Advancements in Lithium Quantification in Geological Samples using Sci-Trace/M-Trace LIBS Technology

Leading-edge poster that received two honorable awards, with one awarded as the best at NordicLibs and the other as one of the top 3 at ESAS. This poster also received significant interest and attention for its content, which is why we decided to share it on our website.

Lithium mining is difficult due to a combination of geological, environmental, technical, regulatory, and social factors. Addressing these challenges is crucial, particularly as lithium is a key component in the production of batteries for electric vehicles and energy storage systems, which are essential for the transition to renewable energy. As the demand for lithium continues to grow, finding sustainable and ethical mining practices becomes a critical duty for the industry, in order to minimize environmental and social impacts. 

LIBS is being implemented in industrial applications, where it can provide important advantages over other techniques. It is a fast analytical technique that provides near real-time analysis. LIBS can quickly determine lithium content in ore samples, making it suitable for high-throughput mining operations where timely information is crucial. This information is essential for assessing the economic viability of a mining site and extraction process. Miners can use LIBS to determine which ore bodies contain higher lithium concentrations, focusing their efforts on the most promising areas. LIBS contributes to process optimization, quality control, environmental compliance, and efficient resource management in the lithium industry, ultimately enhancing the overall efficiency and sustainability of lithium production. 

EXPERIMENTAL – Samples and parameters of measurement  

Measurement was performed on two datasets with different geological matrices. Dataset A were Li-bearing granites with Li-rich micas (concentration range from 30 to 24 863 mg kg-1 ). Dataset B consisted of Li-rich minerals of rhyolite occurrence with MnO mineral varieties (concentration range from 4 mg kg-1 to 814 mg kg-1 ). The parameters of measurement were the following: 

RESULTS – Spectral lines

The spectrum excerpt highlights the region of interest around the lithium peak with greater detail. Diminishing the laser energy results in a more pronounced narrowing of this peak, which is indicative of temperature-dependent Stark and Doppler effects influencing peak broadening. Such a reduction improves the resolution of the peaks, allowing clearer differentiation, especially from the interfering Ar emission line at 811.48 nm.

RESULTS – Calibration curves 

Although it is theoretically feasible to apply a single calibration curve across the entire concentration span, given a coefficient of determination R2 = 0.9685, segmenting into two distinct ranges with bespoke calibrations for varying concentration bands yields a statistically significant enhancement in prediction accuracy. 

The relative deviation, defined as the ratio of the integral of the difference function to the intensity range, was computed, yielding δrel = 246 for lower concentrations and 123 for higher ones. Values far higher than 1 show that the differences between the curves are substantial and should not be overlooked in analytical assessments. The R2 value is improved by comparing the observed peak with the matrix peak as depicted in the figure above.

CONCLUSION

• Demonstration of the analytical ability of LIBS for Li quantification and analyses in ores (R2 = 0.97 – 0.99). 
• Li 812.6 nm gives best results – Li I 610.4 nm interference with Ca, Li I 670.8 nm becomes easily saturated. 
• Decrease in laser energy leads to higher resolution (suppression of Stark effect and Doppler broadening). 
• Using a different calibration curve for different concentration regions increases the accuracy of the prediction.