Spatial confinement effects of laser-induced breakdown spectroscopy at reduced air pressures.

Spatial confinement is a simple and cost-effective method for enhancing signal intensity and improving the detection sensitivity of laser-induced breakdown spectroscopy (LIBS). However, the spatial confinement effects of LIBS under different pressures remains a question to be studied, because the pressure of the ambient gas has a significant influence on the temporal and spatial evolution of plasma. In this study, spatial confinement effects of LIBS under a series of reduced air pressures were investigated experimentally, and the plasma characteristics under different air pressures were studied. The results show that the reduced air pressure can lead to both earlier onset and weakening of the enhancement effect of the spatial confinement on the LIBS line intensity. When the air pressure drops to 0.1 kPa, the enhancement effect of the emission intensity no longer comes from the compression of the reflected shock wave on the plasma, but from the cavity's restriction of the plasma expansion space. In conclusion, the enhancement effect of spatial confinement technology on the LIBS is still effective when the pressure is reduced, which further expands the research and application field of spatial confinement technology.

Sensitive analysis of fluorine and chlorine elements in water solution using laser-induced breakdown spectroscopy assisted with molecular synthesis.

Fluorine and chlorine are key elements to affecting water quality, but they are hard to be determined by conventional laser-induced breakdown spectroscopy (LIBS). To achieve high sensitivity detection of them, the CaF and CaCl molecules were synthesized by combining calcium in calcite and F and Cl in sample. The temporal characteristics of CaF and CaCl molecular emissions were investigated. It shows that molecular emission of CaF and CaCl has a longer lifetime and high spectral intensity than that of their atomic emissions. Such unique feature of molecular emission inspired us to use it for high sensitivity analysis of Cl and F elements in water. The results show that these two elements can be sensitively and accurately detected using LIBS assisted with molecular emission. The limits of detections (LoDs) were 0.38 mg/L and 1.03 mg/L for F and Cl elements, respectively, and the limit of quantitation (LoQ) was 3.404 mg/L to 20.569 mg/L for fluorine elements and 9.986 mg/L to 39.757 mg/L for fluorine. These detection limits can meet the World Health Organization's detection requirements for F and Cl elements in water. The results show that LIBS assisted with molecular synthesis has a huge potential in water quality monitoring.

Self-absorption reduction in laser-induced breakdown spectroscopy using laser-stimulated absorption: publisher's note.

This publisher's note contains corrections to Opt. Lett.40, 5224 (2015).OPLEDP0146-959210.1364/OL.40.005224.

An image features assisted line selection method in laser-induced breakdown spectroscopy.

Analytical lines play a crucial role in laser-induced breakdown spectroscopy (LIBS) technology. To improve the classification performance of LIBS, an image features assisted line selection (IFALS) method which based on spectral morphology and the characteristics of Harris corners was proposed. With this method, a classification experiment for 24 metamorphic rock samples was conducted with linear discriminant analysis (LDA) algorithm. The result showed that the classification accuracy was increased from 94.38% of the conventional classification model MLS-LDA (Manual line selection-linear discriminant analysis) to 98.54% of IFALS-LDA. Furthermore, the time required for the whole classification process was decreased from 2768.38 s of MLS-LDA to 4.36 s of the proposed method, thus the classification efficiency was greatly improved. In addition, compared with the existing automatic line selection method, the convergence rate of IFALS-LDA is significantly faster than that of ASPI (Automatic spectral peaks identification)-LDA. This study demonstrates that LIBS assisted with the image features in machine vision can promote the analytical performance of LIBS technology.

Correction: Fabrication of metal/semiconductor nanocomposites by selective laser nano-welding.

Correction for 'Fabrication of metal/semiconductor nanocomposites by selective laser nano-welding' by Huiwu Yu et al., Nanoscale, 2017, 9, 7012-7015.

A quantitative analysis method assisted by image features in laser-induced breakdown spectroscopy.

The determination accuracy of alloying elements in high alloy steel is generally poor in laser-induced breakdown spectroscopy (LIBS) due to their matrix effect. To solve this problem, an image quantitative analysis (IQA) method was proposed and verified by determining nickel (Ni) in 17 stainless steel samples in this work. The results showed that the coefficient of determination (R2) was increased from 0.9833 of a conventional spectrum quantitative analysis (SQA) method to 0.9996 of the IQA method, and the average relative error of cross-validation (ARECV) and root mean squared error of cross-validation (RMSECV) were decreased from 56.80% and 1.0818 wt% to 15.93% and 0.9866 wt%, respectively. Besides, the determinations of chromium (Cr) and silicon (Si) demonstrated the generalization ability of the IQA. This study provides an effective approach to improving the quantitative performance of LIBS through the combination of image processing and computer vision technology.

