Advancing Mineral Identification in Geological Samples with Laser-Induced Breakdown Spectroscopy Mapping


A recent study published in Spectrochimica Acta Part B: Atomic Spectroscopy presents a new mineral identification technique based on laser-induced breakdown spectroscopy (LIBS) (1). This new technique allows for accurate identification of minerals in geological samples.

minerals extracted in a rare earth mine background, illustration for product presentation template, copy space. Ai generative | Image Credit: © Roni -

minerals extracted in a rare earth mine background, illustration for product presentation template, copy space. Ai generative | Image Credit: © Roni -

The mining sector relies on accurate detection of minerals. Traditional methods that have been deployed in the past for mineral identification had limitations. In particular, these methods relied solely on intrinsic properties (for example, color); as a result, geologists and scientists often struggled to obtain comprehensive insights into the composition of the mineral (1). The new technique rectifies this issue. By using LIBS mapping, mineral identification accuracy is improved because LIBS allowed for an in-depth understanding of chemical element distribution on the surface of samples (1).

Developing the new mineral identification technique required using a feature extraction technique and k-means clustering. The feature extraction technique was based on the specific line intensities of major elements (1). By using this approach, the researchers created a visualization tool for cluster assignment (1). This greatly improved their ability to interpret the results.

Also in their study, the researchers tested the processing pipeline and algorithm on samples composed of mica, albite, quartz, and lepidolite (1). These minerals all have one thing in common; they are typically found in pegmatite veins (1). The algorithm showcased robustness and consistency in identifying spatial regions with the same mineralogical composition (1).

One of the key strengths of this technique using LIBS is its adaptability. By incorporating a training process based on cluster labeling and testing on blind samples, the unsupervised methodology can be transformed into a classifier capable of generalizing and classifying minerals in unseen samples (1). This adaptability makes it valuable for identifying minerals in real-world applications where sample variations are common (1).

LIBS is an important technique in the mining industry and in geological science applications. The successful deployment of this LIBS mapping-based methodology improves the mineral identification process by establishing a more innovative technique (1). The researchers set out to develop a more efficient technique that can conduct mineral identification more efficiently and accurately, and with the development of this technique, they succeeded. As the researchers expand their dataset and refine the algorithm further, the potential for widespread adoption in mining and geological studies becomes increasingly evident. The mining industry can now look forward to enhanced productivity and resource management, while geologists can use this new technique to gain greater insight into the Earth's composition (1).


(1) Capela, D.; Ferreira, M. F. S.; Lima, A.; et al. Robust and interpretable mineral identification using laser-induced breakdown spectroscopy mapping. Spectrochimia Acta Part B: At. Spectrosc. 2023, 206, 106733. DOI: 10.1016/j.sab.2023.106733

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