DOI: 10.3964/j.issn.1000-0593(2017)11-3600-06

Authors
Han, X. ; Li, Y. C. ; Qui, C. L. ; Tian, D. ; Yang, G.

Keywords

Laser-induced breakdown spectroscopy; Plastic; Partial least squares; Classification;IDENTIFICATION; LIBS; DISCRIMINATION; POLYMERS

Abstract

The traditional ways of waste plastics processing mainly use the burning landfill, which lead to environmental pollution and the waste of resources. Waste plastic recycling is very important on the circulation economy and the sustainable development. The traditional instruments have some shortcomings in plastic classification, such as lower precision, higher cost, the influence of the sample color and a serious threat to operating personnel's health. Laser inducedbreakdown spectroscopy has many advantages, such as simultaneous multielement detection of elements, free from sample preparation, rapid and real-time analysis, slight damages to sample and no impact on the sample color. The method of Chemometrics combined with LIBS technique is applied to the plastic, which improves the accuracy of plastic classification. But at present, the classification has many problems, such as more parameters and the poor universality. Using on a self built LIBS instrument, we can study the laser energy, delay time, integration time and the angle of the optical fiber, which can achieve a better experiment condition. With the experimental platform, we analyze the 2 200 sample points and choose the partial least squares to analyze the spectral data. In order to achieve the correlation between the sample label and the data, we discuss the better ratio of the training set and validation set. The experimental results show that replacing the interference spectra, classification accuracy of all 11 plastic is increased to 100%, while the validation set's accuracy is only 99.8% and the test set is 99.09% without replacing the interference spectra. It can be seen that the laser induced breakdown spectroscopy combined with partial least squares method can be successfully used for the plastic sample classification.

DOI: 10.3964/j.issn.1000-0593(2017)10-3274-07

Authors
Gu, Y. H. ; Jia, Y. ; Liu, J. G. ; Liu, W. Q. ; Ma M. J. ; Meng, D. S. ; Zhao, N. J.

Keywords

Laser-induced breakdown spectroscopy; Quantitative analysis; Standard addition method; Curve fitting; Heavy metals;

Abstract

Quantitative analysis of four heavy metals Pb, Cr, Cu and Cd in soils and solid wastes using independently developed portable system of laser-inducedbreakdown spectroscopy. A Nd: YAG pulse laser with fundamental wavelength of 1 064 nm is used as the excitation source, with the single pulse energy of 100 mJ the pulse width of 6 ns, and the operating frequency 3 Hz. The echelle spectroscopy with high resolution and wide spectral range is used as the spectral separation device, and the intensified charge coupled device GOOD) as the spectral detection device in the experiment, with the detection range of 200 similar to 500 nm and a resolution of 0.08 similar to 0.12 nm. In order to improve the spectral intensity and detection sensitivity, a device of hemisphere spatially bound is used to restrain the plasma and a optical fiber with multi-channel is used collect the signal. The reception angle is 45 degrees. The laserrepetition rate is 2 Hz while the delay is 1.5 mu s, with the gate width of 1.05 ms. Standard addition method is used to effectively solve the quantitative analysis of samples of unknown matrix. The innovation lies in the fact that, a curve fit instead of a straight line fit is used in the standard addition method to quantitative analyze the heavy metals in soils and solid wastes, which effectively improve the measurement results. Especially for the low concentrations of soil samples, linear fitting can not be used in quantitative analysis, in contrast, the correlation coefficient of curve fitting is much higher, more closer to the national standard measurement methods, to meet soil pollution detection. The result of seven soils and solid wastes samples are as follows, line fitting relative error: Pb 1.26%similar to 79.38%, Cr-22. 44%similar to 82.06%, Cu 15.09%similar to 190.50%, Cd 32.76%similar to 167.96%, and curve fitting relative error respectively Pb - 4.19%similar to 11.92%, Cr-38.31%similar to 9.26%, Cu-7.24% similar to 26.86%, Cd-10.52%similar to 12.94%, the average relative error is 10.47%.