Quantitative analysis of slurry sample by laser-induced breakdown spectroscopy

Area of Science:

• Analytical Chemistry
• Spectroscopy
• Materials Science

Background:

• Quantitative analysis of slurry samples is critical but difficult due to splashing, surface turbulence, and sedimentation.
• Traditional laser-induced breakdown spectroscopy (LIBS) has shown limited success with slurry matrices owing to inherent disadvantages.
• Developing robust analytical methods for complex industrial slurries is essential for process control and quality assurance.

Purpose of the Study:

• To evaluate a novel spin-on-glass sampling method for enhancing the precision and accuracy of LIBS analysis on slurry samples.
• To investigate the effectiveness of different calibration models for quantitative elemental determination in slurry simulants.
• To compare LIBS results with a reference method for validation.

Main Methods:

• Slurry simulants containing varying concentrations of Al, Ca, Fe, Ni, and Si were prepared.
• A spin-on-glass technique was employed as a sample preparation method for LIBS analysis.
• Univariate calibration, multiple linear regression (MLR), and partial least square regression (PLSR) models were developed.
• Inductively coupled plasma optical emission spectroscopy (ICP-OES) was used as a reference analytical technique.

Main Results:

• The spin-on-glass method demonstrated improved LIBS analysis performance for slurry samples.
• Partial least square regression (PLSR) model provided the best fit for the experimental data.
• LIBS results obtained using the PLSR model showed excellent agreement with ICP-OES measurements.
• The method successfully quantified five key elements (Al, Ca, Fe, Ni, Si) in the slurry simulants.

Conclusions:

• The spin-on-glass sampling method significantly enhances the accuracy and precision of LIBS for slurry analysis.
• Partial least square regression is the most effective calibration strategy for LIBS analysis of slurries using this method.
• This approach offers a viable alternative for reliable elemental quantification in challenging slurry matrices.