Study on Cluster Analysis Used with Laser-Induced Breakdown Spectroscopy

Supervised learning methods(eg.PLS-DA,SVM,etc.) have been widely used with laser-induced breakdown spectroscopy(LIBS) to classify materials;however,it may induce a low correct classification rate if a test sample type is not included in the training dataset.Unsupervised cluster analysis methods(hierarchical clustering analysis,K-means clustering analysis,and iterative self-organizing data analysis technique) are investigated in plastics classification based on the line intensities of LIBS emission in this paper.The results of hierarchical clustering analysis using four different similarity measuring methods(single linkage,complete linkage,unweighted pair-group average,and weighted pair-group average) are compared.In K-means clustering analysis,four kinds of choosing initial centers methods are applied in our case and their results are compared.The classification results of hierarchical clustering analysis,K-means clustering analysis,and ISODATA are analyzed.The experiment results demonstrated cluster analysis methods can be applied to plastics discrimination with LIBS.     

Quantitative analysis and time-resolved characterization of simulated tokamak exhaust gas by laser-induced breakdown spectroscopy

Tokamak exhaust is an important part of the deuterium-tritium fuel cycle system in fusion reactions. In this work, we present a laser-induced breakdown spectroscopy (LIBS)-based method to monitor the gas compositions from the exhaust system in the tokamak device. Helium (He), a main impurity in the exhaust gas, was mixed with hydrogen (H2) in different ratios through a self-designed gas distribution system, and sealed into a measurement chamber as a standard specimen. A 532 nm wavelength laser pulse with an output power of 100 mJ was used for plasma excitation. The time-resolved LIBS is used to study the time evolution characteristics of the signal strength, signal-to-background ratio (SBR), signal-to-noise ratio (SNR) and relative standard deviation (RSD) of the helium and hydrogen characteristic lines. The Boltzmann two-line method was employed to estimate the plasma temperature of laser-induced plasma (LIP). The Stark-broadened profile of He I 587.56 nm was exploited to measure the electron density. From these studies, an appropriate time was determined in which the low RSD% was consistent with the high signal-to-noise ratio. The He I 587.56 nm and Hα emission lines with good signal-to-noise ratio were extracted from the spectrum and used in the external standard method and internal standard method for quantitative analysis. The test results for mixed gas showed that the average relative error of prediction was less than 11.15%, demonstrating the great potential of LIBS in detecting impurities in plasma exhaust gas.     

Hybrid classification of coal and biomass by laser-induced breakdown spectroscopy combined with K-means and SVM

Laser-induced breakdown spectroscopy(LIBS) is a new technology suitable for classification of various materials. This paper proposes a hybrid classification scheme for coal, municipal sludge and biomass by using LIBS combined with K-means and support vector machine(SVM)algorithm. In the study, 10 samples were classified in 3 groups without supervision by K-means clustering, then a further supervised classification of 6 kinds of biomass samples by SVM was carried out. The results show that the comprehensive accuracy of the hybrid classification model is over 98%. In comparison with the single SVM classification model, the hybrid classification model can save 58.92% of operation time while guaranteeing the accuracy. The results demonstrate that the hybrid classification model is able to make an efficient, fast and accurate classification of coal, municipal sludge and biomass, furthermore, it is precise for the detection of various kinds of biomass fuel.     

A Study of the Laser-Induced Breakdown Spectroscopy of Carbon in the Ultraviolet Wavelength Range Under Vacuum Conditions

The influence of a vacuum on the laser-induced breakdown spectroscopy(LIBS) of carbon in the ultraviolet wavelength range is studied.Experiments are performed with graphite using a LIBS system,which consists of a 1064 nm Nd:YAG laser,a vacuum pump,a spectrometer and a vacuum chamber.The vacuum varies from 10 Pa to 1 atm.Atomic lines as well as singly and doubly charged ions are confirmed under the vacuums.A temporal evolution analysis of intensity is performed for the atomic lines of C Ⅰ 193.09 nm and C Ⅰ 247.86 nm under different vacuum conditions.Both time-integrated and time-resolved intensity evolutions under vacuums are achieved.The lifetimes of the two atomic lines have similar trends,which supports the point of view of a 'soft spot'.Variations of plasma temperature and electron density under different vacuums are measured.This study is helpful for research on carbon detection using LIBS under vacuum conditions.     

