Improvement of measurement precision and repeatability is one of the issues currently faced by the laser-induced breakdown spectroscopy （LIBS） technique, which is expected to be capable of precise and accurate quant...Improvement of measurement precision and repeatability is one of the issues currently faced by the laser-induced breakdown spectroscopy （LIBS） technique, which is expected to be capable of precise and accurate quantitative analysis. It was found that there was great potential to improve the signal quality and repeatability by reducing the laser beam divergence angle using a suitable beam expander （BE）. In the present work, the influences of several experimental parameters for the case with BE are studied in order to optimize the analytical performances： the signal to noise ratio （SNR） and the relative standard deviation （RSD）. We demonstrate that by selecting the optimal experimental parameters, the BE-included LIBS setup can give higher SNR and lower RSD values of the line intensity normalized by the whole spectrum area. For validation purposes, support vector machine （SVM） regression combined with principal component analysis （PCA） was used to establish a calibration model to realize the quantitative analysis of the ash content. Good agreement has been found between the laboratory measurement results from the LIBS method and those from the traditional method. The measurement accuracy presented here for ash content analysis is estimated to be 0.31%, while the average relative error is 2.36%.展开更多
Three major elements, carbon, hydrogen, and nitrogen, in twenty-four bituminous coal samples, were measured by laser-induced breakdown spectroscopy. Argon and helium were applied as ambient gas to enhance the signals ...Three major elements, carbon, hydrogen, and nitrogen, in twenty-four bituminous coal samples, were measured by laser-induced breakdown spectroscopy. Argon and helium were applied as ambient gas to enhance the signals and eliminate the interference of nitrogen from surrounding air. The relative standard deviation of the related emission lines and the performance in the partial least squares （PLS） modeling were compared for different ambient environments. The results showed that argon not only improved the intensity, but also reduced signal fluctuation. The PLS model also had the optimal performance in multi-element analysis using argon as ambient gas. The root mean square error of prediction of carbon concentration decreased from 4.25% in air to 3.49% in argon, while the average relative error reduced from 4.96% to 2.98%. Hydrogen line demonstrated similar improvement. Yet, the nitrogen lines were too weak to be detected even in an argon environment which suggested the nitrogen signal measured in air come from the breakdown of nitrogen molecules in the atmosphere.展开更多
基金supported by the 973 Program of China(No.2012CB921603)National Natural Science Foundation of China(Nos.61475093,61127017,61178009,61108030,61378047,61275213,61475093,and 61205216)+3 种基金the National Key Technology R&D Program of China(No.2013BAC14B01)the Shanxi Natural Science Foundation(Nos.2013021004-1 and 2012021022-1)the Shanxi Scholarship Council of China(Nos.2013-011 and 2013-01)the Program for the Outstanding Innovative Teams of Higher Learning Institutions of Shanxi,China
文摘Improvement of measurement precision and repeatability is one of the issues currently faced by the laser-induced breakdown spectroscopy （LIBS） technique, which is expected to be capable of precise and accurate quantitative analysis. It was found that there was great potential to improve the signal quality and repeatability by reducing the laser beam divergence angle using a suitable beam expander （BE）. In the present work, the influences of several experimental parameters for the case with BE are studied in order to optimize the analytical performances： the signal to noise ratio （SNR） and the relative standard deviation （RSD）. We demonstrate that by selecting the optimal experimental parameters, the BE-included LIBS setup can give higher SNR and lower RSD values of the line intensity normalized by the whole spectrum area. For validation purposes, support vector machine （SVM） regression combined with principal component analysis （PCA） was used to establish a calibration model to realize the quantitative analysis of the ash content. Good agreement has been found between the laboratory measurement results from the LIBS method and those from the traditional method. The measurement accuracy presented here for ash content analysis is estimated to be 0.31%, while the average relative error is 2.36%.
基金Acknowledgements The authors are grateful for the financial support from the National Natural Science Foundation of China （Grant No. 51061130536）.
文摘Three major elements, carbon, hydrogen, and nitrogen, in twenty-four bituminous coal samples, were measured by laser-induced breakdown spectroscopy. Argon and helium were applied as ambient gas to enhance the signals and eliminate the interference of nitrogen from surrounding air. The relative standard deviation of the related emission lines and the performance in the partial least squares （PLS） modeling were compared for different ambient environments. The results showed that argon not only improved the intensity, but also reduced signal fluctuation. The PLS model also had the optimal performance in multi-element analysis using argon as ambient gas. The root mean square error of prediction of carbon concentration decreased from 4.25% in air to 3.49% in argon, while the average relative error reduced from 4.96% to 2.98%. Hydrogen line demonstrated similar improvement. Yet, the nitrogen lines were too weak to be detected even in an argon environment which suggested the nitrogen signal measured in air come from the breakdown of nitrogen molecules in the atmosphere.
