Absolute Analysis of Particulate Materials by Laser-Induced Breakdown Spectroscopy

We have developed a new data acquisition approach followed by a suitable data analysis for Laser-induced breakdown spectroscopy. It provides absolute concentrations of elements in particulate materials (e.g., industrial dusts and soils). In contrast to the known calibration procedures (based on the...

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Veröffentlicht in:Analytical chemistry (Washington) 1997-06, Vol.69 (11), p.2103-2108
Hauptverfasser: Xu, Liang, Bulatov, Valery, Gridin, Vladimir V, Schechter, Israel
Format: Artikel
Sprache:eng
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Zusammenfassung:We have developed a new data acquisition approach followed by a suitable data analysis for Laser-induced breakdown spectroscopy. It provides absolute concentrations of elements in particulate materials (e.g., industrial dusts and soils). In contrast to the known calibration procedures (based on the ratio of spectral lines), which are applicable only when one component is constant, this approach requires no constant constituent and results in absolute (rather than relative) concentrations. Thus, the major drawback of this analytical method, namely, the signals' instability (especially when particulate materials are concerned) is partially solved. Unlike the commonly used integrated data acquisition, we use a sequence of signals from single breakdown events. We compensate for pulse to pulse fluctuations in an intrinsic way, and the final results do not depend on the presence of any constant component. Extended linear calibration curves are obtained, and limits of detection are improved by 1 order of magnitude relative to previous methods applied to the same samples (e.g., detection limit of 10-12 g of Zn in aerosol samples). The proposed compensation for pulse variations is based on the assumption that they can be described as a multiplicative effect for both the spectral peaks and a component of the baseline. In other words, we assume that the same fluctuation pattern observed in the spectral peaks is present in the baseline as well. This assumption is shown to hold and is utilized in the proposed method. In addition, a proper data-filtering process, which eliminates ill-conditioned spectra, is shown to partially compensate for problems due to the nature of analysis of particulate materials.
ISSN:0003-2700
1520-6882
DOI:10.1021/ac970006f