Simultaneous Determination of Trace Lead and Chromium in Water Using Laser-Induced Breakdown Spectroscopy and Paper Substrate

Toxic metals such as lead and chromium in aqueous solutions have been analyzed simultaneously by laser-induced breakdown spectroscopy(LIBS), in which the ordinary printing paper is used as a liquid absorber which was immerged into Pb(NO3)2and Cr(NO3)3aqueous solution to enrich the heavy metals. This method overcomes the drawbacks of splashing and low sensitivity in ordinary LIBS analysis of water, in which a laser beam is directly focused on a liquid surface. A good signal intensity and reproducibility has been demonstrated. The Pb 405.78 nm and Cr 427.48 nm spectral lines are used as the analytical lines. The variation of line intensity with immersion time was investigated. The calibration curve for quantitative measurement of Pb and Cr in water was established, and the detection limits are 0.033 mg/L and 0.026 mg/L respectively,which is about 2-3 orders of magnitude better than that in the ordinary LIBS analysis of heavy metal in solution.     

Relative spectral response calibration using Ti plasma lines

This work introduces the branching ratio(BR) method for determining relative spectral responses,which are needed routinely in laser induced breakdown spectroscopy(LIBS). Neutral and singly ionized Ti lines in the 250–498 nm spectral range are investigated by measuring laser-induced micro plasma near a Ti plate and used to calculate the relative spectral response of an entire LIBS detection system. The results are compared with those of the conventional relative spectral response calibration method using a tungsten halogen lamp, and certain lines available for the BR method are selected. The study supports the common manner of using BRs to calibrate the detection system in LIBS setups.     

Enhancement of optical emission generated from femtosecond double-pulse laser-induced glass plasma at different sample temperatures in air

In double-pulse laser-induced breakdown spectroscopy(DP-LIBS), the collinear femtosecond double-pulse laser configuration is experimentally investigated with different initial sample temperatures using a Ti:sapphire laser. The glass sample is ablated to produce the plasma spectroscopy. During the experiment, the detected spectral lines include two Na(I) lines(589.0 nm and 589.6 nm) and one Ca(I) line at the wavelength of 585.7 nm. The emission lines are measured at room temperature(22 ℃) and three higher initial sample temperatures(T_s?=?100 ℃, 200 ℃, and 250 ℃). The inter-pulse delay time ranges from-250 ps to 250 ps.The inter-pulse delay time and the sample temperature strongly influence the spectral intensity,and the spectral intensity can be significantly enhanced by increasing the sample temperature and selecting the optimized inter-pulse time. For the same inter-pulse time of 0 ps(single-pulse LIBS), the enhancement ratio is approximately 2.5 at T_s?=?200 ℃ compared with that obtained at T_s?=?22 ℃. For the same inter-pulse time of 150 ps, the enhancement ratio can be up to 4 at T_s?=?200 ℃ compared with that obtained at T_s?=?22 ℃. The combined enhancement effects of the different initial sample temperatures and the double-pulse configuration in femtosecond LIBS are much stronger than that of the different initial sample temperatures or the double-pulse configuration only.     

