Optimization of the spectral data processing in a LIBS simultaneous elemental analysis system |
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| Affiliation: | 1. School of Computer Science, University of Massachusetts Amherst, 140 Governor''s Drive, Amherst, MA 01003, United States.;2. Department of Astronomy, Mount Holyoke College, South Hadley, MA 01075, United States;3. Los Alamos National Laboratory, P.O. Box 1663, MS J565, Los Alamos, NM 87545, United States;1. School of Electric Power, South China University of Technology, Guangzhou, Guangdong 510640, China;2. State Key Laboratory of Pulsed Power Laser Technology, Electronic Engineering Institute, Hefei 230037, China;1. Laser and Spectroscopy Laboratory, Department of Physics, Banaras Hindu University, Varanasi, India;2. Institute for Clean Energy Technology, Mississippi State University, Starkville, MS, United States;1. Los Alamos National Laboratory, USA;2. USGS Flagstaff, USA;3. L''Institut de Recherche en Astrophysique et Planétologie, France;4. Universite de Lorraine, France;5. University of Massachusetts, USA;6. Mt. Holyoke College, USA;7. SUNY Stony Brook, USA;8. Johnson Space Center, USA;9. Franklin & Marshall College, USA;10. Division of Geological and Planetary Sciences, California Institute of Technology, Pasadena, CA 91125, USA;11. Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA 91109, USA;12. University of New Mexico, USA;13. Space Science Institute, USA;14. University of Massachusetts Lowell, USA;15. The College of New Jersey, USA |
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| Abstract: | An instrumentation variation on laser-induced breakdown spectroscopy (LIBS) is described that allows simultaneous determination of all detectable elements using a multiple spectrograph and synchronized, multiple CCD spectral acquisition system. The system is particularly suited to the rapid analysis of heterogeneous materials such as coal and mineral ores. For the analysis of a heterogeneous material the acquisition cycle typically stores 1000 spectra for subsequent filtering and analysis. The incorporation of an effective data analysis methodology has been critical in achieving both accurate and reproducible results in the analysis of powders with the technology. Using naturally occurring gypsum as the optimization matrix, various data analysis techniques have been investigated including: using pulse-to-pulse internal standardisation; data filtering; and spectral deconvolution. The incorporation of normalization of the elemental emission to the total plasma emission intensity has been found to yield the single biggest improvement in accuracy and precision. Spectral deconvolution has been found to yield further improvement and is particularly relevant to the analysis of complex materials such as black coal. The use of pulse-to-pulse intensity normalization has the further benefit of extending the period between instrument recalibration, thus enhancing the ease of use of the device. The benefit of the optimized data analysis methodology is revealed in the determination of eight elemental components of gypsum (Na, Ca, Mg, Fe, Al, Si, Ti and K) where a typical absolute analysis accuracy of ±10% is obtained. These results compare favourably to analysis by conventional techniques for these materials. The analysis accuracy and repeatability is further demonstrated by the determination of the concentrations of these elements in a black coal sample. |
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