Accuracy improvement of quantitative analysis for major elements in laser-induced breakdown spectroscopy using single-sample calibration.

Accurate determination of major elements using limited standard samples is always a big challenge in laser-induced breakdown spectroscopy (LIBS). Based on a simple calculation process, we propose a new one-point calibration method called single-sample calibration LIBS (SSC-LIBS) to build the calibration and improve the accuracy of determination of major elements. In this work, several major elements (Fe, Cu, Zn, Ni, Cr, Nb, and Mo) in three sets of matrix-matched certified samples were determined without sample preparation. The results showed that compared with multipoint calibration LIBS (MPC-LIBS), the R2, RMSECV, and ARE of Cu elements were improved from 0.40 to 0.97, 3.55 wt% to 0.76 wt%, and 5.19% to 1.05%, respectively, while the ARSD decreased from 16.22% to 1.15%. Furthermore, the AREs in the concentration ranges of 1-10, 10-20, 30-40, 50-60, 60-70, and 80-100 wt% were 5.16%, 2.55%, 1.75%, 1.69%, 1.05%, and 0.44%, respectively, with almost all less than 5%, as calculated by SSC-LIBS. These results demonstrated that SSC-LIBS can improve the accuracy and stability of detecting major elements using only one standard sample, which can greatly promote the application of LIBS.

Quantitative determination of tantalum and niobium in tantalum-niobium ore using laser-induced breakdown spectroscopy.

Tantalum-niobium (Ta-Nb) ore is the main source of two very important rare metals,Ta and Nb. However, it is still a challenge for laser-induced breakdown spectroscopy (LIBS) to quantitatively detect trace Ta and Nb elements in Ta-Nb ore samples. In this work, LIBS assisted with univariate and multivariate calibration methods that were used to quantitatively determine Ta and Nb elements under optimized experimental parameters, such as delay time, gate width, and analytical lines. The results show that LIBS with multivariate calibration methods is a feasible method, and the limit of detection of Ta and Nb elements was 59.21 and 8.02 µg g-1, respectively. It provides a promising way for the rapid and sensitive quantitative detecting of trace Ta and Nb elements in Ta-Nb ore samples.

High-sensitivity determination of cadmium and lead in rice using laser-induced breakdown spectroscopy.

Stability and sensitivity of toxic elements determination is still unsatisfactory in agricultural product using laser-induced breakdown spectroscopy (LIBS). A simple and low cost sample pretreatment method named solid-liquid-solid transformation method was proposed in this work. The target analytes of cadmium (Cd) and lead (Pb) from rice samples were prepared through ultrasound assisted extraction in hydrochloric acid solution. The solution was dropped on the glass slide after centrifuging process and was further dried on a heater. Finally, the glass slide contained the analytes was carried out for LIBS determination. Compare with conventional pellet method, the spectral intensity of Cd and Pb element were enhanced significantly using LIBS. The limits of detection were 2.8 and 43.7 µg/kg, respectively. The limits of quantification were 9.3 and 145.7 µg/kg, respectively. The results demonstrated that LIBS coupled with ultrasound assisted extraction should be a promising tool to detect toxic elements in rice.

Spreading a water droplet through filter paper on the metal substrate for surface-enhanced laser-induced breakdown spectroscopy.

To improve the quantitative analysis accuracy of an aqueous solution using surface-enhanced laser-induced breakdown spectroscopy (SENLIBS), the filter paper was used as a transmission medium by placing it onto the surface of a metallic substrate to make the microdroplet spreading more uniform in a fixed region of the substrate surface. The trace elements (Cu, Pb, Cd, and Cr) in an aqueous solution were detected successfully using this method. The results showed that the sample preparation repeatability of SENLIBS was noticeably improved with the aid of filter paper. Moreover, the limit of detection (LoD) values was similar to those without filter paper. Furthermore, the R2 values were improved from 0.6192~0.9321 to 0.9481~0.9766, the RMSECV values were decreased from 0.53~1.95 µg/mL to 0.33~1.06 µg/mL, and the average relative error (ARE) values were decreased from 8.96~22.31% to 4.28~14.37% with the aid of filter paper. This demonstrated that the use of filter paper could improve the quantitative analysis accuracy of SENLIBS by increasing the sample preparation repeatability.

Classification accuracy improvement of laser-induced breakdown spectroscopy based on histogram of oriented gradients features of spectral images.

