Meirong Dong

Extracting Coal Ash Content from Laser-Induced Breakdown Spectroscopy (LIBS) Spectra by Multivariate Analysis

Laser-induced breakdown spectroscopy (LIBS) combined with partial least squares (PLS) analysis has been applied for the quantitative analysis of the ash content of coal in this paper. The multivariate analysis method was employed to extract coal ash content information from LIBS spectra rather than from the concentrations of the main ash-forming elements. In order to construct a rigorous partial least squares regression model and reduce the calculation time, different spectral range data were used to construct partial least squares regression models, and then the performances of these models were compared in terms of the correlation coefficients of calibration and validation and the root mean square errors of calibration and cross-validation. Afterwards, the prediction accuracy, reproducibility, and the limit of detection of the partial least squares regression model were validated with independent laser-induced breakdown spectroscopy measurements of four unknown samples. The results show that a good agreement is observed between the ash content provided by thermo-gravimetric analyzer and the LIBS measurements coupled to the PLS regression model for the unknown samples. The feasibility of extracting coal ash content from LIBS spectra is approved. It is also confirmed that this technique has good potential for quantitative analysis of the ash content of coal.

Experimental study on the characteristics of molecular emission spectroscopy for the analysis of solid materials containing C and N.

Solid materials with different structure containing C and N were analyzed by laser-induced breakdown spectroscopy (LIBS). Comparing the emission molecular species in different atmosphere (air and argon), it can be determined that whether the molecular species are directly vaporized from sample or generated through dissociation or the interaction between plasma and air molecules. The results showed that the characteristic of C2 bands emission is similar with that of neutral atomic carbon emission CI in different atmosphere (air and argon). While the characteristic of CN bands emission is more complicated and it has great relationship with the existence of CN radicals, the interaction between plasma and air ambient, and the recombination of excited partials.

Multi-elemental analysis of fertilizer using laser-induced breakdown spectroscopy coupled with partial least squares regression

Laser-induced breakdown spectroscopy (LIBS) has been applied for the multi-elemental analysis of fertilizer. With a set of 11 fertilizer samples containing different levels of phosphorus and potassium, it was identified that the line intensity of the analyte does not follow a straightforward correlation with the element concentration with the presence of matrix effects. Instead, the line intensity of a given analyte element is not only related to that analyte, but also to other elements present in the samples. Further analysis reveals the correlations among the line intensities of the main components. Based on the correlation analysis, a set of calibration models were generated for phosphorus and potassium with the method of partial least squares (PLS) analysis, which is known as a multivariate calibration method. The prediction accuracy and reproducibility of these PLS models were then validated using independent LIBS measurements. The results show that the predicted concentrations with these models provided by LIBS measurements are in good agreement with the reference concentrations, which confirms that the LIBS technique has good potential for the in situ rapid determination of the main elements present in fertilizer.

Analyzing unburned carbon in fly ash using laser-induced breakdown spectroscopy with multivariate calibration method

This paper presents an alternate calibration method for measurement of the unburned carbon (UC) in fly ash using laser-induced breakdown spectroscopy (LIBS). Fly ashes studied in this research were produced from pulverized coal in a muffle furnace and the UC was determined by a loss-on-ignition (LOI) test. We apply both univariate calibration and multivariate calibration methods to LIBS data to establish the calibration curve of the UC in measured samples, and the performance of these two approaches was compared. Our analysis shows that traditionally used univariate calibration in LIBS does not qualify quantitative analysis of fly ashes from different kinds of coal due to the presence of matrix effects. Instead, multivariate calibration has a better performance as the matrix effects can be taken into account with the influence of the spectroscopic signals of other components in fly ash. The correlation coefficients R2 of multivariate calibration reach 0.994 (fly ashes from one kind of coal) and 0.981 (fly ashes from different kinds of coal), which is significantly improved compared with univariate calibration.

