scholarly journals Qualitative tissue differentiation by analysing the intensity ratios of atomic emission lines using laser induced breakdown spectroscopy (LIBS): prospects for a feedback mechanism for surgical laser systems

2013 ◽  
Vol 8 (1-2) ◽  
pp. 153-161 ◽  
Author(s):  
Rajesh Kanawade ◽  
Fanuel Mahari ◽  
Florian Klämpfl ◽  
Maximilian Rohde ◽  
Christian Knipfer ◽  
...  
2007 ◽  
Vol 40 (4) ◽  
pp. 643-658 ◽  
Author(s):  
A. M. El Sherbini ◽  
Th. El Sherbini ◽  
H. Hegazy ◽  
G. Cristoforetti ◽  
S. Legnaioli ◽  
...  

2020 ◽  
Vol 1 (2) ◽  
pp. 5-8
Author(s):  
Komang Gde Suastika, Heri Suyanto, Gunarjo, Sadiana, Darmaji

Abstract - Laser-Induced Breakdown Spectroscopy (LIBS) is one method of atomic emission spectroscopy using laser ablation as an energy source. This method is used to characterize the type of amethysts that originally come from Sukamara, Central Kalimantan. The result of amethyst characterization can be used as a reference for claiming the natural wealth of the amethyst. The amethyst samples are directly taken from the amethyst mining field in the District Gem Amethyst and consist of four color variations: white, black, yellow, and purple. These samples were analyzed by LIBS, using laser energy of 120 mJ, delay time detection of 2 μs and accumulation of 3, with and without cleaning. The purpose of this study is to determine emission spectra characteristics, contained elements, and physical characteristics of each amethyst sample. The spectra show that the amethyst samples contain some elements such as Al, Ca, K, Fe, Gd, Ba, Si, Be, H, O, N, Cl and Pu with various emission intensities. The value of emission intensity corresponds to concentration of element in the sample. Hence, the characteristics of the amethysts are based on their concentration value. The element with the highest concentration in all samples is Si, which is related to the chemical formula of SiO2. The element with the lowest concentration in all samples is Ca that is found in black and yellow amethysts. The emission intensity of Fe element can distinguish between white, purple, and yellow amethyst. If Fe emission intensity is very low, it indicates yellow sample. Thus, we may conclude that LIBS is a method that can be used to characterize the amethyst samples.Key words: amethyst, impurity, laser-induced, breakdown spectroscopy, characteristic, gemstones


Minerals ◽  
2021 ◽  
Vol 11 (7) ◽  
pp. 705
Author(s):  
Peter A. Defnet ◽  
Michael A. Wise ◽  
Russell S. Harmon ◽  
Richard R. Hark ◽  
Keith Hilferding

Laser-induced breakdown spectroscopy (LIBS) is a simple and straightforward technique of atomic emission spectroscopy that can provide multi-element detection and quantification in any material, in-situ and in real time because all elements emit in the 200–900 nm spectral range of the LIBS optical emission. This study evaluated two practical applications of LIBS—validation of labels assigned to garnets in museum collections and discrimination of LCT (lithium-cesium-tantalum) and NYF (niobium, yttrium and fluorine) pegmatites based on garnet geochemical fingerprinting, both of which could be implemented on site in a museum or field setting with a handheld LIBS analyzer. Major element compositions were determined using electron microprobe analysis for a suite of 208 garnets from 24 countries to determine garnet type. Both commercial laboratory and handheld analyzers were then used to acquire LIBS broadband spectra that were chemometrically processed by partial least squares discriminant analysis (PLSDA) and linear support vector machine classification (SVM). High attribution success rates (>98%) were obtained using PLSDA and SVM for the handheld data suggesting that LIBS could be used in a museum setting to assign garnet type quickly and accurately. LIBS also identifies changes in garnet composition associated with increasing mineral and chemical complexity of LCT and NYF pegmatites.


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.


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