• Laser Solutions
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• v.17 no.4
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• pp.7-13
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• 2014

In this work, the application of laser induced breakdown spectroscopy (LIBS) for the composition analysis of thin $Cu(In,Ga)Se_2$ (CIGS) solar cell films ($1-2{\mu}m$ thickness) is reported. For the ablation of CIGS films, femtosecond (fs) laser (wavelength = 343nm, pulse width = 500fs) and nanosecond (ns) laser (wavelength = 266nm, pulse width = 5ns) were used under atmospheric environment. The emission spectra were detected with an intensified charge coupled device (ICCD) spectrometer and multichannel CCD spectrometer for fs-LIBS and ns-LIBS, respectively. The calibration curves for fs-LIBS and ns-LIBS intensity ratios of Ga/Cu, In/Cu, and Ga/In were generated with respect to the concentration ratios measured by inductively coupled plasma optical emission spectrometry (ICP-OES).

• Resources Recycling
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• v.27 no.1
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• pp.31-37
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• 2018

To enhance the recycling rate of used metal resources, it is strongly desired to develop a metal sorting system that can automatically identify metal type from mixed metal scraps and sort them separately. Laser-induced breakdown spectroscopy(LIBS) is a technique that enables real time classification of different metals based on multi-elemental and in-air analysis. In this work, we report the results of LIBS elemental analysis of field scrap samples acquired from a recycling company. By applying multivariate analysis, it was found that the LIBS signals of five different metals could be perfectly classified if surface contamination was removed. The classification accuracy degraded for LIBS signals including contaminant emission, which however could be overcome by performing the multivariate analysis using properly selected emission lines of higher correlation only. The significant improvement in classification accuracy and process speed by the selection of proper emission lines demonstrated the feasibility of LIBS technique as an industrial tool for metal scrap sorting.

• Economic and Environmental Geology
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• v.40 no.5
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• pp.563-574
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• 2007

Laser induced breakdown spectroscopy (LIBS) is a recently developed analytical technique that is based upon the measurement of emission lines generated by atomic species close to the surface of the sample, thus allowing their chemical detection, identification and quantification. With powerful advantages of LIBS compared to the conventional analytical methodology, this technique can be applied in the detection of heavy metals in the field. LIBS allows the rapid analysis by avoiding laborious chemical steps. LES have already been applied for the determination of element concentration in a wide range of materials in the solid, liquid and gaseous phase with simplicity of the instrument and diversity of the analytical application. These feasibility of rapid multi elemental analysis are appealing proprieties for the in-situ analytical technique in geochemical investigation, exploration and environmental analysis. There remain still some limitations to be solved for LIBS to be applied in soil environment as an in-situ analytical technology. We would like to provide the basic principle related to the plasma formation and laser-induced breakdown of sample materials. In addition, the matrix effect, laser properties and the various factors affecting on the analytical signal of LIBS was dealt with to enhance understanding of LIBS through literature review. Ultimately, it was investigated the feasibility of LIBS application in soil environment monitoring by considering the basic idea to enhance the data quality of LIBS including the calibration method for the various effects on the analytical signal of LIBS.

• Resources Recycling
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• v.26 no.6
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• pp.73-83
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• 2017

Used small household appliances have a wide variety of product types and component materials, and contain high percentage of black plastics. However, they are not being recycled efficiently as conventional sensors such as near-infrared ray (NIR), etc. are not able to detect black plastic by types. In the present study, an automatic sorting system was developed based on laser-induced breakdown spectroscopy (LIBS) to promote the recycling of waste plastics. The system we developed mainly consists of sample feeder, automatic position recognition system, LIBS device, separator and control unit. By applying laser pulse on the target sample, characteristic spectral data can be obtained and analyzed by using CCD detectors. The obtained data was then treated by using a classifier, which was developed based on artificial intelligent algorithm. The separation tests on waste plastics also were carried out by using a lab-scale automatic sorting system and the test results will be discussed. The classification rate of the radial basis neural network (RBFNNs) classifier developed in this study was about > 97%. The recognition rate of the black plastic by types with the automatic sorting system was more than 94.0% and the sorting efficiency was more than 80.0%. Automatic sorting system based on LIBS technology is in its infant stage and it has a high potential for utilization in and outside Korea due to its excellent economic efficiency.

