Highly sensitive detection of sodium in aqueous solutions using laser-induced breakdown spectroscopy with liquid sheet jets

Chromium in soil detection using adaptive weighted normalization and linear weighted network framework for LIBS matrix effect reduction

Rapid and accurate detection of agricultural soil chromium (Cr) is of great significance for soil pollution assessment. Laser-induced breakdown spectroscopy (LIBS) could serve as a rapid and chemical-free method for hazardous metal analysis compared with conventional chemical methods. However, the detection of LIBS is interfered by uncertainty and matrix effect. In this study, an average strategy combined with linear weighted network (LWNet) was proposed to reduce the uncertainty. Adaptive weighted normalization-LWNet (AWN-LWNet) framework was proposed to reduce the matrix effect in two soil types. The results indicated that LWNet outperformed traditional machine learning and achieved the average relative error (ARE) of 2.08 % and 3.03 % for yellow brown soil and lateritic red soil, respectively. Moreover, LWNet could effectively mine Cr feature peaks even under the low spectral resolution. AWN-LWNet was the optimal model compared with commonly used models to reduce matrix effect (ARE=4.12 %). Besides, AWN-LWNet greatly reduced the number (from 22016 to 72) of spectral variables for model input. By extracting Cr peaks from models, the difference of Cr peaks intensity could be intuitively observed, which served as spectral interpretation for matrix effect reduction. The two methods have the potential to realize the detection of hazardous metals in soil by LIBS.

LIBS assisted PCA analysis of multiple rare-earth elements (La, Ce, Nd, Sm, and Yb) in phosphorite deposits

In the present study, the immediate detection of rare-earth elements (REEs) in phosphorite deposits has been reported using laser-induced breakdown spectroscopy (LIBS). Numerous emission lines corresponding to the REEs such as lanthanum (La), cerium (Ce), neodymium (Nd), samarium (Sm), and ytterbium (Yb), have been detected in the emission spectra of phosphorite-induced plasma plume. For the quantitative analysis, we employed the calibration-free LIBS (CF-LIBS), and Energy Dispersive X-ray (EDX) spectroscopy techniques. The results obtained using the CF-LIBS technique show excellent agreement with that obtained by EDX. Besides principal component analysis (PCA) was employed by incorporating the LIBS spectral data of rare earth phosphorite rocks samples containing La, Ce, Nd, Sm, and Yb emission lines. The first three PCs were observed using LIBS spectral data set showing a covariance (interpretation rate) up to 76.3%. This study suggests that LIBS yields a quick and very reliable qualitative and quantitative analysis of REEs in any geological ore sample.