Development of a method for automated quantitative analysis of ores using LIBS
This paper reports the development of a method for real-time automated quantitative analysis of mineral ores using a commercial laser-induced breakdown spectroscopy instrument, TRACER™ 2100, fitted with a recently developed computer controlled auto-sampler. The auto-sampler permits the execution of...
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Veröffentlicht in: | Spectrochimica acta. Part B: Atomic spectroscopy 2001-06, Vol.56 (6), p.707-714 |
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Sprache: | eng |
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Zusammenfassung: | This paper reports the development of a method for real-time automated quantitative analysis of mineral ores using a commercial laser-induced breakdown spectroscopy instrument, TRACER™ 2100, fitted with a recently developed computer controlled auto-sampler. The auto-sampler permits the execution of methods for performing calibrations and analysis of multiple elements on multiple samples. Furthermore, the analysis is averaged over multiple locations on each sample, thus compensating for heterogeneous morphology. The results for phosphate ore are reported here, but similar methods are being developed for a range of ores and minerals. Methods were developed to automatically perform metallic element calibrations for supplied phosphate ore samples containing known concentrations of the following minerals: P
2O
5, CaO, MgO, SiO
2 and Al
2O
3. A spectral line for each desired element was selected with respect to the best combination of peak intensity and minimum interferences from other lines. This is a key step, because of the observed matrix dependence of the technique. The optimum combination of the time interval between the laser firing (plasma formation), signal detection, and the duration of the optical detection was then determined for each element, to optimize spectral line intensity and resolution. The instrument was capable of analyzing the required elements in the phosphate ore samples supplied with 2–4% relative standard deviations for most elements. Calibrations were achieved for P, Ca, Mg, Al and Si with linear regression coefficients of 0.985, 0.980, 0.993, 0.987 and 0.985, respectively. Preparation and analysis time for each sample was less than 5 min. |
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ISSN: | 0584-8547 1873-3565 |
DOI: | 10.1016/S0584-8547(01)00191-4 |