Raw signal improvement using beam shaping plasma modulation for uranium detection in ore using laser-induced...

Area of Science:

• Geochemistry
• Analytical Chemistry
• Spectroscopy

Background:

• Real-time quantitative detection of uranium in ores is crucial for exploration.
• Laser-induced breakdown spectroscopy (LIBS) shows promise but faces sensitivity challenges due to ore matrix complexity and low uranium concentrations.
• Existing LIBS methods struggle with low uranium detection sensitivity in complex ore samples.

Purpose of the Study:

• To explore a beam-shaping plasma modulation method for improving the limit of detection (LOD) of uranium in ores.
• To enhance the sensitivity and repeatability of LIBS for uranium detection in geological samples.
• To overcome limitations of traditional LIBS in analyzing complex matrices with low analyte concentrations.

Main Methods:

• Utilized a beam-shaping technique to modify the laser beam profile from Gaussian to flat-top.
• Investigated the effect of beam shaping on plasma characteristics, including excitation, electron density, and morphological stability.
• Employed laser-induced breakdown spectroscopy (LIBS) for quantitative analysis of uranium in ore samples.

Main Results:

• The flat-top beam modulation enhanced LIBS signal intensity by approximately 5 times compared to the Gaussian beam, primarily by increasing plasma temperature.
• Relative standard deviation (RSD) of the signal was reduced by about 50%, indicating improved repeatability.
• The limit of detection (LOD) for uranium in ores was estimated at 21.2 ppm using the flat-top beam, a significant improvement.

Conclusions:

• Beam-shaping plasma modulation is a promising method for enhancing LIBS performance in uranium detection in ores.
• This technique effectively increases signal intensity and repeatability while reducing the LOD, addressing key challenges in uranium exploration.
• The optimized LIBS approach facilitates rapid and accurate quantitative analysis of uranium in complex geological matrices.