Determination of Carbon Content in Steels Using Laser-Induced Breakdown Spectroscopy Assisted with Laser-Induced Radical Fluorescence

Collinear double-pulse laser-induced breakdown spectroscopy based Cd profiling in the soil

Cadmium (Cd) can migrate in the soil and is readily absorbed by crops. High Cd accumulated in grains poses a huge threat to human health by inhibiting the function of the kidney system. Thus, it is crucial to reveal the content of soil Cd in vertical-depth series using a fast, real-time, and reliable method. For this purpose, laser-induced breakdown spectroscopy (LIBS) combined with multivariate chemometrics was developed to analyze Cd content in the soil with vertical-depth series. Soil samples spiked with different levels of Cd were prepared, and LIBS spectra were obtained by single-pulse LIBS (SP-LIBS) and collinear double-pulse LIBS (CDP-LIBS) with wavelengths of 532 nm and 1064 nm. With appropriate parameters, CDP-LIBS showed better performance in detecting Cd than SP-LIBS. Partial least squares regression (PLSR), genetic algorithm (GA)-optimized back propagation artificial neural network (BP-ANN), and particle swarm optimization (PSO)-optimized least squares-support vector machine (LS-SVM) were tested for quantitative analysis of the spectra after median absolute deviation (MAD), multiple scattering correction (MSC), wavelet transform (WT), spectral averaging, and normalization. PSO-optimized LS-SVM yielded an ideal result, with a coefficient of determination (R², 0.999) and root mean square error (RMSE, 0.359 mg/Kg) in the prediction dataset. Finally, CDP-LIBS coupled with PSO-optimized LS-SVM was employed to analyze soil Cd content in vertical-depth series to reveal the migration pattern of Cd. Our results indicated that soil Cd had a significant positive relationship with the inverse of soil depth. However, Cd was mainly concentrated in 0-20 cm and rarely leached below 45 cm in the soil. This study suggests that LIBS and its enhancement techniques provide a reliable method for revealing the content of soil Cd in vertical-depth series.

Correlation-based carbon determination in steel without explicitly involving carbon-related emission lines in a LIBS spectrum

As any spectrochemical analysis method, laser-induced breakdown spectroscopy (LIBS) usually relates characteristic spectral lines of the elements or molecules to be analyzed to their concentrations in a material. It is however not always possible for a given application scenario, to rely on such lines because of various practical limitations as well as physical perturbations in the spectrum excitation and recording process. This is actually the case for determination of carbon in steel with LIBS operated in the ambient gas, where the intense C I 193.090 nm VUV line is absorbed, while the C I 247.856 nm near UV one heavily interferes with iron lines. This work uses machine learning, especially a combination of least absolute shrinkage and selection operator (LASSO) for spectral feature selection and back-propagation neural networks (BPNN) for regression, to correlate a LIBS spectrum to the carbon concentration for its precise determination without explicitly including carbon-related emission lines in the selected spectral features.

Lead of detection in rhododendron leaves using laser-induced breakdown spectroscopy assisted by laser-induced fluorescence

Laser-induced breakdown spectroscopy assisted by laser-induced fluorescence (LIBS-LIF) was applied to determine lead (Pb) in rhododendron leaves. Rhododendron leaves are essential types of herbal materials. Rapid detection of lead in rhododendron leaves is urgent for drug monitoring. In this paper, the powder method and solid-liquid-solid transformation (SLST) method were employed as sample preparation. The results showed that the signal of the Pb I 405.78 nm line was substantially enhanced. For samples A, B and C, the LoD values of 0.054 mg/kg, 0.059 mg/kg, 0.062 mg/kg were achieved with R² values of 0.997, 0.996, 0.997 via the SLST approach, whose sensitivity and accuracy was slightly higher compared to the powder method. The RMSECV values of both methods were minimal, ranging from 0.538 to 2.117 mg/kg. Lead content detected by LIBS-LIF in the three samples was between 1.5 and 2.8 mg/kg. The results of lead were validated by inductively coupled plasma optical emission spectrometry (ICP-OES). This research provided us with new technology for the rapid and accurate determination of Pb element in rhododendron leaves.

A plasma-image-assisted method for matrix effect correction in laser-induced breakdown spectroscopy

The matrix effect is one of the main bottlenecks for the laser-induced breakdown spectroscopy (LIBS) technique. In this work, image-assisted, laser-induced breakdown spectroscopy (IA-LIBS) based on the Lomakin-Scherbe formula was put forward as a correction to the matrix effect. The brightness and area information in the plasma image was extracted to correct the spectral line intensities among which the brightness information characterizes the plasma temperature, and the area information characterizes the ablative mass. To verify the feasibility of this method, the experiment was conducted on metal samples and pressed samples. The method was applied for quantitative analysis of copper (Cu), magnesium (Mg) in metal samples and chromium (Cr), manganese (Mn) in pressed samples. For the metal samples, after correcting the matrix effect by IA-LIBS, the determination coefficient R squared (R²) of Cu I 510.55 nm and Mg I 518.36 nm calibration curves were increased from 0.726 to 0.942 to 0.992 and 0.988, respectively. The root-mean-square-error of cross-validation (RMSECV) and the average relative error (ARE) decreased by 75.10% and 77.18%, respectively. For the pressed samples, R² of Cr I 520.84 nm and Mn I 403.07 nm calibration curves corrected by IA-LIBS increased from 0.364 to 0.098 to 0.975 and 0.980; and RMSECV and ARE decreased by 77.88% and 83.83%, respectively. The experimental results showed that IA-LIBS had an obvious improvement on elimination of the matrix effect for the different samples and the different elements. Therefore, IA-LIBS will become a promising technology and will greatly promote the development of LIBS in various fields.

