Au@Ag双端纳米铅笔结合数据增强方法用于精神药物的定量检测

IF 3.7 1区 化学 Q1 CHEMISTRY, ANALYTICAL
Lin Bao , Guoqiang Fang , Xinying Ji , Lizhe Wang , Kunpeng Zhou , Siqiangaowa Han , Wuliji Hasi
{"title":"Au@Ag双端纳米铅笔结合数据增强方法用于精神药物的定量检测","authors":"Lin Bao ,&nbsp;Guoqiang Fang ,&nbsp;Xinying Ji ,&nbsp;Lizhe Wang ,&nbsp;Kunpeng Zhou ,&nbsp;Siqiangaowa Han ,&nbsp;Wuliji Hasi","doi":"10.1016/j.snb.2025.138168","DOIUrl":null,"url":null,"abstract":"<div><div>The development of efficient and accurate methods for the detection of psychotropic drugs is essential for the prevention of drug abuse. In this study, we designed and prepared Au@Ag double-ended nano-pencils (DENPs) combined with data enhancement algorithms for quantitative detection of psychotropic drugs. Au@Ag DENPs was prepared by overgrowing Ag shells on the surface of Au bipyramids, which not only have two tip corners (the lightning rod effect), but also generates strong hotspots region at the gap of the neighboring nanoparticles (plasma resonance effect). The Au@Ag DENPs outperform the Au bipyramids in both theoretical simulations and experimental SERS performance, with an experimental enhancement factor as high as 11.4. This SERS substrate was applied to the detection of promethazine hydrochloride with a detection limit as low as 0.1 ppb. In order to overcome the limitations of machine learning algorithms to analyze a small amount of SERS spectral data, multiple data enhancement algorithms were used to expand the SERS spectra. It was shown that the generative adversarial networks (GAN) data enhancement algorithm combined with the principal component analysis-partial least squares (PCA-PLS) algorithm realized the accurate detection of promethazine hydrochloride, with the coefficient of determination between the predicted concentration and the actual concentration as high as 0.978, and the root-mean-square error as low as 47.56. Therefore, Au@Ag DENPs substrate combined with the data enhancement algorithm is promising to be applied in the rapid on-site detection of psychotropic drugs.</div></div>","PeriodicalId":425,"journal":{"name":"Sensors and Actuators B: Chemical","volume":"442 ","pages":"Article 138168"},"PeriodicalIF":3.7000,"publicationDate":"2025-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Au@Ag double-ended nano-pencils combined with data-enhanced methods for quantitative detection of psychotropic drugs\",\"authors\":\"Lin Bao ,&nbsp;Guoqiang Fang ,&nbsp;Xinying Ji ,&nbsp;Lizhe Wang ,&nbsp;Kunpeng Zhou ,&nbsp;Siqiangaowa Han ,&nbsp;Wuliji Hasi\",\"doi\":\"10.1016/j.snb.2025.138168\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>The development of efficient and accurate methods for the detection of psychotropic drugs is essential for the prevention of drug abuse. In this study, we designed and prepared Au@Ag double-ended nano-pencils (DENPs) combined with data enhancement algorithms for quantitative detection of psychotropic drugs. Au@Ag DENPs was prepared by overgrowing Ag shells on the surface of Au bipyramids, which not only have two tip corners (the lightning rod effect), but also generates strong hotspots region at the gap of the neighboring nanoparticles (plasma resonance effect). The Au@Ag DENPs outperform the Au bipyramids in both theoretical simulations and experimental SERS performance, with an experimental enhancement factor as high as 11.4. This SERS substrate was applied to the detection of promethazine hydrochloride with a detection limit as low as 0.1 ppb. In order to overcome the limitations of machine learning algorithms to analyze a small amount of SERS spectral data, multiple data enhancement algorithms were used to expand the SERS spectra. It was shown that the generative adversarial networks (GAN) data enhancement algorithm combined with the principal component analysis-partial least squares (PCA-PLS) algorithm realized the accurate detection of promethazine hydrochloride, with the coefficient of determination between the predicted concentration and the actual concentration as high as 0.978, and the root-mean-square error as low as 47.56. Therefore, Au@Ag DENPs substrate combined with the data enhancement algorithm is promising to be applied in the rapid on-site detection of psychotropic drugs.</div></div>\",\"PeriodicalId\":425,\"journal\":{\"name\":\"Sensors and Actuators B: Chemical\",\"volume\":\"442 \",\"pages\":\"Article 138168\"},\"PeriodicalIF\":3.7000,\"publicationDate\":\"2025-06-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Sensors and Actuators B: Chemical\",\"FirstCategoryId\":\"92\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S092540052500944X\",\"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":"Sensors and Actuators B: Chemical","FirstCategoryId":"92","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S092540052500944X","RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CHEMISTRY, ANALYTICAL","Score":null,"Total":0}
引用次数: 0

