Laser-Induced Breakdown Spectroscopy of Liquids: Aqueous Solutions of Nickel and Chlorinated Hydrocarbons

1998 ◽  
Vol 52 (3) ◽  
pp. 438-443 ◽  
Author(s):  
Leonard M. Berman ◽  
Paul J. Wolf

Spectrochemical analyses of aqueous solutions containing nickel or the chlorinated hydrocarbons (CHCs) C2Cl4, CCl4, CHCl3, and C2HCl3 were performed with the use of laser-induced breakdown spectroscopy. A Nd:YAG laser operating at 60 mJ/pulse was focused onto the surface of the liquid. Elemental line intensities were monitored in the laser-produced plume as a function of analyte concentration to determine detection limits. The limits of detection for nickel in water were 36.4 ± 5.4 mgAL and 18.0 ± 3.8 mg/L for laser irradiation at 1.06 μm and 355 nm, respectively. Ablation of pure CHCs at 355 nm produced extremely intense plasma emissions that primarily consisted of spectroscopic features attributed to CN, C3, H, N, and Cl. The spectra were structurally identical for all the CHCs except for differences in the intensities of various emission lines. With the use of emission from neutral atomic chlorine as an identifier for CHC contamination of water, no detectable traces of these elements were observed in saturated aqueous solutions. The detection limits for the CHCs were well above the saturation limits of CHC in water.

Atoms ◽  
2019 ◽  
Vol 7 (3) ◽  
pp. 84 ◽  
Author(s):  
Ashwin P. Rao ◽  
Matthew T. Cook ◽  
Howard L. Hall ◽  
Michael B. Shattan

A hand-held laser-induced breakdown spectroscopy device was used to acquire spectral emission data from laser-induced plasmas created on the surface of cerium-gallium alloy samples with Ga concentrations ranging from 0–3 weight percent. Ionic and neutral emission lines of the two constituent elements were then extracted and used to generate calibration curves relating the emission line intensity ratios to the gallium concentration of the alloy. The Ga I 287.4-nm emission line was determined to be superior for the purposes of Ga detection and concentration determination. A limit of detection below 0.25% was achieved using a multivariate regression model of the Ga I 287.4-nm line ratio versus two separate Ce II emission lines. This LOD is considered a conservative estimation of the technique’s capability given the type of the calibration samples available and the low power (5 mJ per 1-ns pulse) and resolving power ( λ / Δ λ = 4000) of this hand-held device. Nonetheless, the utility of the technique is demonstrated via a detailed mapping analysis of the surface Ga distribution of a Ce-Ga sample, which reveals significant heterogeneity resulting from the sample production process.


2019 ◽  
Vol 74 (1) ◽  
pp. 42-54 ◽  
Author(s):  
Daniel Diaz ◽  
Alejandro Molina ◽  
David W. Hahn

Laser-induced breakdown spectroscopy (LIBS) and principal component analysis (PCA) were applied to the classification of LIBS spectra from gold ores prepared as pressed pellets from pulverized bulk samples. For each sample, 5000 single-shot LIBS spectra were obtained. Although the gold concentrations in the samples were as high as 7.7 µg/g, Au emission lines were not observed in most single-shot LIBS spectra, rendering the application of the usual ensemble-averaging approach for spectral processing to be infeasible. Instead, a PCA approach was utilized to analyze the collection of single-shot LIBS spectra. Two spectral ranges of 21 nm and 0.15 nm wide were considered, and LIBS variables (i.e., wavelengths) reduced to no more than three principal components. Single-shot spectra containing Au emission lines (positive spectra) were discriminated by PCA from those without the spectral feature (negative spectra) in a spectral range of less than 1 nm wide around the Au(I) 267.59 nm emission line. Assuming a discrete gold distribution at very low concentration, LIBS sampling of gold particles seemed unlikely; therefore, positive spectra were considered as data outliers. Detection of data outliers was possible using two PCA statistical parameters, i.e., sample residual and Mahalanobis distance. Results from such a classification were compared with a standard database created with positive spectra identified with a filtering algorithm that rejected spectra with an Au intensity below the smallest detectable analytical LIBS signal (i.e., below the LIBS limit of detection). The PCA approach successfully identified 100% of the data outliers when compared with the standard database. False identifications in the multivariate approach were attributed to variations in shot-to-shot intensity and the presence of interfering emission lines.


2007 ◽  
Vol 61 (2) ◽  
pp. 171-176 ◽  
Author(s):  
Marion Lawrence-Snyder ◽  
Jon Scaffidi ◽  
S. Michael Angel ◽  
Anna P. M. Michel ◽  
Alan D. Chave

Author(s):  
Qiuyun Wang ◽  
Ting Ge ◽  
Yitong Liu ◽  
Luyun Jiang ◽  
Anmin Chen ◽  
...  

By combining surface-enhanced and discharge-assisted laser-induced breakdown spectroscopy (LIBS), the study successfully realized the quantitative analysis of trace heavy metal Cr, Cu, and Pb in aqueous solutions. We used an...


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