To improve the classification accuracy of laser-induced breakdown spectroscopy (LIBS), image histogram of oriented gradients (HOG) features method (IHFM) for materials analysis was proposed in this work. 24 rice (Oryza sativa L.) samples were carried out to verify the proposed method. The results showed that the classification accuracy of rice samples by the full-spectra intensities method (FSIM) and IHFM were 60.25% and 81.00% respectively. The classification accuracy was obviously improved by 20.75%. Universality test results showed that this method also achieved good results in the plastics, steel, rock and minerals classification. This study provides an effective method to improve the classification performance of LIBS.

Laser-induced breakdown spectroscopy assisted chemometric methods for rice geographic origin classification.

The problems of adulteration and mislabeling are very common in the food industry. Laser-induced breakdown spectroscopy (LIBS) coupled with chemometric methods has many intrinsic advantages on adulteration analysis of various materials. In this work, several chemometric algorithms, i.e., principal component analysis (PCA), decision tree (DT), random forest (RF), partial least squares discriminant analysis (PLS-DA), linear discriminant analysis (LDA), and support vector machine (SVM), were carried out assisted by LIBS technology to study the classification performances on rice geographic origins. A series of samples, including 20 kinds of rice samples from different geographic origins, was detected using LIBS with no pretreatment processes. For data analysis, PCA was employed to reduce the input variables, and to reduce the collinearity of LIBS spectral results as well. The results showed the classification accuracies of the mentioned chemometric algorithms of DT, RF, PLS-DA, LDA, and SVM with 89 input variables of 86.80%, 96.30%, 96.80%, 98.60%, and 99.20%, respectively. At the same time, the operation times of these algorithms were 3.81 s, 54.64 s, 3.63 s, 2.09 s, and 531.01 s, respectively. On the other hand, 30 principal components of input variables were also tested under the same conditions. The classification accuracies for the above algorithms were 81.60%, 98.00%, 95.70%, 98.40%, and 99.20%, respectively. The operation times were 2.01 s, 4.88 s, 3.67 s, 0.36 s, and 308.55 s, respectively. In addition, the five-fold cross-validation classification accuracies with 30 input variables for DT, RF, PLS-DA, LDA, and SVM were 83.75%, 97.95%, 94.75%, 98.35%, and 99.25%, respectively. As a result, LDA was demonstrated to be the best and most efficient tool for rice geographic origin classification assisted by LIBS with high accuracy and analytical speed, which has great potential for rapid identification of adulterated products in agriculture without use of any chemical reagent.

Determination of antimony in soil using laser-induced breakdown spectroscopy assisted with laser-induced fluorescence.

Antimony (Sb) in soil is attracting attention in the research community due to its potential toxicity and carcinogenicity. Traditional methods of detecting Sb lack the ability of rapid and nondigestion analysis, which hinders their development and application. Moreover, it is still a challenge for laser-induced breakdown spectroscopy (LIBS) to detect Sb in soil due to the weak intensities and intense interference of spectral lines. Here, LIBS, assisted with laser-induced fluorescence (LIBS-LIF), was used to selectively enhance the Sb's characteristic spectral lines under optimal parameters. The quantitative analysis performance was notably improved with a determination coefficient (R2) of 0.991, the limit of detection of 0.221 µg/g, and root mean square error of cross validation of 3.592 µg/g. These results demonstrate that LIBS-LIF has the potential to realize the rapid and accurate analysis of Sb in soil.

Analytical-performance improvement of aqueous solution by chemical replacement combined with surface-enhanced laser-induced breakdown spectroscopy.

In this study, chemical replacement combined with surface-enhanced laser-induced breakdown spectroscopy (CR-SENLIBS) was introduced for detecting the trace chromium (Cr) element in an aqueous solution, which could use chemical replacement to change the sample from liquid to solid. In order to illustrate the analytical-performance of the CR-SENLIBS, the direct analysis of the liquid surface by LIBS (LSLIBS) was investigated for comparison. The results show that the spectral intensity of Cr I 357.86 nm, plasma lifetime, and spectral stability were improved. Moreover, the limit of detection of Cr I 357.86 nm was 0.018 µg/mL, which was lower than 1.814 µg/mL for LSLIBS. Furthermore, the accuracy and precision were improved more than 60% and 80%, respectively; for example, the root-mean-square error of cross-validation was improved from 1.09 to 0.75 µg/mL, and the average relative standard deviation of the predicted concentration of Cr was reduced from 22.89% to 4.53% by using CR-SENLIBS. These results suggest that CR-SENLIBS has good analytical-performance, which exhibits great potential in water quality monitoring.

