A modified algorithm of background removal based on wavelet transform was developed for spectrum correction in laser-induced breakdown spectroscopy (LIBS). The optimal type of wavelet function, decomposition level and scaling factor γ were determined by the root-mean-square error of calibration (RMSEC) of the univariate regression model of the analysis element, which is considered as the optimization criteria. After background removal by this modified algorithm with RMSEC, the root-mean-square error of cross-validation (RMSECV) and the average relative error (ARE) criteria, the accuracy of quantitative analysis on chromium (Cr), vanadium (V), cuprum (Cu), and manganese (Mn) in the low alloy steel was all improved significantly. The results demonstrated that the algorithm developed is an effective pretreatment method in LIBS to significantly improve the accuracy in the quantitative analysis.

Size-controlled synthesis and size-dependent antibacterial activity of Cu₂O nanoparticles with high efficiency for H₂O₂ evolution.

A new approach to polymer identification by laser-induced breakdown spectroscopy (LIBS) with adjusting spectral weightings (ASW) was developed in this work aiming at improving the identification accuracy. This approach has been achieved through increasing the intensities of specific characteristic spectral lines which are important to polymer identification but difficult to be excited. Using the ASW method, the identification accuracies of all 11 polymers were increased to nearly 100%, while the accuracies of PE, PU, PP and PC were only 98%, 74%, 90% and 98%, respectively, without using the ASW method.

A multi-spectral-line calibration approach based on an artificial neural network is presented for steel analysis in LIBS.

A portable laser-induced breakdown spectroscopy (LIBS) system based on a fiber laser was developed and employed to quantitatively analyze manganese (Mn), vanadium (V), and silicon (Si) elements in steels. After background removal, the coefficients of determination (R² factors) of the calibration curves for Mn, V, and Si elements reached 0.997, 0.991 and 0.992, respectively, obvious improvements compared to those of the original spectra. The leave-one-out cross-validation (LOOCV) method was used to test the system. The root-mean-square error of cross-validation (RMSECV) for Mn (0.072–2.06 wt%), V (0.009–0.821 wt%), and Si (0.099–1.85 wt%) elements were 0.037, 0.041 and 0.079 wt%, respectively. The average relative errors (AREs) for Mn elements reached 7.6%. These results are comparable with those of the conventional LIBS which refers to utilizing the traditional flash-lamp-pumped laser as a laser source. However, compared to conventional LIBS, a fiber laser LIBS (FL-LIBS) is more compact, robust, and cost effective. The FL-LIBS, coupling a compact fiber laser and spectrometer, is a convenient approach to providing a portable solution for real-time and in situ detection in industry, especially in harsh environments.