Continuous-wavelet-transform-based automatic curve fitting method for laser-induced breakdown spectroscopy

Spectral filtering method for improvement of detection accuracy of Mg, Cu, Mn and Cr elements in aluminum alloys using femtosecond LIBS

In this work, magnesium (Mg), copper (Cu), manganese (Mn) and chromium (Cr) in aluminum alloy samples were quantified by femtosecond laser-induced breakdown spectroscopy (fs-LIBS). The different parameters affecting the experimental results, including the laser pulse energy, moving speed of the 2D platform and spectral average number were optimized. The background signal preprocessing methods of median filtering (MF corrected) and Savitzky-Golay filtering (SG corrected) algorithms were used and the effect of the LIBS spectral analysis in the experiment investigated. The calibration curves of Mg, Cu, Mn and Cr elements were established separately and their corresponding detection limits (LODs) were calculated. After background correction, the LODs of Mg, Cu, Mn and Cr elements in MF corrected were 54.52, 11.69, 7.33 and 27.72 ppm, and in SG corrected were 59.15, 17.48, 14.75 and 31.97 ppm. The LODs of these elements in MF corrected and SG corrected have 1.4-5.2 and 1.2-2.5 improvement factors compared to those obtained using the fs-LIBS technique. This work demonstrates that background signal preprocessing methods are very helpful for improving analytical sensitivity and accuracy in quantitative analyses of aluminum alloys.

Measurement of Temperature and H2O Concentration in Premixed CH4/Air Flame Using Two Partially Overlapped H2O Absorption Signals in the Near Infrared Region

It is important to monitor the temperature and H2O concentration in a large combustion environment in order to improve combustion (and thermal) efficiency and reduce harmful combustion emissions. However, it is difficult to simultaneously measure both internal temperature and gas concentration in a large combustion system because of the harsh environment with rapid flow. In regard, tunable diode laser absorption spectroscopy, which has the advantages of non-intrusive, high-speed response, and in situ measurement, is highly attractive for measuring the concentration of a specific gas species in the combustion environment. In this study, two partially overlapped H2O absorption signals were used in the tunable diode laser absorption spectroscopy (TDLAS) to measure the temperature and H2O concentration in a premixed CH4/air flame due to the wide selection of wavelengths with high temperature sensitivity and advantages where high frequency modulation can be applied. The wavelength regions of the two partially overlapped H2O absorptions were 1.3492 and 1.34927 μm. The measured signals separated the multi-peak Voigt fitting. As a result, the temperature measured by TDLAS based on multi-peak Voigt fitting in the premixed CH4/air flame was the highest at 1385.80 K for an equivalence ratio of 1.00. It also showed a similarity to those tendencies to the temperature measured by the corrected R-type T/C. In addition, the H2O concentrations measured by TDLAS based on the total integrated absorbance area for various equivalent ratios were consistent with those calculated by the chemical equilibrium simulation. Additionally, the H2O concentration measured at an equivalence ratio of 1.15 was the highest at 18.92%.

High-Sensitivity Determination of Nutrient Elements in Panax notoginseng by Laser-induced Breakdown Spectroscopy and Chemometric Methods

High-accuracy and fast detection of nutritive elements in traditional Chinese medicine Panax notoginseng (PN) is beneficial for providing useful assessment of the healthy alimentation and pharmaceutical value of PN herbs. Laser-induced breakdown spectroscopy (LIBS) was applied for high-accuracy and fast quantitative detection of six nutritive elements in PN samples from eight producing areas. More than 20,000 LIBS spectral variables were obtained to show elemental differences in PN samples. Univariate and multivariate calibrations were used to analyze the quantitative relationship between spectral variables and elements. Multivariate calibration based on full spectra and selected variables by the least absolute shrinkage and selection operator (Lasso) weights was used to compare the prediction ability of the partial least-squares regression (PLS), least-squares support vector machines (LS-SVM), and Lasso models. More than 90 emission lines for elements in PN were found and located. Univariate analysis was negatively interfered by matrix effects. For potassium, calcium, magnesium, zinc, and boron, LS-SVM models based on the selected variables obtained the best prediction performance with R_p values of 0.9546, 0.9176, 0.9412, 0.9665, and 0.9569 and root mean squared error of prediction (RMSEP) of 0.7704 mg/g, 0.0712 mg/g, 0.1000 mg/g, 0.0012 mg/g, and 0.0008 mg/g, respectively. For iron, the Lasso model based on full spectra obtained the best result with an R_p value of 0.9348 and RMSEP of 0.0726 mg/g. The results indicated that the LIBS technique coupled with proper multivariate chemometrics could be an accurate and fast method in the determination of PN nutritive elements for traditional Chinese medicine management and pharmaceutical analysis.