Quantitative estimation of elemental composition employing a synthetic generated spectrum

Area of Science:

• Analytical Chemistry
• Spectroscopy
• Materials Science

Background:

• Accurate elemental composition analysis is crucial for materials characterization.
• Traditional methods can struggle with complex spectra and merged emission lines.
• Self-absorption in plasma spectra complicates quantitative analysis.

Purpose of the Study:

• To develop an improved method for estimating the elemental composition of multielement samples.
• To minimize errors in quantitative analysis by fitting a large number of emission lines simultaneously.
• To account for self-absorption effects in synthetic spectrum generation for enhanced accuracy.

Main Methods:

• Utilizing a nonlinear fitting routine with a synthetically generated spectrum.
• Incorporating self-absorption of emission lines based on species number density in the plasma.
• Iteratively calculating Stark width using observed width and self-absorption degree.
• Applying the developed scheme to stainless steel and brass samples.

Main Results:

• The method successfully minimized estimation errors by fitting numerous emission lines concurrently.
• Accurate convergence of the retrieval algorithm was achieved even for dense and merged spectral lines.
• Laser-induced breakdown spectroscopy (LIBS) results for stainless steel and brass showed excellent agreement with electron probe microanalyzer (EPMA) measurements.

Conclusions:

• The developed synthetic spectrum generation and nonlinear fitting approach provides accurate elemental composition estimation.
• The method effectively handles spectral complexities like self-absorption and merged lines.
• This technique offers a reliable and accurate alternative for analyzing multielemental samples using LIBS.