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A recent study describes the development of a neural network data analysis method to rapidly characterize gallium concentration in plutonium matrices using laser-induced breakdown spectroscopy (LIBS).
Gallium is a rare and valuable metal that is used in various applications, including semiconductors, photovoltaic cells, and medical imaging. The analysis of gallium in plutonium matrices is essential for quality control (QC) when producing nuclear materials (1). According to this study, researchers have developed a data analysis method to rapidly characterize gallium concentration in plutonium matrices using laser-induced breakdown spectroscopy (LIBS) (1).
As a technique, LIBS concentrates a laser beam on the surface of a material, which causes a miniscule amount of material to vaporize and emit light. Then, the emitted light is analyzed to determine the chemical composition of the material (1). The researchers used LIBS to analyze the concentration of gallium in plutonium matrices and developed a data analysis method to rapidly characterize the concentration of gallium (1).
The machine-learning data analysis method involved using a convolutional neural network training to rapidly analyze LIBS spectra (1). This method accomplished its goal of identifying the spectral signature of gallium in the LIBS spectra (1). The researchers used this method to accurately determine the concentration of gallium in plutonium matrices, with a limit of detection (LOD) of 0.05 wt% (1).
The new method that the researchers used has several advantages over traditional methods of analyzing gallium in plutonium matrices. It is nondestructive, meaning that the sample can be reused or repurposed after the measurement is taken (1). It is also fast, taking only a few minutes to collect and analyze a measurement. The method is highly accurate, with a precision of 1–2% and a relative error of less than 10% (1).
The researchers suggest that the method could be used for routine QC in the production of nuclear materials (1). They also recommend that it could be adapted for applications that require the rapid and accurate analysis of gallium concentration (1).
The study highlights the potential of data analysis methods in improving the accuracy and efficiency of chemical analysis using LIBS. The method could be adapted for use with other elements and matrices, helping to improve QC in a wide range of industries.
In summary, the development of a data analysis method to rapidly characterize gallium concentration in plutonium matrices using LIBS represents an advancement in chemical analysis (1). It has the potential to provide more confidence in the composition of materials in actinide-associated targets (1). The method may also help improve quality control in the production of nuclear materials and promote the efficient use of rare and valuable metals in a variety of industries.
(1) Vu, D. M.; Auxier II, J. D.; Judge, E. J.; Aldrich, K. E.; Gifford, B. J.; Saumon, D.; Neukirch, A. J.; Auxier, J. P.; Barefield II, J. E.; Clegg, S. M.; Martinez, R. K. A data analysis method to rapidly characterize gallium concentration in plutonium matrices using LIBS. Spectrochim. Acta Part B 2023, 203, 106650. DOI: 10.1016/j.sab.2023.106650.