Laser-Induced Breakdown Spectroscopy and Plasma Characterization Generated by Long-Pulse Laser on Soil Samples

2017 ◽  
Vol 84 (1) ◽  
pp. 35-39 ◽  
Author(s):  
S. Xu ◽  
W. Duan ◽  
R. Ning ◽  
Q. Li ◽  
R. Jiang
Keyword(s):  
Pulse Laser ◽  
Soil Samples ◽  
Laser Induced Breakdown Spectroscopy ◽  
Breakdown Spectroscopy ◽  
Laser Induced Breakdown ◽  
Plasma Characterization ◽  
Long Pulse

Simultaneous detection of a submerged Cu target and bulk water by long-pulse laser-induced breakdown spectroscopy

2021 ◽  
Author(s):  
Nan Li ◽  
Kota Tanabe ◽  
Naoya Nishi ◽  
Ronger Zheng ◽  
Tetsuo Sakka
Keyword(s):  
Pulse Laser ◽  
Simultaneous Detection ◽  
Bulk Water ◽  
Simultaneous Analysis ◽  
Laser Induced Breakdown Spectroscopy ◽  
Detection Capability ◽  
Breakdown Spectroscopy ◽  
Laser Induced Breakdown ◽  
Long Pulse

The detection capability of long-pulse laser-induced breakdown spectroscopy (LIBS) for simultaneous analysis of submerged solids and bulk water has been investigated with a Cu target immersed in a CaCl2 solution....

Signal enhancement in underwater long-pulse laser-induced breakdown spectroscopy for the analysis of bulk water

2021 ◽  
Author(s):  
Nan Li ◽  
Naoya Nishi ◽  
Ronger Zheng ◽  
Tetsuo Sakka
Keyword(s):  
Pulse Laser ◽  
Bulk Water ◽  
Signal Enhancement ◽  
Laser Induced Breakdown Spectroscopy ◽  
Breakdown Spectroscopy ◽  
Laser Induced Breakdown ◽  
Underwater Laser ◽  
Long Pulse

Significant signal enhancement in underwater laser-induced breakdown spectroscopy for the analysis of bulk water by using a long ns pulse.

Improved Analysis of Manganese in Steel Samples Using Collinear Long–Short Double Pulse Laser-Induced Breakdown Spectroscopy (LIBS)

2018 ◽  
Vol 73 (2) ◽  
pp. 152-162 ◽  
Author(s):  
Minchao Cui ◽  
Yoshihiro Deguchi ◽  
Zhenzhen Wang ◽  
Seiya Tanaka ◽  
Yuki Fujita ◽  
...  
Keyword(s):  
Pulse Laser ◽  
Double Pulse ◽  
Analytical Performance ◽  
Laser Induced Breakdown Spectroscopy ◽  
Detection Ability ◽  
Breakdown Spectroscopy ◽  
Measurement Results ◽  
Laser Induced Breakdown ◽  
Long Pulse ◽  
Double Pulse Laser

A long–short double pulse laser-induced breakdown spectroscopy (long–short DP-LIBS) method was employed to improve the analytical performance of LIBS for the measurement of manganese in steel samples. The long pulse with a duration of 60 μs was generated using a neodymium-doped yttrium aluminum garnet (Nd:YAG) laser which was operated at free-running (FR) mode. To investigate the detection ability without sample preparation, the steel washers were tested using single-pulse LIBS (SP-LIBS) and long–short DP-LIBS, respectively. The measurement results show that long–short DP-LIBS was able to record clear spectra from the steel washers with a surface layer. Through the observation on the laser craters with a scanning electron microscope (SEM), the results suggest that the improvement in detection ability can be attributed to the pre-irradiation effect of long-pulse laser beam. Next, the analytical performance for quantitative measurement of manganese was evaluated employing ten standard steel samples. The results show that the linearity fit (R2) of the calibration curve is 0.988 for long–short DP-LIBS, whereas, R2 is only 0.810 for SP-LIBS under the same measurement conditions. The repeated measurement results show that the average relative standard deviation (RSD) of the tested samples is 29.3% for SP-LIBS and is 10.5% for long–short DP-LIBS. The prediction results also show that the average relative error of prediction (REP) is 94.9% for SP-LIBS and is 4.9% for long–short DP-LIBS.

Deep Learning Associated with Laser-Induced Breakdown Spectroscopy (LIBS) for the Prediction of Lead in Soil

2019 ◽  
Vol 73 (5) ◽  
pp. 565-573 ◽  
Author(s):  
Yun Zhao ◽  
Mahamed Lamine Guindo ◽  
Xing Xu ◽  
Miao Sun ◽  
Jiyu Peng ◽  
...  
Keyword(s):  
Deep Learning ◽  
Confusion Matrix ◽  
Principal Component ◽  
Classification Performance ◽  
Soil Samples ◽  
Laser Induced Breakdown Spectroscopy ◽  
Support Vector ◽  
Breakdown Spectroscopy ◽  
Laser Induced Breakdown ◽  
Different Levels

In this study, a method based on laser-induced breakdown spectroscopy (LIBS) was developed to detect soil contaminated with Pb. Different levels of Pb were added to soil samples in which tobacco was planted over a period of two to four weeks. Principal component analysis and deep learning with a deep belief network (DBN) were implemented to classify the LIBS data. The robustness of the method was verified through a comparison with the results of a support vector machine and partial least squares discriminant analysis. A confusion matrix of the different algorithms shows that the DBN achieved satisfactory classification performance on all samples of contaminated soil. In terms of classification, the proposed method performed better on samples contaminated for four weeks than on those contaminated for two weeks. The results show that LIBS can be used with deep learning for the detection of heavy metals in soil.

High-resolution three-dimensional compositional imaging by double-pulse laser-induced breakdown spectroscopy

2016 ◽  
Vol 11 (08) ◽  
pp. C08002-C08002 ◽  
Author(s):  
C. Schiavo ◽  
L. Menichetti ◽  
E. Grifoni ◽  
S. Legnaioli ◽  
G. Lorenzetti ◽  
...  
Keyword(s):  
High Resolution ◽  
Pulse Laser ◽  
Three Dimensional ◽  
Double Pulse ◽  
Laser Induced Breakdown Spectroscopy ◽  
Breakdown Spectroscopy ◽  
Laser Induced Breakdown ◽  
Double Pulse Laser

Double pulse laser induced breakdown spectroscopy with Gaussian and multimode beams

2016 ◽  
Vol 124 ◽  
pp. 47-55 ◽  
Author(s):  
V.N. Lednev ◽  
S.M. Pershin ◽  
A.F. Bunkin ◽  
A.A. Samokhvalov ◽  
V.P. Veiko ◽  
...  
Keyword(s):  
Pulse Laser ◽  
Double Pulse ◽  
Laser Induced Breakdown Spectroscopy ◽  
Breakdown Spectroscopy ◽  
Laser Induced Breakdown ◽  
Multimode Beams ◽  
Double Pulse Laser
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