摘要

发展有效和准确的精神药物检测方法对于预防药物滥用至关重要。在这项研究中,我们设计并制备了Au@Ag双端纳米铅笔(denp),并结合数据增强算法用于精神药物的定量检测。Au@Ag DENPs是通过在Au双锥体表面过度生长Ag壳而制备的,它不仅具有两个尖端角(避雷针效应),而且在相邻纳米颗粒的间隙处产生了强热点区域(等离子体共振效应)。Au@Ag denp在理论模拟和实验SERS性能上都优于Au双金字塔,实验增强因子高达11.4。该SERS底物用于盐酸异丙嗪的检测,检出限低至0.1 ppb。为了克服机器学习算法分析少量SERS光谱数据的局限性,采用多种数据增强算法对SERS光谱进行扩展。结果表明,生成对抗网络(GAN)数据增强算法结合主成分分析-偏最小二乘(PCA-PLS)算法实现了盐酸异丙嗪的准确检测,预测浓度与实际浓度的决定系数高达0.978,均方根误差低至47.56。因此,Au@Ag DENPs底物结合数据增强算法在精神药物的快速现场检测中具有广阔的应用前景。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Au@Ag double-ended nano-pencils combined with data-enhanced methods for quantitative detection of psychotropic drugs

Au@Ag double-ended nano-pencils combined with data-enhanced methods for quantitative detection of psychotropic drugs
The development of efficient and accurate methods for the detection of psychotropic drugs is essential for the prevention of drug abuse. In this study, we designed and prepared Au@Ag double-ended nano-pencils (DENPs) combined with data enhancement algorithms for quantitative detection of psychotropic drugs. Au@Ag DENPs was prepared by overgrowing Ag shells on the surface of Au bipyramids, which not only have two tip corners (the lightning rod effect), but also generates strong hotspots region at the gap of the neighboring nanoparticles (plasma resonance effect). The Au@Ag DENPs outperform the Au bipyramids in both theoretical simulations and experimental SERS performance, with an experimental enhancement factor as high as 11.4. This SERS substrate was applied to the detection of promethazine hydrochloride with a detection limit as low as 0.1 ppb. In order to overcome the limitations of machine learning algorithms to analyze a small amount of SERS spectral data, multiple data enhancement algorithms were used to expand the SERS spectra. It was shown that the generative adversarial networks (GAN) data enhancement algorithm combined with the principal component analysis-partial least squares (PCA-PLS) algorithm realized the accurate detection of promethazine hydrochloride, with the coefficient of determination between the predicted concentration and the actual concentration as high as 0.978, and the root-mean-square error as low as 47.56. Therefore, Au@Ag DENPs substrate combined with the data enhancement algorithm is promising to be applied in the rapid on-site detection of psychotropic drugs.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Sensors and Actuators B: Chemical
Sensors and Actuators B: Chemical 工程技术-电化学
CiteScore
14.60
自引率
11.90%
发文量
1776
审稿时长
3.2 months
期刊介绍: Sensors & Actuators, B: Chemical is an international journal focused on the research and development of chemical transducers. It covers chemical sensors and biosensors, chemical actuators, and analytical microsystems. The journal is interdisciplinary, aiming to publish original works showcasing substantial advancements beyond the current state of the art in these fields, with practical applicability to solving meaningful analytical problems. Review articles are accepted by invitation from an Editor of the journal.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信