An Image Auxiliary Method for Quantitative Analysis of Laser-Induced Breakdown Spectroscopy

Area of Science:

• Analytical Chemistry
• Spectroscopy
• Materials Science

Background:

• Quantitative analysis using Laser-Induced Breakdown Spectroscopy (LIBS) faces challenges in stability and accuracy, particularly in non-laboratory environments.
• Maintaining a consistent distance between the optical system and sample surface is crucial but difficult, leading to spectral fluctuations.
• Fluctuations in LIBS spectra significantly impact the reliability of quantitative elemental analysis.

Purpose of the Study:

• To develop and validate an auxiliary method using plasma image analysis to improve LIBS stability and accuracy.
• To reduce spectral fluctuations caused by variations in the optical system-sample distance.
• To apply the enhanced LIBS method for the quantitative analysis of elements in steel samples.

Main Methods:

• Extraction of principal components from plasma images to correct spectral line intensities.
• Integration of the image auxiliary method with both univariate and multivariate analysis techniques.
• Analysis of Copper (Cu), Manganese (Mn), Vanadium (V), and Chromium (Cr) concentrations in steel samples.

Main Results:

• Univariate analysis showed determination coefficients (R²) exceeding 0.99 for all four elements.
• Average relative standard deviations (RSDs) for spectral intensities decreased significantly, e.g., from over 20% to below 4%.
• Multivariate analysis also achieved R² values above 0.99, with validation sample concentration RSDs below 7%.

Conclusions:

• The proposed image auxiliary method effectively enhances the stability and accuracy of LIBS for quantitative analysis.
• This approach mitigates spectral fluctuations, making LIBS more reliable for in-situ or field applications.
• The method demonstrates high performance for determining multiple elements in steel matrices using both univariate and multivariate approaches.