ENHANCING SENSITIVITY AND SELECTIVITY OF SURFACE RAMAN SCATTERING DETECTION BY CHEMOMETRIC METHOD

カテゴリ: 研究会(論文単位)

論文No: DEI20019,EFM20019

グループ名: 【A】基礎・材料・共通部門 誘電・絶縁材料/【C】電子・情報・システム部門 電子材料合同研究会

発行日: 2020/01/22

タイトル(英語): ENHANCING SENSITIVITY AND SELECTIVITY OF SURFACE RAMAN SCATTERING DETECTION BY CHEMOMETRIC METHOD

著者名: Sricharoen Nontawat(Center of Excellence on Petrochemical and Materials Technology, Chulalongkorn University),Pienpinijtham Prompong(Sensor Research Unit, Faculty of Science, Chulalongkorn University),Ekgasit Sanong(Sensor Research Unit, Faculty of Scienc

著者名(英語): Nontawat Sricharoen(Center of Excellence on Petrochemical and Materials Technology, Chulalongkorn University),Prompong Pienpinijtham(Sensor Research Unit, Faculty of Science, Chulalongkorn University),Sanong Ekgasit(Sensor Research Unit, Faculty of Science, Chulalongkorn University),Kanet Wongravee(Sensor Research Unit, Faculty of Science, Chulalongkorn University)

キーワード: Chemometrics |SERS|Raman Scattering|MCR-ALS|Chemometrics |SERS|Raman Scattering|MCR-ALS

要約(日本語): Surface Enhanced Raman Scattering (SERS) spectroscopy is a rapid and ultrasensitive technique for detecting the vibrational patterns of functional groups of molecules using nanoparticles as substrate. To acquire the analyte signal, the analyte should be immobilized and interacted on the surface of nanoparticles. To differentiate the signal of the analyte, signal patterns of capping agent and analyte must be different, otherwise, SERS signals of both capping agent and analyte will be overlapped and difficult for any further analysis. In the study, Multivariate curve resolution-alternative least square (MCR-ALS) was performed to extract the pure spectrum of the capping agent and the analyte from the overlapped signals. In the case, the efficiency of our developed algorithm was tested with the simulated spectra generated by Gaussian peaks representing the analyte and capping agent signal, respectively. The key step is to eliminate the influences of the capping agent signals by increasing the variance of the capping agent signals. These spectra were simulated using different conditions involving the concentration ratios, noise levels, and resolutions in order to indicate the limitation of the developed method. The pure analyte signals were successfully obtained with the R2 values > 0.99 and the prediction error 1-5%. The developed program has the potential features to monitor and quantify an analyte in the practical SERS detection.

要約(英語): Surface Enhanced Raman Scattering (SERS) spectroscopy is a rapid and ultrasensitive technique for detecting the vibrational patterns of functional groups of molecules using nanoparticles as substrate. To acquire the analyte signal, the analyte should be immobilized and interacted on the surface of nanoparticles. To differentiate the signal of the analyte, signal patterns of capping agent and analyte must be different, otherwise, SERS signals of both capping agent and analyte will be overlapped and difficult for any further analysis. In the study, Multivariate curve resolution-alternative least square (MCR-ALS) was performed to extract the pure spectrum of the capping agent and the analyte from the overlapped signals. In the case, the efficiency of our developed algorithm was tested with the simulated spectra generated by Gaussian peaks representing the analyte and capping agent signal, respectively. The key step is to eliminate the influences of the capping agent signals by increasing the variance of the capping agent signals. These spectra were simulated using different conditions involving the concentration ratios, noise levels, and resolutions in order to indicate the limitation of the developed method. The pure analyte signals were successfully obtained with the R2 values > 0.99 and the prediction error 1-5%. The developed program has the potential features to monitor and quantify an analyte in the practical SERS detection.

原稿種別: 英語

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