Marios Constantinou, Christoforos Panteli, L. Potamiti, M. Panayiotidis, A. Agapiou, S. Christodoulou, C. Andreou
{"title":"推进基于呼吸的诊断:通过溶液加工金纳米颗粒装饰的二氧化钛纳米线的介电排列实现三维网状 SERS 传感器","authors":"Marios Constantinou, Christoforos Panteli, L. Potamiti, M. Panayiotidis, A. Agapiou, S. Christodoulou, C. Andreou","doi":"10.1002/adsr.202300161","DOIUrl":null,"url":null,"abstract":"Surface enhanced Raman spectroscopy (SERS) is becoming an attractive analytical technique for the next generation of breath diagnostics. However, current SERS substrates present challenges related to fabrication cost, complexity, signal uniformity, and reproducibility. Here, a low‐cost, label‐free SERS sensor based on fully solution‐processed decoration of TiO2 nanowires is demonstrated (NW) with plasmonic Au nanoparticles (NP) followed by the dielectrophoretic self‐assembly into a 3D mesh with high signal to noise ratio. The sensor performance is tested using 4‐aminothiophenol (4‐ATP) as a model analyte in gas phase, at concentrations down to 10 ppbv, and in solution, with limit of detection ≈2.4 pM. Finally, to explore the sensor capability for breath‐based diagnostics, a proof‐of‐concept experiment is performed with exhaled breath condensates (EBCs). The possibility to discriminate EBCs of individuals with upper respiratory tract infection (URTI) from healthy ones is demonstrated. Multiple SERS spectra (n≈50) from each sample are analyzed using orthogonal partial least squares discriminant analysis (OPLS‐DA), which identifies spectral features representative of URTI in up to 80% of the infection‐related spectra. These results demonstrate the applicability and potential of 1D nanomaterials together with state‐of‐the‐art solution‐processed techniques for the development of low‐cost and compact SERS breath‐based diagnostic platforms for clinical point‐of‐care applications.","PeriodicalId":100037,"journal":{"name":"Advanced Sensor Research","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2024-02-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Advancing Breath‐Based Diagnostics: 3D Mesh SERS Sensor Via Dielectrophoretic Alignment of Solution‐Processed Au Nanoparticle‐Decorated TiO2 Nanowires\",\"authors\":\"Marios Constantinou, Christoforos Panteli, L. Potamiti, M. Panayiotidis, A. Agapiou, S. Christodoulou, C. Andreou\",\"doi\":\"10.1002/adsr.202300161\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Surface enhanced Raman spectroscopy (SERS) is becoming an attractive analytical technique for the next generation of breath diagnostics. However, current SERS substrates present challenges related to fabrication cost, complexity, signal uniformity, and reproducibility. Here, a low‐cost, label‐free SERS sensor based on fully solution‐processed decoration of TiO2 nanowires is demonstrated (NW) with plasmonic Au nanoparticles (NP) followed by the dielectrophoretic self‐assembly into a 3D mesh with high signal to noise ratio. The sensor performance is tested using 4‐aminothiophenol (4‐ATP) as a model analyte in gas phase, at concentrations down to 10 ppbv, and in solution, with limit of detection ≈2.4 pM. Finally, to explore the sensor capability for breath‐based diagnostics, a proof‐of‐concept experiment is performed with exhaled breath condensates (EBCs). The possibility to discriminate EBCs of individuals with upper respiratory tract infection (URTI) from healthy ones is demonstrated. Multiple SERS spectra (n≈50) from each sample are analyzed using orthogonal partial least squares discriminant analysis (OPLS‐DA), which identifies spectral features representative of URTI in up to 80% of the infection‐related spectra. These results demonstrate the applicability and potential of 1D nanomaterials together with state‐of‐the‐art solution‐processed techniques for the development of low‐cost and compact SERS breath‐based diagnostic platforms for clinical point‐of‐care applications.\",\"PeriodicalId\":100037,\"journal\":{\"name\":\"Advanced Sensor Research\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-02-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Advanced Sensor Research\",\"FirstCategoryId\":\"0\",\"ListUrlMain\":\"https://doi.org/10.1002/adsr.202300161\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Advanced Sensor Research","FirstCategoryId":"0","ListUrlMain":"https://doi.org/10.1002/adsr.202300161","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Advancing Breath‐Based Diagnostics: 3D Mesh SERS Sensor Via Dielectrophoretic Alignment of Solution‐Processed Au Nanoparticle‐Decorated TiO2 Nanowires
Surface enhanced Raman spectroscopy (SERS) is becoming an attractive analytical technique for the next generation of breath diagnostics. However, current SERS substrates present challenges related to fabrication cost, complexity, signal uniformity, and reproducibility. Here, a low‐cost, label‐free SERS sensor based on fully solution‐processed decoration of TiO2 nanowires is demonstrated (NW) with plasmonic Au nanoparticles (NP) followed by the dielectrophoretic self‐assembly into a 3D mesh with high signal to noise ratio. The sensor performance is tested using 4‐aminothiophenol (4‐ATP) as a model analyte in gas phase, at concentrations down to 10 ppbv, and in solution, with limit of detection ≈2.4 pM. Finally, to explore the sensor capability for breath‐based diagnostics, a proof‐of‐concept experiment is performed with exhaled breath condensates (EBCs). The possibility to discriminate EBCs of individuals with upper respiratory tract infection (URTI) from healthy ones is demonstrated. Multiple SERS spectra (n≈50) from each sample are analyzed using orthogonal partial least squares discriminant analysis (OPLS‐DA), which identifies spectral features representative of URTI in up to 80% of the infection‐related spectra. These results demonstrate the applicability and potential of 1D nanomaterials together with state‐of‐the‐art solution‐processed techniques for the development of low‐cost and compact SERS breath‐based diagnostic platforms for clinical point‐of‐care applications.