Chemical analysis of industrial scale deposits by combined use of correlation coefficients with emission line detection of laser induced breakdown spectroscopy spectra

Laser-induced breakdown spectroscopy (LIBS) was used to determine the mineral composition of various industrial scale samples. The aim of the study has been to investigate the capacity of LIBS to provide a fast, reliable analytical tool for carrying out routine analysis of inorganic scales, potentia...

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Veröffentlicht in:Spectrochimica acta. Part B: Atomic spectroscopy 2013-09, Vol.87, p.86-91
Hauptverfasser: Siozos, P., Philippidis, A., Hadjistefanou, M., Gounarakis, C., Anglos, D.
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Sprache:eng
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Zusammenfassung:Laser-induced breakdown spectroscopy (LIBS) was used to determine the mineral composition of various industrial scale samples. The aim of the study has been to investigate the capacity of LIBS to provide a fast, reliable analytical tool for carrying out routine analysis of inorganic scales, potentially on site, as a means to facilitate decision making concerning scale removal procedures. LIBS spectra collected in the range of 200–660nm conveyed information about the metal content of the minerals. Via a straightforward analysis based on linear correlation of LIBS spectra it was possible to successfully discriminate scale samples into three main groups, Fe-rich, Ca-rich and Ba-rich, on the basis of correlation coefficients. By combining correlation coefficients with spectral data collected in the NIR, 860–960nm, where sulfur emissions are detected, it became further possible to discriminate sulfates from carbonates as confirmed by independent analysis based on Raman spectroscopy. It is emphasized that the proposed LIBS-based method successfully identifies the major mineral or minerals present in the samples classifying the scales into relevant groups hence enabling process engineers to select appropriate scale dissolution strategies. •LIBS was used to determine the mineral composition of industrial scale samples.•Three groups of inorganic scales were identified: Ca rich, Ba rich and Fe rich.•A method that combines correlation coefficients and line detection is proposed.•The method successfully identifies the main mineral, or minerals, in the samples.•The results were compared with results obtained by use of Raman analysis.
ISSN:0584-8547
1873-3565
DOI:10.1016/j.sab.2013.05.008