Determination of trace heavy metal elements in aqueous solution using surface-enhanced laser-induced breakdown spectroscopy

Heavy metal pollution is one of the main problems in water pollution, which is harmful to humans. Surface-enhanced laser-induced breakdown spectroscopy (SENLIBS) has been applied to detect trace amounts of heavy metal elements in aqueous solution; however, it is still a big challenge to explore the relationship between the LIBS detection sensitivity and the substrate's physical properties. In this work, four typical substrates, zinc (Zn), magnesium alloy (Mg), nickel (Ni), and silicon (Si), were compared; and the mechanism of spectral enhancement by different substrates in SENLIBS was investigated. The results indicated that the limit of detection (LoD) of heavy metal elements on different substrates is positively proportional to the boiling of the substrate. That is mainly because a higher plasma excitation temperature and electron density are obtained, leading to more intense collision between particles. The signal enhancement is associated with the lower boiling point of the substrate (corresponding to a lower ablation threshold and higher ablation quantity from the substrate). As a result, the best LoD was 0.0011 mg/L for chromium (Cr) and 0.004 mg/L for lead (Pb) on an optimal Zn substrate, respectively. The LoDs were sufficiently low to meet the drinking water sanitation standard. These results showed that the detection sensitivity of heavy metal elements in aqueous solution can be improved by choosing a substrate with a lower boiling point in SENLIBS.

Experimental investigation of laser-induced breakdown spectroscopy assisted with laser-induced fluorescence for trace aluminum detection in steatite ceramics

Laser-induced breakdown spectroscopy (LIBS) assisted with laser-induced fluorescence (LIF) was introduced to detect trace aluminum in steatite ceramics in this work. The mechanism and transition process of laser-induced aluminum atomic fluorescence in laser-induced plasma was described and discussed. Selective enhancement of LIF and temporal synchronicity between radiation laser and fluorescence were studied. The influences of ablation laser energy, power density of the radiation laser, and interpulse delay were experimentally investigated. The results showed that 60 mJ in ablation laser energy and 4 μs in interpulse delay were the optimal choice for fluorescent intensity. The fluorescence was increased to the saturation level over 4  MW/cm². Spectral stability improvement of LIBS-LIF was also discovered in this work. The results proved that LIBS-LIF is a feasible and effective modification of LIBS for ceramics analysis.

Isotopic determination with molecular emission using laser-induced breakdown spectroscopy and laser-induced radical fluorescence

Molecular emission can be used for isotopic analysis in laser-induced breakdown spectroscopy (LIBS) due to its large isotopic shift. However, spectral weakness and interference have become the main flaws in molecular isotopic analysis, causing deterioration of quantitative accuracy and sensitivity. Here, to overcome these problems, laser-induced radical fluorescence (LIRF) was applied to enhance the molecular spectra and eliminate the spectral interference. The root mean square errors of cross validation (RMSECVs) of boron and carbon isotopes (¹¹BO, ¹⁰BO, ¹²CN, and ¹³CN) improved to 2.632, 5.721, 5.990, and 1.543 at.%, as compared with 16.96, 35.79, 57.10, and 13.89 at.%, respectively, obtained in the case without LIRF. The limits of detection (LoDs) of ¹¹BO, ¹⁰BO, ¹²CN, and ¹³CN were 0.9858, 0.8470, 1.606, and 1.193 at.%, respectively. This work demonstrates the feasibility of LIBS-LIRF to achieve isotopic determination with high accuracy and sensitivity.

High-sensitivity determination of cadmium and lead in rice using laser-induced breakdown spectroscopy

Stability and sensitivity of toxic elements determination is still unsatisfactory in agricultural product using laser-induced breakdown spectroscopy (LIBS). A simple and low cost sample pretreatment method named solid-liquid-solid transformation method was proposed in this work. The target analytes of cadmium (Cd) and lead (Pb) from rice samples were prepared through ultrasound assisted extraction in hydrochloric acid solution. The solution was dropped on the glass slide after centrifuging process and was further dried on a heater. Finally, the glass slide contained the analytes was carried out for LIBS determination. Compare with conventional pellet method, the spectral intensity of Cd and Pb element were enhanced significantly using LIBS. The limits of detection were 2.8 and 43.7 μg/kg, respectively. The limits of quantification were 9.3 and 145.7 μg/kg, respectively. The results demonstrated that LIBS coupled with ultrasound assisted extraction should be a promising tool to detect toxic elements in rice.

Determination of boron with molecular emission using laser-induced breakdown spectroscopy combined with laser-induced radical fluorescence

Boron is an essential element for industry, but it is hard to accurately and rapidly determine high boron content with conventional laser-induced breakdown spectroscopy (LIBS), due to the matrix and self-absorption effect. Using molecular emission is an alternative method for boron content analysis, but its weak spectra are major challenges. Here, boron monoxide (BO) radicals were used to establish calibration assisted by LIBS and laser-induced radical fluorescence (LIBS-LIRF). Two types of BO radical excitations, vibrational ground state excitation (LIRFG) and vibrational excited state excitation (LIRFE), were compared. The results showed that LIRFG achieved better sensitivity with a limit of detection of 0.0993 wt.%, while the LIRFE was more accurate with a root mean square error of cross validation of 0.2514 wt.%. In conclusion, this work provided a potential approach for molecular emission analysis with LIBS-LIRF.