Standoff Detection of Geological Samples of Metal, Rock, and Soil at Low Pressures Using 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.

Laser beam steering automation with an Arduino-based CNC shield for standoff femtosecond filament-induced breakdown spectroscopic studies

In this study, we report a novel, to the best of our knowledge, instrumentation procedure in the automation of laser beam steering for raster/spiral scanning of the samples used in standoff femtosecond laser-induced breakdown spectroscopy (LIBS) experiments. We have used a readily available and easy-to-handle Arduino-based computerized numerical control (CNC) shield along with the free software, universal G-code sender, for the automation. Standoff femtosecond filamentation-induced breakdown spectra (St-Fs-FIBS) of metals, three compositions of Ag-Au alloy, and polyvinyl chloride, unplasticized polyvinyl chloride, and chlorinated polyvinyl chloride plastic samples were recorded using the developed automated experimental setup. The St-Fs-FIBS spectra were recorded at a standoff distance of ∼5m utilizing a simple hand-held spectrometer. Furthermore, principal component analysis technique was utilized for the successful classification of three compositions of Au-Ag alloy spectra using their St-Fs-FIBS spectral data.

Surface hardness determination of 3D printed parts using laser-induced breakdown spectroscopy

Laser-induced breakdown spectroscopy was used to determine the relationship between the spectral line intensity and surface hardness of 3D printed 18Ni300 maraging steel. Research found that there is a linear relationship between the spectral intensity ratio of ion line to atomic line and the surface hardness of the samples. This linear relationship is closely related to the selected elements and spectral lines. The weak self-absorption spectrum of minor elements can obtain a better linear relationship. We study the effect of the number of laser pulses on the linear relationship. The results show that the ideal results can be obtained by using 100 pulses, which can minimize the damage to the sample.

Half-life determination of inorganic-organic hybrid nanomaterials in mice using laser-induced breakdown spectroscopy

Inorganic or inorganic-organic hybrid nanomaterials have great potential for applications in the biomedical fields. Biological half-life is an essential pharmacokinetic parameter for these materials to function in vivo. Compared to inductively coupled plasma mass spectrometry (ICP-MS), which is the gold standard, laser-induced breakdown spectroscopy (LIBS) is a faster and more efficient elemental detection method. We investigated an efficient way to quantify the metabolic rate using LIBS. Nanoparticle platforms, such as manganese dioxide-bovine serum albumin (MnO2-BSA) or boehmite-bovine serum albumin (AlO(OH)-BSA) were injected into mice through intravenous administration for LIBS spectrum acquisition. First, the spectral background was corrected using the polynomial fitting method; The spectral interference was eliminated by Lorentz fitting for each LIBS spectrum simultaneously. The support vector regression (SVR) was then used for LIBS quantitative analyses. Finally, the LIBS results were compared with the ICP-MS ones. The half-lives of MnO2-BSA calculated by LIBS and ICP-MS were 2.49 and 2.42 h, respectively. For AlO(OH)-BSA, the half-lives detected by LIBS and ICP-MS were 3.46 and 3.57 h, respectively. The relative error of LIBS is within 5% compared to ICP-MS. The results demonstrate that LIBS is a valuable tool for quantifying the metabolic rates with a high degree of accuracy.

Real-time in situ detection of the local air pollution with laser-induced breakdown spectroscopy

The smoke of burning mosquito-repellent incense was taken as an example for the local air pollution to be detected and analyzed in situ and in real time. And the spectra of the ambient air, human breathing, and smoke were detected in situ with the LIBS technique. There are some additional spectral lines being found in human breathing, such as the C, H_β line, and the CN molecular bands. Some characteristic peaks of the elements Fe, Ca, Ti, Sr, and Cr have been observed in the smoke. Moreover, the vibrational and rotational temperature of the CN molecule were calculated. The mosquito-repellent incense was dipped into the solutions containing Mn and Pb to simulate heavy metal pollution in the atmosphere.

Forensic Discrimination of Latent Fingerprints Using Laser-Induced Breakdown Spectroscopy (LIBS) and Chemometric Approaches

A novel technique is reported for separating overlapping latent fingerprints using chemometric approaches that combine laser-induced breakdown spectroscopy (LIBS) and multivariate analysis. The LIBS technique provides the capability of real time analysis and high frequency scanning as well as the data regarding the chemical composition of overlapping latent fingerprints. These spectra offer valuable information for the classification and reconstruction of overlapping latent fingerprints by implementing appropriate statistical multivariate analysis. The current study employs principal component analysis and partial least square methods for the classification of latent fingerprints from the LIBS spectra. This technique was successfully demonstrated through a classification study of four distinct latent fingerprints using classification methods such as soft independent modeling of class analogy (SIMCA) and partial least squares discriminant analysis (PLS-DA). The novel method yielded an accuracy of more than 85% and was proven to be sufficiently robust. Furthermore, through laser scanning analysis at a spatial interval of 125 µm, the overlapping fingerprints were reconstructed as separate two-dimensional forms.

Decomposition and correction overlapping peaks of LIBS using an error compensation method combined with curve fitting

The laser induced breakdown spectroscopy (LIBS) technique is an effective method to detect material composition by obtaining the plasma emission spectrum. The overlapping peaks in the spectrum are a fundamental problem in the qualitative and quantitative analysis of LIBS. Based on a curve fitting method, this paper studies an error compensation method to achieve the decomposition and correction of overlapping peaks. The vital step is that the fitting residual is fed back to the overlapping peaks and performs multiple curve fitting processes to obtain a lower residual result. For the quantitative experiments of Cu, the Cu-Fe overlapping peaks in the range of 321-327 nm obtained from the LIBS spectrum of five different concentrations of CuSO₄·5H₂O solution were decomposed and corrected using curve fitting and error compensation methods. Compared with the curve fitting method, the error compensation reduced the fitting residual about 18.12-32.64% and improved the correlation about 0.86-1.82%. Then, the calibration curve between the intensity and concentration of the Cu was established. It can be seen that the error compensation method exhibits a higher linear correlation between the intensity and concentration of Cu, which can be applied to the decomposition and correction of overlapping peaks in the LIBS spectrum.