scholarly journals Classification of Geological Samples Based on Soft Independent Modeling of Class Analogy Using Laser-Induced Breakdown Spectroscopy

2018 ◽  
Vol 2018 ◽  
pp. 1-7
Author(s):  
Ying Zhang ◽  
Ying Li ◽  
Wendong Li ◽  
Zigang Sun ◽  
Yunfeng Bi
Keyword(s):  
Matrix Effects ◽  
Principal Component ◽  
Misclassification Rate ◽  
Laser Induced Breakdown Spectroscopy ◽  
Geological Samples ◽  
Classification Rate ◽  
Breakdown Spectroscopy ◽  
Laser Induced Breakdown ◽  
Similar Sample

Laser-induced breakdown spectroscopy with soft independent modeling of class analogy is used in the identification of a large number of unprocessed geological samples having similar components in this study. Considering a variety of data from different samples, representative spectral regions representing the major components were extracted. In addition, principal component analysis was applied to remove noninformative variables from the spectrum. The unclassification rate, misclassification rate, and average correct classification rate for 25 types of geological samples were 1.2%, 4.7%, and 94.1%, respectively. These results suggest that laser-induced breakdown spectroscopy using soft independent modeling of class analogy can be used to identify a wide variety of geological samples. Furthermore, we found that this approach can be used to identify spectral differences among similar sample types because of matrix effects and the trace element impurities.

scholarly journals Laser-Induced Breakdown Spectroscopy and Principal Component Analysis for the Classification of Spectra from Gold-Bearing Ores

2019 ◽  
Vol 74 (1) ◽  
pp. 42-54 ◽  
Author(s):  
Daniel Diaz ◽  
Alejandro Molina ◽  
David W. Hahn
Keyword(s):  
Principal Component Analysis ◽  
Limit Of Detection ◽  
Principal Component ◽  
Component Analysis ◽  
Emission Lines ◽  
Laser Induced Breakdown Spectroscopy ◽  
Single Shot ◽  
Breakdown Spectroscopy ◽  
Laser Induced Breakdown

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.

scholarly journals Detection of Rare Earth Elements in Minerals and Soils by Laser-Induced Breakdown Spectroscopy (LIBS) Using Interval PLS

Minerals ◽  
2021 ◽  
Vol 11 (12) ◽  
pp. 1379
Author(s):  
Nina Rethfeldt ◽  
Pia Brinkmann ◽  
Daniel Riebe ◽  
Toralf Beitz ◽  
Nicole Köllner ◽  
...  
Keyword(s):  
Rare Earth ◽  
Rare Earth Elements ◽  
Matrix Effects ◽  
Principal Component ◽  
Laser Induced Breakdown Spectroscopy ◽  
Regression Methods ◽  
Breakdown Spectroscopy ◽  
Field Samples ◽  
Laser Induced Breakdown

The numerous applications of rare earth elements (REE) has lead to a growing global demand and to the search for new REE deposits. One promising technique for exploration of these deposits is laser-induced breakdown spectroscopy (LIBS). Among a number of advantages of the technique is the possibility to perform on-site measurements without sample preparation. Since the exploration of a deposit is based on the analysis of various geological compartments of the surrounding area, REE-bearing rock and soil samples were analyzed in this work. The field samples are from three European REE deposits in Sweden and Norway. The focus is on the REE cerium, lanthanum, neodymium and yttrium. Two different approaches of data analysis were used for the evaluation. The first approach is univariate regression (UVR). While this approach was successful for the analysis of synthetic REE samples, the quantitative analysis of field samples from different sites was influenced by matrix effects. Principal component analysis (PCA) can be used to determine the origin of the samples from the three deposits. The second approach is based on multivariate regression methods, in particular interval PLS (iPLS) regression. In comparison to UVR, this method is better suited for the determination of REE contents in heterogeneous field samples.

scholarly journals An Approach of Laser-Induced Breakdown Spectroscopy to Detect Toxic Metals in Crushed Ice Ball

2013 ◽  
Vol 2013 ◽  
pp. 1-9 ◽  
Author(s):  
Rahul Agrawal ◽  
Ashok Kumar Pathak ◽  
Awadhesh Kumar Rai ◽  
Gyanendra Kumar Rai
Keyword(s):  
Toxic Metals ◽  
Principal Component ◽  
Analytical Tool ◽  
Laser Induced Breakdown Spectroscopy ◽  
Breakdown Spectroscopy ◽  
Minimal Sample ◽  
Laser Induced Breakdown ◽  
Crushed Ice

