Accuracy enhancement of laser induced breakdown spectra using permittivity and size optimized plasma confinement rings

Optimizing analysis of coal property using laser-induced breakdown and near-infrared reflectance spectroscopies

Coal properties have different correlations with elements or molecules. It is difficult to optimize the analysis of multiple coal properties simultaneously by a single analytical technique. This paper reports a method for optimizing analysis of coal properties by using laser-induced breakdown spectroscopy (LIBS) and near-infrared reflectance spectroscopy (NIRS). Briefly, LIBS, NIRS, as well as spectral information fusion of LIBS and NIRS (LIBS&NIRS) were used to establish the quantitative analysis models of coal properties with partial least squares (PLS) method. The performance of models based on different spectral information was compared with each other according to the determination coefficient (R²), root mean square error of prediction (RMSEP), average absolute error (AAE), and average relative error (ARE). As a result, the models of calorific value and volatile matter based on LIBS&NIRS have the best performance with minimum root mean square error for prediction (RMSEP) of 0.192 MJ/kg and 0.672%. However, for the model of ash content, the minimum RMSEP of 0.774% was achieved by using LIBS. Meanwhile, optimal performance of modeling moisture content was obtained from NIRS with the minimum RMSEP of 0.308%. After obtaining the best prediction results of volatile matter content, ash content, and moisture content, the fixed carbon content can be calculated by the definition formula. These results demonstrated that the reported method can optimize the rapid analysis of multiple coal properties simultaneously.

Lithium ion detection in liquid with low detection limit by laser-induced breakdown spectroscopy

Lithium (Li), as the lightest metal and the most important powerful material in battery fabrication, is widely used in many fields. The fast detection of Li is necessary for industrial application. The slow-speed detection methods, including atomic absorption spectroscopy and inductively coupled plasma mass spectroscopy with high accuracy and low limit of detection, are hard to utilize in in situ industrial control due to complex prepreparation of samples. Here, through the analysis of the typical spectrum line at Li I 670.79 nm, Li ions in water were detected quantitatively in 1 min, including sample preparation by laser-induced breakdown spectroscopy (LIBS) with filter paper as the adsorption substrate. The calibration curve by polynomial function fitting is used to predict the Li⁺ concentration. The limit of detection (LOD) as low as 18.4 ppb is obtained, which is much lower than the results ever reported by using filter paper. The related factor R² reaches 99%, and the prediction error is lower than 2%, proving the fast and online monitor for Li⁺ by LIBS is feasible. Furthermore, by comparison with the results with filter paper enrichment, the Li⁺ detection from water directly shows higher LOD to 10.5 ppm. Moreover, the plasma images, by gate-controlled intensified charge-coupled device, illustrate a different morphology and evolution between that on water surface and filter paper surface through visual observation. This study provides experimental and theoretical experience in a fast way for the quantitative detection of the lightest metal ion (Li⁺) in liquid.

Accuracy enhancement of laser induced breakdown spectroscopy by safely low-power discharge

Improvement in detection accuracy is an important and hot topic for laser induced breakdown spectroscopy (LIBS). Discharged-pulse assisted (DPA) plasma has been investigated as an effective way to enhance analytical capabilities and accuracy of LIBS. Most of reported DPA experiments have been performed using high voltage and power to comprehend spectrum enhancement. For safety concerns and maneuverability of LIBS equipment; low power and small current discharge are viable for industrial application. In this paper, the enhanced spectra with many extra peaks and higher line intensities were also detected, realized by a low-power discharge assisted LIBS (Max. 2.8 kV and ~1 mA), which are much lower than reported in literature ~MW discharge. The number of atomic peaks of the sample increases, on the other hand, and gradual peaks become stronger with the increase of discharged HV from 1 kV to 1.5 kV, 1.75 kV, 2 kV, 2.5 kV and 2.8 kV. The discharge current increases from 0.2 mA to 1.5 mA, which is almost threshold discharge voltage. After processing, the original spectra, including the peak shift and peak correction by statistics and physics, resulted in achievement of better line stability in terms of relative standard deviation (RSD) of ash, carbon, and volatile coal samples with root mean square error prediction (RMSEP) of 0.4864, 0.3682, 0.3374 and the linear regression coefficient R² = 0.99, 0.99,0.98, respectively. The result proposes a promising method to improve detection accuracy of LIBS with simple setup, high safety and low-cost.