A comprehensive assessment of soils was developed using laser induced breakdown spectroscopy (LIBS) coupled with univariate and multivariate regression methods.
The major application of the laser-induced breakdown spectroscopy (LIBS) technique had been in the analysis of solid samples because the measurement of LIBS for liquid samples experiences some experimental difficulties, such as splashing, a quenching effect, and a shorter plasma lifetime. In the present work, electrospun ultrafine fibers were explored and used for the first time as a solid-phase support to quantify chromium (Cr) and copper (Cu) in aqueous solutions by LIBS. The liquid sample was first transferred to an ultrafine fiber surface, which could minimize the drawbacks of liquid sample analysis with LIBS. Due to the special micro-porous structure, the electrospun ultrafine fibers could hold a larger liquid sample and also the liquid sample was easy to evaporate. On the other hand, as a polymer substrate, the porous electrospun ultrafine fibers contributed to the minimal blank since there was no other unwanted heavy metal matrix that affected the detection during the liquid LIBS analysis.Meanwhile, the large sampling spot to fiber diameter ratio will minimize the potential influence generated in the liquid sample distribution process. With this pre-treated sample technique, the sensitivities of LIBS for liquid samples are improved considerably and the detection limits for Cr and Cu reached 1.8 ppm and 1.9 ppm, respectively. Therefore, the present strategy definitely paves the way for a wider application of LIBS in liquid sample analysis.
Laser Induced Breakdown Spectroscopy (LIBS) is attracting more and more attention in geology fields for its unique adventages of on-line and in-situ analysis and the portable even handheld instruments due to the development of laser source and mini-spectrometers. However, parameters such as accuracy and precision of the instrument is still essential for field application.In this paper, two algorithm to determine the concentrations of five main elements (Si, Ca, Mg, Fe and Al) in sedimentary rock samples are proposed based on support vector regression (SVR) and partial least squares regression (PLSR). The proposed comparison demonstrates that the SVR model performed better with more satisfied accuracy and precision under the optimized conditions.For SVR quantitative analysis, the spectral features (20 lines) without principal component analysis (PCA) were selected as input variables. The optimized penalty parameter C and the key parameter of radial basis function (RBF)-σ obtained by genetic algorithmare (GA) were 4.63 and 0.9159, respectively. As well, The best number of the best principal components of PLSR was 2 optimized to be 8 by 10-fold cross-validation(CV) testing. Furthermor, the accuracy corresponding to the average relative standard deviations (RSDs) and the precision related to the root mean square error (RMSE) were calculated according to the two regression models performance. A significant enhancement of accuracy up to 43.50 times and the precision of 7.19 times for SVR model was obtained, which can eliminate the self-absorbtion of plasma efficiently compared with linear machine learning method PLSR. In conclusion, the chemometric method of SVR with better accuracy and precision can be successfully applied for quantitative analysis of complex geological samples using LIBS technique.
In this paper, a nano-channel material was combined with laser induced breakdown spectroscopy (LIBS) to achieve sensitive and quick detection of metal ions in liquid samples. A 3D anodic aluminum oxide porous membrane (AAOPM) was selected as a novel substrate for the first time, which showed excellent potential for liquid analysis. It is worth mentioning that the LIBS signal of the target elements in aqueous solution dropped on the 3D AAOPM was increased by up to 19 times in comparison with that on the tablet sample made of aluminium oxide powder. The attractive results are mainly attributed to the peculiar structure of the 3D AAOPM. Firstly, an abundant strong coordination metal-oxygen bond between hydroxyl groups and metal ions existed on the surface of the novel substrate. Secondly, the extremely high aspect ratio of the 3D AAOPM could supply a much larger contact area between the matrix and analytes. Thirdly, the special nano-channel distribution could make efficient coupling of a laser beam with the materials. Finally, the sample pervasion and volatilization could be finished within a very short time because of the micrometer level thickness and porosity of the 3D AAOPM. The calibration curves with linearity ranges (1-100 mg mL À1 ) and good linearity (R squared better than 0.983 for all of the four target elements) were established, and the limits of detection (LODs) obtained were 0.18 mg mL À1 , 0.12 mg mL À1 , 0.081 mg mL À1 , and 0.11 mg mL À1 for Cu 2+ , Ag + , Pb 2+ , and Cr 3+ , respectively. In real sample analyses, the recoveries of three elements at different concentration levels were all in the range of 92.5-107.4%, with the relative standard deviations of parallel samples around 10.0%. This novel method showed a fast, simple and super sensitive monitoring tool for liquid sample analysis compared with the traditional LIBS method.
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