Research progress on laser-induced breakdown spectroscopy for improving the accuracy of mining and metallurgical analysis

Laser-induced breakdown spectroscopy (LIBS) is a type of atomic emission spectroscopy for multi-element analysis. This analysis is rapid and accurate, has a simple sample preparation, and realizes remote analysis. However, the accuracy of the qualitative and quantitative LIBS analysis methods in the field of mining and metallurgy has suffered from the complexity and diversity of the chemical composition of ore and metallurgical samples, interference signals, high dimension of the laser spectrum line, and severe self-absorption effect. To enhance the accuracy of LIBS analysis in the mining and metallurgy field, researchers have conducted numerous research on signal enhancement, spectral pretreatment, and modeling methods. In this review, three signal enhancement methods of LIBS in mining and metallurgy are evaluated: double pulse, nanoparticle enhancement, and space constraint. To avoid noise interference, overfitting, and “self-erosion,” three spectral preprocessing methods, including noise reduction, normalization, and self-absorption correction, are also reviewed. Moreover, to improve the generalization ability and analysis accuracy of the qualitative and quantitative modeling methods, extensive research has been conducted on model algorithms and parameter optimization. This paper briefly outlines the application of five typical LIBS qualitative analysis modeling methods in ore and metallurgical samples: principal component analysis method, partial least squares discriminant analysis method, support vector machine, random forest, and artificial neural network, and application results of five quantitative analysis modeling methods in ore and metallurgical samples: multiple linear regression method, partial least square method, support vector machine, artificial neural network, and free calibration method. Currently, light element ores, such as phosphate and lithium ores, rare earth and scattered elements, and the combined use of instruments are rarely investigated using LIBS; thus, future developments in LIBS technology for mineral and metallurgical analysis should mainly focus on the following aspects: (1) Research on LIBS online monitoring technology and suitable instrumentation because the application of online real-time and in situ monitoring analysis in the mining and metallurgical process has not been fully achieved. (2) Application of this method for the rapid analysis of light elements and complex ore and metallurgical samples, especially for online analysis, under special environmental conditions. (3) Improvement in the accuracy of the LIBS analysis and its application range in combination with other analytical techniques, such as Raman spectroscopy and infrared spectroscopy.