The classification of plants by laser-induced breakdown spectroscopy based on two chemometric methods

The applications of laser-induced breakdown spectroscopy(LIBS) on classifying complex natural organics are relatively limited and their accuracy still requires improvement.In this work,to study the methods on classification of complex organics,three kinds of fresh leaves were measured by LIBS.100 spectra from 100 samples of each kind of leaves were measured and then they were divided into a training set and a test set in a ratio of 7:3.Two algorithms of chemometric methods including the partial least squares discriminant analysis(PLS-DA) and principal component analysis Mahalanobis distance(PCA-MD) were used to identify these leaves.By using 23 lines from 16 elements or molecules as input data,these two methods can both classify these three kinds of leaves successfully.The classification accuracies of training sets are both up to 100% by PCA-MD and PLS-DA.The classification accuracies of the test set are 93.3% by PCA-MD and 97.8% by PLS-DA.It means that PLS-DA is better than PCA-MD in classifying plant leaves.Because the components in PLS-DA process are more suitable for classification than those in PCA-MD process.We think that this work can provide a reference for plant traceability using LIBS.     

气体采样滤膜中钚的激光诱导击穿光谱定量分析研究

在核设施排放物的监测中,为确保环境安全及实现核材料衡算,需针对通风管气体采样滤膜中钚的含量进行分析。为探索利用激光诱导击穿光谱（LIBS）技术定量分析滤膜中钚元素含量的可行性,开展了某核设施热室内含钚气体采样滤膜的LIBS分析研究。通过分析含钚气体采样滤膜中钚的LIBS特征光谱信号,筛选出钚的有效发射谱线,并优化LIBS测量延迟时间参数,最终得到了浓度范围较低情况下的定量标准曲线,并进行了技术验证分析。研究结果显示,针对滤膜中的钚元素可采用有效特征谱线进行LIBS定量分析,能用于定量分析钚的可分析有效特征谱线为PuⅡ 443.298 nm、PuⅠ 460.721 nm、PuⅡ 466.389 nm。分析结果表明,LIBS分析结果的精度好于3%。     

Nondestructive Determination of Cu Residue in Orange Peel by Laser Induced Breakdown Spectroscopy

Laser induced breakdown spectroscopy(LIBS) is an emerging tool with rapid,nondestructive,green characteristics in qualitative or quantitative analyses of composition in materials.But LIBS has its shortcomings in detect limit and sensitivity.In this work,heavy metal Cu in Gannan Navel Orange,which is one of famous fruits from Jiangxi of China,was analyzed.In view of LIBS's limit,it is difficult to determinate heavy metals in natural fruits.In this work,nine orange samples were pretreated in 50-500 μg/mL Cu solution,respectively.Another one orange sample was chosen as a control group without any pollution treatment.Previous researchers observed that the content of heavy metals is much higher in peel than in pulp.So,the content in pulp can be reflected by detecting peel.The real concentrations of Cu in peels were acquired by atomic absorption spectrophotometer(AAS).A calibration model of Cu I 324.7 and Cu Ⅰ 327.4was constructed between LIBS intensity and AAS concentration by six samples.The correlation coefficient of the two models is also 0.95.All of the samples were used to verify the accuracy of the model.The results show that the relative error(RE) between predicted and real concentration is less than 6.5%,and Cu Ⅰ 324.7 line has smaller RE than Cu Ⅰ 327.4.The analysis demonstrated that different characteristic lines decided different accuracy.The results prove the feasibility of detecting heavy metals in fruits by LIBS.But the results are limited in treated samples.The next work will focus on direct analysis of heavy metals in natural fruits without any pretreatment.This work is helpful to explore the distribution of heavy metals between pulp and peel.     

Quantitative analysis of saindha salt using laser induced breakdown spectroscopy and cross-validation with ICP-MS

