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Dependence of Laser-induced Breakdown Spectroscopy Results on Pulse Energies and Timing Parameters Using Soil Simulants
Published on: September 23, 2013
Extraction of information from laser-induced breakdown spectroscopy spectral data by multivariate analysis
Nicole Labbé1, Isabel Maya Swamidoss, Nicolas André
1Forest Products Center, Department of Forestry, Wildlife and Fisheries, University of Tennessee, 2506 Jacob Drive, Knoxville, Tennessee 37996-4570, USA.
Applied Optics
|January 6, 2009
Summary
Laser-induced breakdown spectroscopy (LIBS) can assess material elemental composition. Multivariate analysis of LIBS spectral data, using multiple emission lines, enhances elemental analysis robustness in biological materials.
Area of Science:
- Analytical Chemistry
- Spectroscopy
- Chemometrics
Background:
- Laser-induced breakdown spectroscopy (LIBS) is a high-throughput method for elemental composition analysis.
- Semiquantification of elements is typically achieved using single emission line intensities in calibration models.
- Multiple emission lines from a single element often provide superior analytical information compared to individual lines.
Purpose of the Study:
- To explore the application of multivariate chemometric methods for enhanced elemental analysis in biological materials using LIBS.
- To develop more robust calibration models by incorporating multiple emission lines per element.
Main Methods:
- Utilized Laser-induced breakdown spectroscopy (LIBS) to collect spectral data from biological samples.
- Applied multivariate chemometric techniques, specifically Principal Component Analysis (PCA) and Partial Least Squares (PLS).
- Developed calibration models considering all relevant emission lines for specific elements.
Main Results:
- Demonstrated that multivariate approaches integrating multiple emission lines improve analytical robustness.
- Successfully extracted valuable information from complex LIBS spectral data of biological materials.
- Showcased the potential of PCA and PLS in enhancing LIBS quantitative analysis.
Conclusions:
- Multivariate analysis of LIBS spectral data offers a more robust approach to elemental composition assessment.
- Combining multiple emission lines through chemometric methods significantly improves analytical performance.
- LIBS coupled with PCA and PLS is a powerful strategy for analyzing biological materials.
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