Quantitative Analysis of U by Laser-induced Breakdown Spectroscopy.

Uranium ore is one of the most important mineral resources in nuclear industry, and the nuclear industry is in urgent need of an analytical technology that can quickly and effectively explore uranium ore resources. Rapid and effective exploration of uranium ore resources could promote the stable and healthy development of the nuclear industry. Laser induced breakdown spectroscopy (LIBS) is a kind of emission spectral element analysis technology, which has the advantages of rapid detection of multi-target elements, and can realize the purpose of rapid and accurate field exploration and analysis of uranium resources. The quantitative analysis of U in uranium ore was carried out based on LIBS technology and machine learning. A total of 12 groups of experimental samples were prepared in this work, and 9 groups of samples were set as training sets for model establishment and hyper-parameter optimization. Three sets of samples were set for model validation. Partial least squares(PLS) and Random forest(RF) algorithms were used to establish a quantitative model, and the hyper-parameters of the two models were optimized by the ten-fold cross-validation method. Finally, the quantitative effects of the two models were verified and compared by three verification sets. After hyper-parameter optimization, both quantitative models had good linear correlation and model stability. The linear correlation coefficient of RF quantitative model was 0.996, while that of PLS quantitative model was 0.997. In terms of model validation, the relative errors of RF model for the three validation sets were 22.33%, 12.79% and 12.04%, respectively. The relative errors of PLS model for the three verification sets were 4.33%, 6.63% and 6.85 %, respectively. Compared with the verification results of the two quantitative models, the relative error of the PLS model on the three verification sets was lower than that of the RF model, which indicated that the PLS model had higher quantitative accuracy than the RF model. Therefore, compared with RF algorithm, PLS algorithm is more suitable for quantitative analysis of U LIBS in uranium ore. [ABSTRACT FROM AUTHOR]