This paper deals the application of laser-induced breakdown spectroscopy (LIBS) to toxic metals used as pigment in crushed ice-ball samples. The present work highlights the advantages of LIBS as in situ, real-time analytical tool for rapid detection of toxic or heavy metals like lead (Pb) and chromium (Cr) and non toxic elements like carbon (C), nitrogen (N), magnesium (Mg), calcium (Ca), sodium (Na), and potassium (K) in crushed ice-ball of different colors (red, green, yellow, pale yellow, and orange) collected from five different areas, with minimal sample preparation. For rapid surveillance of toxic metals we have used multivariate analysis, that is, principal component analysis (PCA) with the LIBS spectral data of ice-ball samples. This study suggests that LIBS coupled with PCA may be an instant diagnostic tool for identification and classification of adulterated and nonadulterated samples.

scholarly journals Fast Classification of Geographical Origins of Honey Based on Laser-Induced Breakdown Spectroscopy and Multivariate Analysis

Sensors ◽  
2020 ◽  
Vol 20 (7) ◽  
pp. 1878 ◽  
Author(s):  
Zhangfeng Zhao ◽  
Lun Chen ◽  
Fei Liu ◽  
Fei Zhou ◽  
Jiyu Peng ◽  
...  
Keyword(s):  
Principal Component ◽  
Laser Induced Breakdown Spectroscopy ◽  
Support Vector ◽  
Breakdown Spectroscopy ◽  
Linear Discrimination ◽  
Acacia Honey ◽  
Laser Induced Breakdown ◽  
Fast Classification ◽  
Better Than

Traceability of honey is highly required by consumers and food administration with the consideration of food safety and quality. In this study, a technique named laser-induced breakdown spectroscopy (LIBS) was used to fast trace geographical origins of acacia honey and multi-floral honey. LIBS emissions from elements of Mg, Ca, Na, and K had significant differences among different geographical origins. The clusters of honey from different geographical origins were visualized with principal component analysis. In addition, support vector machine (SVM) and linear discrimination analysis (LDA) were used to quantitively classify the origins. The results indicated that SVM performed better than LDA, and the discriminant results of multi-floral honey were better than acacia honey. The accuracy and mean average precision for multi-floral honey were 99.7% and 99.7%, respectively. This study provided a fast approach for geographical origin classification, and might be helpful for food traceability.

scholarly journals Classification of Greek Olive Oils from Different Regions by Machine Learning-Aided Laser-Induced Breakdown Spectroscopy and Absorption Spectroscopy

Molecules ◽  
2021 ◽  
Vol 26 (5) ◽  
pp. 1241
Author(s):  
Nikolaos Gyftokostas ◽  
Eleni Nanou ◽  
Dimitrios Stefas ◽  
Vasileios Kokkinos ◽  
Christos Bouras ◽  
...  
Keyword(s):  
Machine Learning ◽  
Olive Oil ◽  
Absorption Spectra ◽  
Absorption Spectroscopy ◽  
Laser Induced Breakdown Spectroscopy ◽  
Spectroscopic Techniques ◽  
Breakdown Spectroscopy ◽  
Olive Oils ◽  
Laser Induced Breakdown

In the present work, the emission and the absorption spectra of numerous Greek olive oil samples and mixtures of them, obtained by two spectroscopic techniques, namely Laser-Induced Breakdown Spectroscopy (LIBS) and Absorption Spectroscopy, and aided by machine learning algorithms, were employed for the discrimination/classification of olive oils regarding their geographical origin. Both emission and absorption spectra were initially preprocessed by means of Principal Component Analysis (PCA) and were subsequently used for the construction of predictive models, employing Linear Discriminant Analysis (LDA) and Support Vector Machines (SVM). All data analysis methodologies were validated by both “k-fold” cross-validation and external validation methods. In all cases, very high classification accuracies were found, up to 100%. The present results demonstrate the advantages of machine learning implementation for improving the capabilities of these spectroscopic techniques as tools for efficient olive oil quality monitoring and control.

A NOVEL STRATEGY FOR DIRECT ELEMENTAL DETERMINATION USING LASER-INDUCED BREAKDOWN SPECTROSCOPY: FLUENCE CALIBRATION

2021 ◽  
Author(s):  
Raquel C Machado ◽  
Diego Victor Babos ◽  
Daniel Fernandes Andrade ◽  
Edenir Rodrigues Pereira-Filho
Keyword(s):  
Quantitative Analysis ◽  
Matrix Effects ◽  
Calibration Method ◽  
Laser Induced Breakdown Spectroscopy ◽  
Breakdown Spectroscopy ◽  
Elemental Determination ◽  
Laser Induced Breakdown ◽  
Direct Solid Analysis ◽  
Novel Strategy ◽  
Direct Solid

Quantitative analysis requires several efforts to obtain an adequate calibration method to overcome matrix effects employing direct solid analysis by laser-induced breakdown spectroscopy (LIBS). To this end, in this study,...

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