Xinyan Yang

Determination of cobalt in low-alloy steels using laser-induced breakdown spectroscopy combined with laser-induced fluorescence

Cobalt element plays an important role for the properties of magnetism and thermology in steels. In this work, laser-induced breakdown spectroscopy combined with laser-induced fluorescence (LIBS-LIF) was studied to selectively enhance the intensities of Co lines. Two states of Co atoms were resonantly excited by a wavelength-tunable laser. LIBS-LIF with ground-state atom excitation (LIBS-LIFG) and LIBS-LIF with excited-state atom excitation (LIBS-LIFE) were compared. The results show that LIBS-LIFG has analytical performance with LoD of 0.82μg/g, R(2) of 0.982, RMSECV of 86μg/g, and RE of 9.27%, which are much better than conventional LIBS and LIBS-LIFE. This work provided LIBS-LIFG as a capable approach for determining trace Co element in the steel industry.

Acidity measurement of iron ore powders using laser-induced breakdown spectroscopy with partial least squares regression

Laser-induced breakdown spectroscopy (LIBS) with partial least squares regression (PLSR) has been applied to measuring the acidity of iron ore, which can be defined by the concentrations of oxides: CaO, MgO, Al₂O₃, and SiO₂. With the conventional internal standard calibration, it is difficult to establish the calibration curves of CaO, MgO, Al₂O₃, and SiO₂ in iron ore due to the serious matrix effects. PLSR is effective to address this problem due to its excellent performance in compensating the matrix effects. In this work, fifty samples were used to construct the PLSR calibration models for the above-mentioned oxides. These calibration models were validated by the 10-fold cross-validation method with the minimum root-mean-square errors (RMSE). Another ten samples were used as a test set. The acidities were calculated according to the estimated concentrations of CaO, MgO, Al₂O₃, and SiO₂ using the PLSR models. The average relative error (ARE) and RMSE of the acidity achieved 3.65% and 0.0048, respectively, for the test samples.

Background removal in soil analysis using laser- induced breakdown spectroscopy combined with standard addition method

The matrix effect of powder samples, especially for soil samples, is significant in laser-induced breakdown spectroscopy (LIBS), which affects the prediction accuracy of the element concentration. In order to reduce this effect of the soil samples in LIBS, the standard addition method (SAM) based on background removal by wavelet transform algorithm was investigated in this work. Five different kinds of certified reference soil samples (lead (Pb) concentrations were 110, 283, 552, 675, and 1141 ppm, respectively) were used to examine the accuracy of this method. The root mean square error of prediction (RMSEP) was more than 303 ppm by using the conventional calibration method. After adoption of SAM with background removal by wavelet transform algorithm, the RMSEP was reduced to 25.7 ppm. Therefore, the accuracy of the Pb element was improved significantly. The mechanism of background removal by wavelet transform algorithm based on SAM is discussed. Further study demonstrated that this method can also improve the predicted accuracy of the Cd element.

Sensitive determinations of Cu, Pb, Cd, and Cr elements in aqueous solutions using chemical replacement combined with surface-enhanced laser-induced breakdown spectroscopy.

In this study, chemical replacement combined with surface-enhanced laser-induced breakdown spectroscopy (CR-SENLIBS) was for the first time applied to improve the detection sensitivities of trace heavy metal elements in aqueous solutions. Utilizing chemical replacement effect, heavy metal ions in aqueous solution were enriched on the magnesium alloy surface as a solid replacement layer through reacting with the high chemical activity metallic magnesium (Mg) within 1 minute. Unitary and mixed solutions with Cu, Pb, Cd, and Cr elements were prepared to construct calibration curves, respectively. The CR-SENLIBS showed a much better detection sensitivity and accuracy for both unitary and mixed solutions. The coefficients of determination R2 of the calibration curves were above 0.96, and the LoDs were of the same order of magnitude, i.e., in the range of 0.016-0.386 μg/mL for the unitary solution, and in the range of 0.025-0.420 μg/mL for the mixed solution. These results show that CR-SENLIBS is a feasible method for improving the detection sensitivity of trace element in liquid sample, which definitely provides a way for wider application of LIBS in water quality monitoring.

Spectral Interference Elimination in Soil Analysis Using Laser-Induced Breakdown Spectroscopy Assisted by Laser-Induced Fluorescence

The complex and serious spectral interference makes it difficult to detect trace elements in soil using laser-induced breakdown spectroscopy (LIBS). To address it, LIBS-assisted by laser-induced fluorescence (LIBS-LIF) was applied to selectively enhance the spectral intensities of the interfered lines. Utilizing this selective enhancement effect, all the interference lines could be eliminated. As an example, the Pb I 405.78 nm line was enhanced selectively. The results showed that the determination coefficient (R2) of calibration curve (Pb concentration range = 14-94 ppm), the relative standard deviation (RSD) of spectral intensities, and the limit of detection (LOD) for Pb element were improved from 0.6235 to 0.9802, 10.18% to 4.77%, and 24 ppm to 0.6 ppm using LIBS-LIF, respectively. These demonstrate that LIBS-LIF can eliminate spectral interference effectively and improve the ability of LIBS to detect trace heavy metals in soil.

