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Updated: Feb 20, 2026

ARL Spectral Fitting as an Application to Augment Spectral Data via Franck-Condon Lineshape Analysis and Color Analysis
Published on: August 19, 2021
Decomposition and correction overlapping peaks of LIBS using an error compensation method combined with curve fitting
This study introduces an error compensation method to resolve overlapping peaks in laser-induced breakdown spectroscopy (LIBS) spectra. This technique improves spectral analysis accuracy for material composition detection.
Area of Science:
- Analytical Chemistry
- Spectroscopy
- Materials Science
Background:
- Laser-induced breakdown spectroscopy (LIBS) is crucial for material composition analysis.
- Overlapping spectral peaks present a significant challenge in LIBS data interpretation.
- Accurate peak decomposition is essential for reliable qualitative and quantitative analysis.
Purpose of the Study:
- To develop and evaluate an error compensation method for decomposing and correcting overlapping peaks in LIBS spectra.
- To enhance the accuracy of quantitative analysis in LIBS by addressing spectral interferences.
- To improve the correlation and reduce fitting residuals in spectral analysis.
Main Methods:
- Utilized a curve fitting approach with an iterative error compensation mechanism.
- Implemented a feedback loop where fitting residuals inform subsequent curve fitting iterations.
- Applied the method to decompose and correct overlapping Cu-Fe peaks (321-327 nm) in LIBS spectra of CuSO4·5H2O solutions.
Main Results:
- The error compensation method significantly reduced fitting residuals by 18.12-32.64% compared to standard curve fitting.
- Improved the correlation coefficient by 0.86-1.82% for quantitative analysis of copper (Cu).
- Established a more linear calibration curve between spectral intensity and Cu concentration.
Conclusions:
- The developed error compensation method effectively decomposes and corrects overlapping peaks in LIBS spectra.
- This technique enhances the accuracy and reliability of quantitative LIBS analysis.
- The method shows promise for broader applications in spectral analysis where peak overlap is an issue.
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