Jia-Yi Luo, Zhao-Jing Huang, Ming Zhao, Shunxing Li*, Fengying Zheng, Xuguang Huang, Fengjiao Liu, Luxiu Lin, Zheng Bin Huang and Haijiao Xie,
{"title":"用于饮用水中多种金属风险评估的一对九单光谱智能探针。","authors":"Jia-Yi Luo, Zhao-Jing Huang, Ming Zhao, Shunxing Li*, Fengying Zheng, Xuguang Huang, Fengjiao Liu, Luxiu Lin, Zheng Bin Huang and Haijiao Xie, ","doi":"10.1021/acs.analchem.4c02181","DOIUrl":null,"url":null,"abstract":"<p >26% of the world’s population lacks access to clean drinking water; clean water and sanitation are major global challenges highlighted by the UN Sustainable Development Goals, indicating water security in public water systems is at stake today. Water monitoring using precise instruments by skilled operators is one of the most promising solutions. Despite decades of research, the professionalism–convenience trade-off when monitoring ubiquitous metal ions remains the major challenge for public water safety. Thus, to overcome these disadvantages, an easy-to-use and highly sensitive visual method is desirable. Herein, an innovative strategy for one-to-nine metal detection is proposed, in which a novel thiourea spectroscopic probe with high 9-metal affinity is synthesized, acting as “one”, and is detected based on the 9 metal–thiourea complexes within portable spectrometers in the public water field; this is accomplished by nonspecialized personnel as is also required. During the processing of multimetal analysis, issues arise due to signal overlap and reproducibility problems, leading to constrained sensitivity. In this innovative endeavor, machine learning (ML) algorithms were employed to extract key features from the composite spectral signature, addressing multipeak overlap, and completing the detection within 30–300 s, thus achieving a detection limit of 0.01 mg/L and meeting established conventional water quality standards. This method provides a convenient approach for public drinking water safety testing.</p>","PeriodicalId":27,"journal":{"name":"Analytical Chemistry","volume":null,"pages":null},"PeriodicalIF":6.7000,"publicationDate":"2024-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"One-to-Nine Single Spectroscopic Intelligent Probe for Risk Assessment of Multiple Metals in Drinking Water\",\"authors\":\"Jia-Yi Luo, Zhao-Jing Huang, Ming Zhao, Shunxing Li*, Fengying Zheng, Xuguang Huang, Fengjiao Liu, Luxiu Lin, Zheng Bin Huang and Haijiao Xie, \",\"doi\":\"10.1021/acs.analchem.4c02181\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p >26% of the world’s population lacks access to clean drinking water; clean water and sanitation are major global challenges highlighted by the UN Sustainable Development Goals, indicating water security in public water systems is at stake today. Water monitoring using precise instruments by skilled operators is one of the most promising solutions. Despite decades of research, the professionalism–convenience trade-off when monitoring ubiquitous metal ions remains the major challenge for public water safety. Thus, to overcome these disadvantages, an easy-to-use and highly sensitive visual method is desirable. Herein, an innovative strategy for one-to-nine metal detection is proposed, in which a novel thiourea spectroscopic probe with high 9-metal affinity is synthesized, acting as “one”, and is detected based on the 9 metal–thiourea complexes within portable spectrometers in the public water field; this is accomplished by nonspecialized personnel as is also required. During the processing of multimetal analysis, issues arise due to signal overlap and reproducibility problems, leading to constrained sensitivity. In this innovative endeavor, machine learning (ML) algorithms were employed to extract key features from the composite spectral signature, addressing multipeak overlap, and completing the detection within 30–300 s, thus achieving a detection limit of 0.01 mg/L and meeting established conventional water quality standards. This method provides a convenient approach for public drinking water safety testing.</p>\",\"PeriodicalId\":27,\"journal\":{\"name\":\"Analytical Chemistry\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":6.7000,\"publicationDate\":\"2024-07-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Analytical Chemistry\",\"FirstCategoryId\":\"92\",\"ListUrlMain\":\"https://pubs.acs.org/doi/10.1021/acs.analchem.4c02181\",\"RegionNum\":1,\"RegionCategory\":\"化学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"CHEMISTRY, ANALYTICAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Analytical Chemistry","FirstCategoryId":"92","ListUrlMain":"https://pubs.acs.org/doi/10.1021/acs.analchem.4c02181","RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CHEMISTRY, ANALYTICAL","Score":null,"Total":0}
One-to-Nine Single Spectroscopic Intelligent Probe for Risk Assessment of Multiple Metals in Drinking Water
26% of the world’s population lacks access to clean drinking water; clean water and sanitation are major global challenges highlighted by the UN Sustainable Development Goals, indicating water security in public water systems is at stake today. Water monitoring using precise instruments by skilled operators is one of the most promising solutions. Despite decades of research, the professionalism–convenience trade-off when monitoring ubiquitous metal ions remains the major challenge for public water safety. Thus, to overcome these disadvantages, an easy-to-use and highly sensitive visual method is desirable. Herein, an innovative strategy for one-to-nine metal detection is proposed, in which a novel thiourea spectroscopic probe with high 9-metal affinity is synthesized, acting as “one”, and is detected based on the 9 metal–thiourea complexes within portable spectrometers in the public water field; this is accomplished by nonspecialized personnel as is also required. During the processing of multimetal analysis, issues arise due to signal overlap and reproducibility problems, leading to constrained sensitivity. In this innovative endeavor, machine learning (ML) algorithms were employed to extract key features from the composite spectral signature, addressing multipeak overlap, and completing the detection within 30–300 s, thus achieving a detection limit of 0.01 mg/L and meeting established conventional water quality standards. This method provides a convenient approach for public drinking water safety testing.
期刊介绍:
Analytical Chemistry, a peer-reviewed research journal, focuses on disseminating new and original knowledge across all branches of analytical chemistry. Fundamental articles may explore general principles of chemical measurement science and need not directly address existing or potential analytical methodology. They can be entirely theoretical or report experimental results. Contributions may cover various phases of analytical operations, including sampling, bioanalysis, electrochemistry, mass spectrometry, microscale and nanoscale systems, environmental analysis, separations, spectroscopy, chemical reactions and selectivity, instrumentation, imaging, surface analysis, and data processing. Papers discussing known analytical methods should present a significant, original application of the method, a notable improvement, or results on an important analyte.