• Korean Journal of Soil Science and Fertilizer
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• v.42 no.5
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• pp.399-407
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• 2009

Laser induced breakdown spectroscopy(LIBS) is an simple analysis method for directly quantifying many kinds of soil micro-elements on site using a small size of laser without pre-treatment at any property of materials(solid, liquid and gas). The purpose of this study were to find an optimum condition of the LIBS measurement including wavelengths for quantifying soil elements, to relate spectral properties to the concentration of soil elements using LIBS as a simultaneous un-breakdown quantitative analysis technology, which can be applied for the safety assessment of agricultural products and precision agriculture, and to compare the results with a standardized chemical analysis method. Soil samples classified as fine-silty, mixed, thermic Typic Hapludalf(Memphis series) from grassland and uplands in Tennessee, USA were collected, crushed, and prepared for further analysis or LIBS measurement. The samples were measured using LIBS ranged from 200 to 600 nm(0.03 nm interval) with a Nd:YAG laser at 532 nm, with a beam energy of 25 mJ per pulse, a pulse width of 5 ns, and a repetition rate of 10 Hz. The optimum wavelength(${\lambda}nm$) of LIBS for estimating soil and plant elements were 308.2 nm for Al, 428.3 nm for Ca, 247.8 nm for T-C, 438.3 nm for Fe, 766.5 nm for K, 85.2 nm for Mg, 330.2 nm for Na, 213.6 nm for P, 180.7 nm for S, 288.2 nm for Si, and 351.9 nm for Ti, respectively. Coefficients of determination($r^2$) of calibration curve using standard reference soil samples for each element from LIBS measurement were ranged from 0.863 to 0.977. In comparison with ICP-AES(Inductively coupled plasma atomic emission spectroscopy) measurement, measurement error in terms of relative standard error were calculated. Silicon dioxide(SiO2) concentration estimated from two methods showed good agreement with -3.5% of relative standard error. The relative standard errors for the other elements were high. It implies that the prediction accuracy is low which might be caused by matrix effect such as particle size and constituent of soils. It is necessary to enhance the measurement and prediction accuracy of LIBS by improving pretreatment process, standard reference soil samples, and measurement method for a reliable quantification method.

• Resources Recycling
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• v.26 no.1
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• pp.69-77
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• 2017

Used small household appliances(small e-waste) consists of a variety of complex materials and components. The small e-waste is mainly composed of plastics and an important potential source of waste plastic. The black plastics, particularly are very difficult to separate by resin type and therefore these are mainly recycled in the form of a mixtures. In the present study, the sorting technologies such as gravity and electro static separation, near-infrared ray(NIR) and IR/Raman optical sorting separation on mixture of black plastics were analyzed and their limitations on sorting process were also investigated. The Laser Induced Breakdown Spectroscopy(LIBS) spectrum of each black plastics was used for identification of black plastics by resin type, and after analyzing the normalization operation, Principal Component Analysis(PCA) was carried out. The spectrum data was optimized through PCA process. In order to improve the identification accuracy and sorting efficiency of black plastics, it is necessary to design a classifier with high efficiency and to improve the performance and reliability of the classifier by applying the field of intelligent algorithms.

• Resources Recycling
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• v.26 no.2
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• pp.46-55
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• 2017

In this study, the design methodology of Radial Basis Function Neural Networks is developed with the aid of Laser Induced Breakdown Spectroscopy and also applied to the practical plastics sorting system. To identify black plastics such as ABS, PP, and PS, RBFNNs classifier as a kind of intelligent algorithms is designed. The dimensionality of the obtained input variables are reduced by using PCA and divided into several groups by using K-means clustering which is a kind of clustering techniques. The entire data is split into training data and test data according to the ratio of 4:1. The 5-fold cross validation method is used to evaluate the performance as well as reliability of the proposed classifier. In case of input variables and clusters equal to 5 respectively, the classification performance of the proposed classifier is obtained as 96.78%. Also, the proposed classifier showed superiority in the viewpoint of classification performance where compared to other classifiers.