{"title":"利用二维相关分析提高LIBS中原子跃迁的信噪比","authors":"L. Narlagiri, Venugopal Rao Soma","doi":"10.1364/OSAC.426995","DOIUrl":null,"url":null,"abstract":"In this study, two-dimensional (2D) correlation analysis was utilized for achieving a significant improvement in the signal-to-noise (S/N) ratio of laser-induced breakdown spectroscopy (LIBS) data. Time-resolved LIBS spectra of metallic, bimetallic targets and the normal LIBS spectra of bimetallic targets with varying compositions were used for the detailed analysis. The diagonal of the matrix in the synchronous spectra was used to demonstrate the improvement in the S/N ratio. An improvement in the peak intensities by few orders of magnitude accompanied by suppression in the noise was observed. The correlations between LIBS peaks were also visualized using 2-D plots. Correlation strengths of atomic transitions were visualized in Aluminium (Al), Copper (Cu), and Brass whereas correlation strengths of atomic, atomic and ionic transitions were visualized in Au-Ag bimetallic targets with different compositions (Au30Ag70, Au50Ag50, Au80Ag20). The improved spectra were subsequently used in the principal component analysis for classification studies of four compositions of bimetallic targets (Au20Ag80, Au30Ag70, Au50Ag50, and Au80Ag20). The variance of the first three principal components was found to be improved from the analysis. The accumulated percentage of explained variance of ~95 was achieved with the first three components from improved spectra whereas only ~80 was achieved with the regular LIBS spectra from PCA studies.","PeriodicalId":19750,"journal":{"name":"OSA Continuum","volume":" ","pages":""},"PeriodicalIF":1.6000,"publicationDate":"2021-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Improving the signal-to-noise ratio of atomic transitions in LIBS using two-dimensional correlation analysis\",\"authors\":\"L. Narlagiri, Venugopal Rao Soma\",\"doi\":\"10.1364/OSAC.426995\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this study, two-dimensional (2D) correlation analysis was utilized for achieving a significant improvement in the signal-to-noise (S/N) ratio of laser-induced breakdown spectroscopy (LIBS) data. Time-resolved LIBS spectra of metallic, bimetallic targets and the normal LIBS spectra of bimetallic targets with varying compositions were used for the detailed analysis. The diagonal of the matrix in the synchronous spectra was used to demonstrate the improvement in the S/N ratio. An improvement in the peak intensities by few orders of magnitude accompanied by suppression in the noise was observed. The correlations between LIBS peaks were also visualized using 2-D plots. Correlation strengths of atomic transitions were visualized in Aluminium (Al), Copper (Cu), and Brass whereas correlation strengths of atomic, atomic and ionic transitions were visualized in Au-Ag bimetallic targets with different compositions (Au30Ag70, Au50Ag50, Au80Ag20). The improved spectra were subsequently used in the principal component analysis for classification studies of four compositions of bimetallic targets (Au20Ag80, Au30Ag70, Au50Ag50, and Au80Ag20). The variance of the first three principal components was found to be improved from the analysis. The accumulated percentage of explained variance of ~95 was achieved with the first three components from improved spectra whereas only ~80 was achieved with the regular LIBS spectra from PCA studies.\",\"PeriodicalId\":19750,\"journal\":{\"name\":\"OSA Continuum\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":1.6000,\"publicationDate\":\"2021-03-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"OSA Continuum\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1364/OSAC.426995\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"OPTICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"OSA Continuum","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1364/OSAC.426995","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"OPTICS","Score":null,"Total":0}
Improving the signal-to-noise ratio of atomic transitions in LIBS using two-dimensional correlation analysis
In this study, two-dimensional (2D) correlation analysis was utilized for achieving a significant improvement in the signal-to-noise (S/N) ratio of laser-induced breakdown spectroscopy (LIBS) data. Time-resolved LIBS spectra of metallic, bimetallic targets and the normal LIBS spectra of bimetallic targets with varying compositions were used for the detailed analysis. The diagonal of the matrix in the synchronous spectra was used to demonstrate the improvement in the S/N ratio. An improvement in the peak intensities by few orders of magnitude accompanied by suppression in the noise was observed. The correlations between LIBS peaks were also visualized using 2-D plots. Correlation strengths of atomic transitions were visualized in Aluminium (Al), Copper (Cu), and Brass whereas correlation strengths of atomic, atomic and ionic transitions were visualized in Au-Ag bimetallic targets with different compositions (Au30Ag70, Au50Ag50, Au80Ag20). The improved spectra were subsequently used in the principal component analysis for classification studies of four compositions of bimetallic targets (Au20Ag80, Au30Ag70, Au50Ag50, and Au80Ag20). The variance of the first three principal components was found to be improved from the analysis. The accumulated percentage of explained variance of ~95 was achieved with the first three components from improved spectra whereas only ~80 was achieved with the regular LIBS spectra from PCA studies.