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Lithium ion detection in liquid with low detection limit by laser-induced breakdown spectroscopy.
Appl Opt ; 58(2): 422-427, 2019 Jan 10.
Article in En | MEDLINE | ID: mdl-30645331
Lithium (Li), as the lightest metal and the most important powerful material in battery fabrication, is widely used in many fields. The fast detection of Li is necessary for industrial application. The slow-speed detection methods, including atomic absorption spectroscopy and inductively coupled plasma mass spectroscopy with high accuracy and low limit of detection, are hard to utilize in in situ industrial control due to complex prepreparation of samples. Here, through the analysis of the typical spectrum line at Li I 670.79 nm, Li ions in water were detected quantitatively in 1 min, including sample preparation by laser-induced breakdown spectroscopy (LIBS) with filter paper as the adsorption substrate. The calibration curve by polynomial function fitting is used to predict the Li+ concentration. The limit of detection (LOD) as low as 18.4 ppb is obtained, which is much lower than the results ever reported by using filter paper. The related factor R2 reaches 99%, and the prediction error is lower than 2%, proving the fast and online monitor for Li+ by LIBS is feasible. Furthermore, by comparison with the results with filter paper enrichment, the Li+ detection from water directly shows higher LOD to 10.5 ppm. Moreover, the plasma images, by gate-controlled intensified charge-coupled device, illustrate a different morphology and evolution between that on water surface and filter paper surface through visual observation. This study provides experimental and theoretical experience in a fast way for the quantitative detection of the lightest metal ion (Li+) in liquid.

Full text: 1 Collection: 01-internacional Database: MEDLINE Type of study: Diagnostic_studies / Prognostic_studies Language: En Journal: Appl Opt Year: 2019 Document type: Article Country of publication: Estados Unidos

Full text: 1 Collection: 01-internacional Database: MEDLINE Type of study: Diagnostic_studies / Prognostic_studies Language: En Journal: Appl Opt Year: 2019 Document type: Article Country of publication: Estados Unidos