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DOI	10.1016/j.sab.2019.105715
	Accuracies of lithium; boron; carbon; and sulfur quantification in geological samples with laser-induced breakdown spectroscopy in Mars; Earth; and vacuum conditions
	Ytsma C.R.; Dyar M.D.
发表日期	2019
ISSN	5848547
卷号	162
英文摘要	Laser-induced breakdown spectroscopy (LIBS) is valued for its ability to remotely detect a wide range of elements, including light elements, under a variety of atmospheric conditions. This study uses LIBS spectra of 402 rock standards to quantify lithium (Li), boron (B), carbon/carbon dioxide (C/CO2), and sulfur (S) in Mars and Earth atmospheres and under vacuum. Two regression methods were tested: univariate analysis (UVA), here using peak areas to predict concentrations, and multivariate analysis (MVA). Partial least squares (PLS) and the least absolute shrinkage and selection operator (lasso) use information from larger regions of LIBS spectra. Rock powders were doped with up to 10 wt% of each light element to help identify strongly correlated peaks for UVA. UVA and MVA models were assessed using root mean square errors (RMSEs) of cross-validation (CV), calibration RMSEs, and R2 correlation between predicted and true concentrations. Li had the most strongly correlated peaks, similar UVA and MVA model performance, and the lowest relative prediction errors. B and C had few weakly-correlated peaks, leading to extremely poor UVA R2 correlations despite having similar RMSEs to MVA models with mediocre performance. S had no visible peaks in our LIBS setup and as a result, MVA models had extremely high prediction errors. Model performance was not significantly affected by atmospheric differences despite visible changes in peak appearance, as long as model and test data were acquired under identical conditions. PLS regression on the entire LIBS spectrum consistently created models with the lowest quantification errors and highest R2 correlations. Light element predictions may be improved using higher resolution, gated spectrometers that cover a wider wavelength range than those used in our setup, which matches ChemCam. Elsevier B.V.
英文关键词	Atmospheric differences; LIBS; Light elements; Multivariate analysis; Univariate analysis
scopus关键词	Atomic emission spectroscopy; Errors; Forecasting; Learning algorithms; Least squares approximations; Lithium; Mean square error; Regression analysis; Spectrometers; Spectrum analysis; Sulfur; Sulfur dioxide; Laserinduced breakdown spectroscopy (LIBS); Least absolute shrinkage and selection operators; LIBS; Light elements; Multi variate analysis; Partial least square (PLS); Root mean square errors; Univariate analysis; Multivariant analysis
来源期刊	Spectrochimica Acta - Part B Atomic Spectroscopy
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/176285
作者单位	Department of Astronomy, Mount Holyoke College, South Hadley, MA 01075, United States
推荐引用方式 GB/T 7714	Ytsma C.R.,Dyar M.D.. Accuracies of lithium; boron; carbon; and sulfur quantification in geological samples with laser-induced breakdown spectroscopy in Mars; Earth; and vacuum conditions[J],2019,162.
APA	Ytsma C.R.,&Dyar M.D..(2019).Accuracies of lithium; boron; carbon; and sulfur quantification in geological samples with laser-induced breakdown spectroscopy in Mars; Earth; and vacuum conditions.Spectrochimica Acta - Part B Atomic Spectroscopy,162.
MLA	Ytsma C.R.,et al."Accuracies of lithium; boron; carbon; and sulfur quantification in geological samples with laser-induced breakdown spectroscopy in Mars; Earth; and vacuum conditions".Spectrochimica Acta - Part B Atomic Spectroscopy 162(2019).