Investigation of the self-absorption effect using spatially resolved laser-induced breakdown spectroscopy

The self-absorption effect will seriously influence the accuracy of quantitative analyses using laser-induced breakdown spectroscopy (LIBS). To reduce the self-absorption effect, elements Na and K (major elements) and Pb and Cu (minor elements) in soil plasmas have been studied by spatially resolved LIBS (SRLIBS). The 2-dimensional distributions of line intensities and self-absorption coefficients of lines in the plasmas were investigated and the influence parameters of the self-absorption effect were also studied. Results have shown that the self-absorption effect could be reduced greatly and the accuracy of quantitative LIBS could be improved obviously by selecting the collecting zones of the plasmas carefully. Meanwhile, a high laser energy and a short delay time could be useful to expand the region which is influenced slightly by the self-absorption effect.

Quantitative analyses of Mn, V, and Si elements in steels using a portable laser-induced breakdown spectroscopy system based on a fiber laser

A portable laser-induced breakdown spectroscopy (LIBS) system based on a fiber laser was developed and employed to quantitatively analyze manganese (Mn), vanadium (V), and silicon (Si) elements in steels. After background removal, the coefficients of determination (R2 factors) of the calibration curves for Mn, V, and Si elements reached 0.997, 0.991 and 0.992, respectively, obvious improvements compared to those of the original spectra. The leave-one-out cross-validation (LOOCV) method was used to test the system. The root-mean-square error of cross-validation (RMSECV) for Mn (0.072–2.06 wt%), V (0.009–0.821 wt%), and Si (0.099–1.85 wt%) elements were 0.037, 0.041 and 0.079 wt%, respectively. The average relative errors (AREs) for Mn elements reached 7.6%. These results are comparable with those of the conventional LIBS which refers to utilizing the traditional flash-lamp-pumped laser as a laser source. However, compared to conventional LIBS, a fiber laser LIBS (FL-LIBS) is more compact, robust, and cost effective. The FL-LIBS, coupling a compact fiber laser and spectrometer, is a convenient approach to providing a portable solution for real-time and in situ detection in industry, especially in harsh environments.

Wavelet-based interference correction for laser-induced breakdown spectroscopy

To minimize the impact of spectral interference on laser-induced breakdown spectroscopy (LIBS) quantitative analyses, an algorithm based on wavelet transform was developed for simultaneous correction of spectral interference and continuum background. The root-mean-square error of calibration (RMSEC) of the univariate regression model for the element of interest was applied to determine the wavelet function, decomposition level, and scaling factor α. When the interference-free analytical lines of the elements of interest cannot be directly obtained from the measured spectra, they can be extracted from the spectra with the developed method for quantitative analysis. This method was applied for LIBS analyses of chromium (Cr), silicon (Si), titanium (Ti), and manganese (Mn) with continuum backgrounds and spectral interference in low alloy steel samples. The root-mean-square errors of cross-validation (RMSECV) of elements Cr, Si, Ti, and Mn were 0.0295, 0.0140, 0.0183, and 0.0558 wt%, respectively. The results demonstrated that the developed algorithm contributed to accuracy improvement for LIBS quantitative analyses with the presence of spectral interference.

On-stream analysis of iron ore slurry using laser-induced breakdown spectroscopy

On-stream analysis of the element content in ore slurry has important significance in the control of the flotation process and full use of raw materials. Therefore, techniques that can monitor the chemistry in slurries online are required. Laser-induced breakdown spectroscopy (LIBS) is one of the potential approaches to online measurements due to its capability of in situ and real-time analysis. However, using LIBS for on-stream analysis of slurries is challenging due to the issues such as surface ripples, sample splashing, sedimentation, etc. To address these problems, we developed a slurry circulation system. The effects of slurry flow rate on LIBS spectra were investigated to achieve the optimal detecting surface for better repeatability of LIBS. The coefficient of determination R2 of the calibration curve for Fe element is 0.982, and the limit of detection of Fe element was estimated to be 0.075 wt. % under the optimized experimental parameters. The results show that this slurry circulation system is applicable to the on-stream slurry analysis.

Quantitative analysis of steel samples using laser-induced breakdown spectroscopy with an artificial neural network incorporating a genetic algorithm

In this work, a genetic algorithm (GA) was employed to select the intensity ratios of the spectral lines belonging to the target and domain matrix elements, then these selected line-intensity ratios were taken as inputs to construct an analysis model based on an artificial neural network (ANN) to analyze the elements copper (Cu) and vanadium (V) in steel samples. The results revealed that the root mean square errors of prediction (RMSEPs) for the elements Cu and V can reach 0.0040 wt. % and 0.0039 wt. %, respectively. Compared to 0.0190 wt. % and 0.0201 wt. % of the conventional internal calibration approach, the reduction rates of the RMSEP values reached 78.9% and 80.6%, respectively. These results indicate that the GA combining ANN can excellently execute the quantitative analysis in laser-induced breakdown spectroscopy for steel samples and further improve analytical accuracy.