Improving LIBS analysis of non-flat heterogeneous samples by signals mapping

Area of Science:

• Analytical Chemistry
• Materials Science

Background:

• Laser-induced breakdown spectroscopy (LIBS) faces challenges in heterogeneous material analysis due to sampling and surface irregularities.
• Accurate zinc (Zn) determination in complex matrices like soybean grist requires robust analytical methods.

Purpose of the Study:

• To evaluate complementary methods for improving LIBS analysis of soybean grist.
• To assess the effectiveness of different LIBS signal processing techniques for Zn quantification.
• To investigate the impact of sample heterogeneity and surface topography on LIBS accuracy.

Main Methods:

• Utilized laser-induced breakdown spectroscopy (LIBS) for material analysis.
• Employed complementary techniques: plasma imaging, plasma acoustics, and sample surface color imaging.
• Performed statistical analysis of LIBS signals and correlations with complementary data.
• Applied LIBS mapping to analyze non-flat heterogeneous samples.

Main Results:

• Atomic/ionic emission and most LIBS signals followed normal distribution, unlike acoustic signals.
• Correlations between LIBS and complementary signals were weak due to material variability.
• Analyte line normalization on plasma background emission proved effective for Zn analysis.
• Representative Zn quantification required hundreds of spot samplings.
• LIBS mapping highlighted the critical importance of sampling area selection for accurate determination.

Conclusions:

• Complementary methods offer limited improvement for Zn determination in soybean grist via LIBS.
• Analyte line normalization is a viable strategy for Zn quantification in heterogeneous materials.
• Achieving representative quantification necessitates extensive sampling or careful area selection in LIBS analysis.