• Resources Recycling
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• v.27 no.1
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• pp.84-91
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• 2018

In this study, a novel soft information based most probable classification scheme is proposed for sorting recyclable metal alloys with laser induced breakdown spectroscopy (LIBS). Regression analysis with LIBS captured spectrums for estimating concentrations of common elements can be efficient for classifying unknown arbitrary metal alloys, even when that particular alloy is not included for training. Therefore, partial least square regression (PLSR) is employed in the proposed scheme, where spectrums of the certified reference materials (CRMs) are used for training. With the PLSR model, the concentrations of the test spectrum are estimated independently and are compared to those of CRMs for finding out the most probable class. Then, joint soft information can be obtained by assuming multi-variate normal (MVN) distribution, which enables to account the probability measure or a prior information and improves classification performance. For evaluating the proposed schemes, MVN soft information is evaluated based on PLSR of LIBS captured spectrums of 9 metal CRMs, and tested for classifying unknown metal alloys. Furthermore, the likelihood is evaluated with the radar chart to effectively visualize and search the most probable class among the candidates. By the leave-one-out cross validation tests, the proposed scheme is not only showing improved classification accuracies but also helpful for adaptive post-processing to correct the mis-classifications.

• Proceedings of the Korea Air Pollution Research Association Conference
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• 2010.04a
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• pp.496-497
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• 2010

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.18 no.7
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• pp.71-76
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• 2019

The diffusion of the drug component of the inflammatory patch into the living tissue was analyzed by laser induced plasma spectroscopy (LIBS). Calcium element, which is a diffusion catalyst of the drug in the inflammatory analgesic patch, is transferred into the body through the diffusion process of the substance. The test pieces used in the experiment are pig skin tissues which are similar to human skin. As a result, the diffusion coefficient D of the calcium element was found to be average $8.24{\times}10^{-2}({\mu}m^2/s)$. Experimental results showed that the most influential factors on the diffusion of materials were temperature variables.

• 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.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.17 no.5
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• pp.149-154
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• 2018

To improve the efficiency and lifetime of filters, we analyze the element distribution at the entrance and exit by using the flow inside a filter, confirming that the internal structure affects the filter efficiency. The flow in the pipe is predicted through computer simulations, and the filtration efficiency of each element is compared through experiments. The efficiency and lifetime of the filter are indirectly improved through the element distribution at the filter outlet according to the internal structure. Because pressure loss from the structure inevitably occurs, the efficiency and lifetime of filters against pressure loss must be considered.

• 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.