The application of spectrum standardization method for carbon analysis in coal using laser-induced breakdown spectroscopy

TL;DR

This paper introduces a spectrum standardization method for laser-induced breakdown spectroscopy (LIBS) that improves the accuracy and precision of carbon content measurement in coal by compensating for matrix effects and plasma fluctuations.

Contribution

The study develops a modified spectrum standardization model with an iterative algorithm that outperforms traditional normalization methods in LIBS coal analysis.

Findings

Reduced relative standard deviation to 3.44%

Achieved a coefficient of determination of 0.83

Lowered root-mean-square error to 2.71%

Abstract

Measurements of carbon content in coal using laser-induced breakdown spectroscopy (LIBS) is limited by its low measurement precision and accuracy. A spectrum standardization method was proposed to achieve both reproducible and accurate results for the quantitative analysis of carbon content in coal with LIBS. The proposed method utilized the molecular carbon emissions to compensate the diminution of atomic carbon emission caused by matrix effect. The compensated carbon line intensities were further converted into an assumed standard state with fixed plasma temperature, electron density, and total number density of elemental carbon, which is proportional to its concentration in the coal samples. In addition, in order to obtained better compensation for total carbon number density fluctuations, an iterative algorithm was applied, which is different from our previous standardization calculations. The modified spectrum standardization model was applied to the measurement of carbon content in 24 bituminous coal samples. The results demonstrated that the proposed method had superior performance over the generally applied normalization methods. The average relative standard deviation, the coefficient of determination, the root-mean-square error of prediction, and the average maximum relative error for the modified model were 3.44%, 0.83, 2.71%, and 12.61%, respectively, while the corresponding values for the normalization with segmental spectrum area were 6.00%, 0.75, 3.77%, and 15.40%, respectively, showing an overwhelming improvement.