indicate that the ultralowbackground SERS substrate will greatly push the development of SERS characterization applications. |
资助机构 | National Natural Science Foundation of China ; Key Deployment Project of Centre for Ocean Mega-Research of Science, Chinese Academy of Sciences ; Taishan Scholars Program ; Shandong Provincial Natural Science Foundation ; Special Fund for the Scholar Program of Yantai |
收录类别 | SCI |
语种 | 英语 |
关键词[WOS] | ENHANCED RAMAN-SCATTERING ; LABEL-FREE DETECTION ; ORGANOPHOSPHORUS PESTICIDES ; PLASMON RESONANCES ; GOLD NANOPARTICLES ; NANOSTRUCTURES ; PRODUCTS ; REMOVAL ; RESIDUE |
研究领域[WOS] | Engineering ; Environmental Sciences & Ecology |
WOS记录号 | WOS:001078271300001 |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://ir.yic.ac.cn/handle/133337/32867 |
专题 | 中国科学院海岸带环境过程与生态修复重点实验室 中国科学院海岸带环境过程与生态修复重点实验室_海岸带环境工程技术研究与发展中心 |
通讯作者 | Zhang, Zhiyang; Chen, Lingxin |
作者单位 | 1.Yantai Univ, Sch Chem & Chem Engn, Yantai 264005, Peoples R China 2.Chinese Acad Sci, Yantai Inst Coastal Zone Res, Res Ctr Coastal Environm Engn & Technol, CAS Key Lab Coastal Environm Proc & Ecol Remediat, Yantai 264003, Peoples R China 3.Chinese Acad Sci, Beijing Natl Lab Mol Sci, Mol React Dynam Lab, CAS Res Educ Ctr Excellence Mol Sci,Inst Chem, Beijing 100190, Peoples R China 4.Univ Chinese Acad Sci, Beijing 100049, Peoples R China 5.Binzhou Med Univ, Sch Pharm, Yantai 264003, Peoples R China 6.Chinese Acad Sci, Ctr Ocean Mega Sci, Qingdao 266071, Peoples R China 7.Chinese Acad Sci, Ctr Ocean Mega Sci, Qingdao 264003, Peoples R China |
推荐引用方式 GB/T 7714 | Zhang, Longfei,Zhao, Rongfang,Wu, Yanzhou,et al. Ultralow-background SERS substrates for reliable identification of organic pollutants and degradation intermediates[J]. JOURNAL OF HAZARDOUS MATERIALS,2023,460:9. |
APA | Zhang, Longfei.,Zhao, Rongfang.,Wu, Yanzhou.,Zhang, Zhiyang.,Chen, Yan.,...&Chen, Lingxin.(2023).Ultralow-background SERS substrates for reliable identification of organic pollutants and degradation intermediates.JOURNAL OF HAZARDOUS MATERIALS,460,9. |
MLA | Zhang, Longfei,et al."Ultralow-background SERS substrates for reliable identification of organic pollutants and degradation intermediates".JOURNAL OF HAZARDOUS MATERIALS 460(2023):9. |
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