Application of LIBS for direct determination of volatile matter content in coal

Volatile matter content is an important index of coal quality characteristics. Laser-induced breakdown spectroscopy (LIBS) is a promising analytical spectroscopy technique. In this paper, a broad set of coal samples with different amounts of volatile matter content were tested by LIBS. Analytical methods with partial correlation and principal component regression were used to extract related LIBS spectral information based on coal structure, which indicates a strong correlation with the content of volatile matter to establish the calibration model. The experimental results derived from the correlation are consistent with those from standard analysis procedures (thermo-gravimetric analysis, TGA). This demonstrates that LIBS is a viable approach to directly determine the volatile content rather than indirect ultimate analysis.

Experimental study of laser-induced breakdown spectroscopy (LIBS) for direct analysis of coal particle flow.

Laser-induced breakdown spectroscopy (LIBS) was employed to directly analyze coal particles in the form of descending flow. Coal-particle ablation was performed using a 1064 nm neodymium-doped yttrium aluminum garnet (Nd:YAG) laser at atmospheric conditions. Spectral identification schemes were used to acquire spectra containing all the emission lines of the important elements in coal. These acquired spectra were classified as representative spectra. The background of the line emission plus three times the standard deviation of the background of the representative spectra was chosen as the threshold value. A method using a single line and a method using combined multiple lines (C, 247.8 nm; N, 746.8 nm; Si, 288.2 nm; and Ca, 396.8 nm) were compared to obtain the best results for the spectral identification of coal particle flow. The feasibility of rejecting the partial breakdown spectra was verified using quantitative analysis of fixed carbon in coal.

Correlation between grade of pearlite spheroidization and laser induced spectra

Laser induced breakdown spectroscopy (LIBS) which is used traditionally as a spectrochemical analytical technique was employed to analyze the grade of pearlite spheroidization. Three 12Cr1MoV steel specimens with different grades of pearlite spheroidization were ablated to produce plasma by pulse laser at 266?nm. In order to determine the optimal temporal condition and plasma parameters for correlating the grade of pearlite spheroidization and laser induced spectra, a set of spectra at different delays were analyzed by the principal component analysis method. Then, the relationship between plasma temperature, intensity ratios of ionic to atomic lines and grade of pearlite spheroidization was studied. The analysis results show that the laser induced spectra of different grades of pearlite spheroidization can be readily identifiable by principal component analysis in the range of 271.941?289.672?nm with 1000?ns delay time. It is also found that a good agreement exists between the Fe ionic to atomic line ratios and the tensile strength, whereas there is no obvious difference in the plasma temperature. Therefore, LIBS may be applied not only as a spectrochemical analytical technique but also as a new way to estimate the grade of pearlite spheroidization.

Estimation of the mechanical properties of steel via LIBS combined with canonical correlation analysis (CCA) and support vector regression (SVR)

Degradation of steel is a significant issue in the field of material aging, with the mechanical properties of steel degrading during service, affecting the safety of equipment. In this work, laser-induced breakdown spectroscopy (LIBS) was applied to investigate the mechanical properties of steel. T91 steel specimens with different degrees of microstructure aging were selected as model samples. Surface hardness was chosen as the key indicator of mechanical properties. The correlation between emission line intensity and hardness was analyzed in order to establish a calibration model of hardness. Multivariate analysis methods (principal component analysis [PCA] and canonical correlation analysis [CCA]) were introduced to identify the important variables from the whole spectrum. Then, two regression algorithms (partial least-squares regression [PLSR] and support vector regression [SVR]) were used to establish the calibration models with the selected variables. The results showed that it is feasible to couple CCA and SVR to estimate hardness, which can effectively identify the correlated variables and establish the correlation between emission lines and hardness, with maximum values for mean relative error (MRE), relative standard deviation (RSD) and root mean square error of prediction (RMSEP) of 2.47%, 2.94% and 6.14, respectively. In addition, the influence of collinearity variables on the established model was investigated in order to show that there is little multicollinearity issue in the calibration models constructed with CCA and SVR according to the values of RMSEP, RSD and MRE. This demonstrates that LIBS technology coupled with chemometrics (CCA and SVR) is an appropriate method to estimate the mechanical properties of steel.