Identification of cervical cancer using laser-induced breakdown spectroscopy coupled with principal component analysis and support vector machine.

Cervical cancer is one of the most widespread diseases in women. Traditional cancer diagnosis is extremely complicated and relies on subjective interpretation of biopsy material. In this work, laser-induced breakdown spectroscopy (LIBS) was used in cervical cancer recognition. In order to improve identification accuracy of cervical cancer by LIBS, the chemometric methods of principal component analysis (PCA) and support vector machine (SVM) were combined. The results show that the content of trace elements in normal tissues and cervical cancer tissues was significantly different. Normalized peak intensities of Na, Mg, and K in the cervical cancer tissues were significantly higher than normal tissues, and the normalized peak intensities of Ca in the normal tissues were higher than cervical cancer tissues. The identification accuracies of PCA-SVM are better than SVM, with the achieved accuracies of 94.44% and 93.06%, respectively. It can be concluded that LIBS techniques coupled with chemometric method is a potential in cancer tissue identification, which provides a preliminary research basis for real-time diagnosis of cancer tissues using LIBS.

Analytical-performance improvement of laser-induced breakdown spectroscopy for the processing degree of wheat flour using a continuous wavelet transform.

Quality and safety of food are two of the most important matters in our lives. Wheat is one of the most important products in the modern agricultural processing industry. Issues of mislabeling and adulteration are of increasingly serious concern in the grain market. They threaten the credibility of producers and traders and the rights of the consumers. Therefore, it is very significant to guarantee the processing degree of wheat flour. In this work, two different spectral peak recognition methods, i.e., artificial spectral peak recognition and automatic spectral peak recognition, are carried out to study the adulteration problem in the food industry. Three grades of the processing degree of wheat flour from northern China are classified by laser-induced breakdown spectroscopy (LIBS). To search for an automatic classification model, continuous wavelet transform is used for the automatic recognition of the LIBS spectrum peak. Principal component analysis is used to reduce the collinearity of LIBS spectra data. First, 20 principal components were selected to represent the spectral data for the following discrimination analysis by a support vector machine. The results showed that the classification accuracies of automatic spectral peak recognition are better than those of artificial spectral peak recognition. The classification accuracies of artificial spectral peak recognition and automatic spectral peak recognition are 95.33% and 98.67%; the fivefold cross-validation classification accuracies are 94.67% and 96.67%; and the operation times were 240 min and 2 min, respectively. It can be concluded that LIBS can provide simpler and faster classification without the use of any chemical reagent, which represents a decisive advantage for applications dedicated to rapidly detecting the processing degree of wheat flour and other cereals.

Determination of Trace Available Heavy Metals in Soil Using Laser-Induced Breakdown Spectroscopy Assisted with Phase Transformation Method.

To detect available heavy metals in soil using laser-induced breakdown spectroscopy (LIBS) and improve its poor detection sensitivity, a simple and low cost sample pretreatment method named solid-liquid-solid transformation was proposed. By this method, available heavy metals were extracted from soil through ultrasonic vibration and centrifuging and then deposited on a glass slide. Utilization of this solid-liquid-solid transformation method, available Cd and Pb elements in soil were detected successfully. The results show that the regression coefficients of calibration curves for soil analyses reach to more than 0.98. The limits of detection could reach to 0.067 and 0.94 ppm for available Cd and Pb elements in soil under optimized conditions, respectively, which are much better than those obtained by conventional LIBS.

Multielemental self-absorption reduction in laser-induced breakdown spectroscopy by using microwave-assisted excitation.

The self-absorption effect seriously affects the accuracy of determination in laser-induced breakdown spectroscopy (LIBS). In this work, we proposed to reduce multielemental self-absorption within a wide spectral range (200-900 nm) by using microwave-assisted excitation in LIBS (MAE-LIBS). Self-absorption reduction of sodium (Na), potassium (K), aluminum (Al), silicon (Si), and calcium (Ca) in potassium feldspar using MAE-LIBS was investigated. The mechanisms of self-absorption reduction in MAE-LIBS were also investigated. The results show that the serious self-absorption of spectral lines (Na and K) was reduced. The full widths at half maximum (FWHMs) of Na I 589.0 nm, Na I 589.6 nm, K I 766.5 nm, and K I 769.9 nm in potassium feldspar were reduced by 43%, 43%, 53%, and 47%, respectively. MAE-LIBS also has a little FWHM reduction for spectral lines with weak self-absorption. The results demonstrate that MAE-LIBS can simultaneously reduce multielemental self-absorption.