Saindha salt is considered to be more advantageous than the other edible salts for the patients suffering from diabetes,blood pressure and kidney diseases.To explore the constituent elements of this salt,laser induced breakdown spectroscopy(LIBS) has been exploited for its qualitative and quantitative analysis.The third harmonic(355 nm) of a Q-switched Nd:YAG laser has been used to produce the saindha salt plasma and the time integrated optical emission spectra were registered using a set of six miniature spectrometers covering the spectral range of 230-805 nm.The spectroscopic analysis of the emission spectra predominately revealed numerous neutral or singly ionized emission lines of Ca,Mg,Na,K,Fe,Sr,Si,Li and Al.The laser produced plasma was characterized by calculating the electron temperature from the Boltzmann plots and the electron number density from the Stark broadened line profile as a function of laser irradiance and distance from the target sample.The relative concentration of the constituent elements was extracted by the integrated line intensities of the strongest spectral line of each element using the self-calibration-LIBS(SC-LIBS) and one-line calibration free-LIBS(OLCF-LIBS) methods.For cross-validation,the LIBS results have been compared with that obtained from the inductively coupled plasma-mass spectroscopy(ICP-MS) showing good agreement.     

Preliminary results of in situ laser-induced breakdown spectroscopy for the first wall diagnostics on EAST

Post-mortem methods cannot fulfill the requirement of monitoring the lifetime of the plasma facing components(PFC) and measuring the tritium inventory for the safety evaluation.Laserinduced breakdown spectroscopy(LIBS) is proposed as a promising method for the in situ study of fuel retention and impurity deposition in a tokamak.In this study,an in situ LIBS system was successfully established on EAST to investigate fuel retention and impurity deposition on the first wall without the need of removal tiles between plasma discharges.Spectral lines of D,H and impurities(Mo,Li,Si,...) in laser-induced plasma were observed and identified within the wavelength range of 500-700 nm.Qualitative measurements such as thickness of the deposition layers,element depth profile and fuel retention on the wall are obtained by means of in situ LIBS.The results demonstrated the potential applications of LIBS for in situ characterization of fuel retention and co-deposition on the first wall of EAST.     

Improvement in classification accuracy of stainless steel alloys by laser-induced breakdown spectroscopy based on elemental intensity ratio analysis

Laser-induced breakdown spectroscopy(LIBS) is a useful technique for accurate sorting of metal scrap by chemical composition analysis.In this work,a method for intensity-ratiobased LIBS classification of stainless steel applicable to highly fluctuating LIBS signal conditions is proposed.The spectral line pairs for intensity ratio calculation are selected according to elemental concentration and upper levels of emission lines.It is demonstrated that the classification accuracy can be significantly improved from that of full-spectra principal component analysis or intensity-based analysis.The proposed method is considered to be suited to an industrial scrap sorting system that requires minimal maintenance and low system price.     

Microanalysis of Multi-Element in Juncus effusus L. by LIBS Technique

Laser-induced breakdown spectroscopy (LIBS) was used to decipher the unique multi-elemental characteristics of Juncus e?usus L. The spectral fingerprints of Juncus e?usus L. were established based on elemental microanalysis via LIBS. Microanalysis and multimode sam?pling methodologies were designed in this study. The relative standard deviation (RSD) approach was performed to optimize the multi-shot measurements. Taking advantage of the capability with no or minimal sample pre-treatment of LIBS, a thermodynamic chart of four elements (Mg, Ca, Ba, and Na) was created from twelve collection regions. The diagram of elemental distribution on a micro-scale was generated to explore the nature of Juncus e?usus L. by LIBS. The results demon?strated that LIBS is a promising technique for rapid elemental microanalysis of heterogeneous samples.     

Detection of K in soil using time-resolved laser-induced breakdown spectroscopy based on convolutional neural networks

One of the technical bottlenecks of traditional laser-induced breakdown spectroscopy (LIBS) is the difficulty in quantitative detection caused by the matrix effect. To troubleshoot this problem, this paper investigated a combination of time-resolved LIBS and convolutional neural networks (CNNs) to improve K determination in soil. The time-resolved LIBS contained the information of both wavelength and time dimension. The spectra of wavelength dimension showed the characteristic emission lines of elements, and those of time dimension presented the plasma decay trend. The one-dimensional data of LIBS intensity from the emission line at 766.49 nm were extracted and correlated with the K concentration, showing a poor correlation of R²_c=0.0967, which is caused by the matrix effect of heterogeneous soil. For the wavelength dimension, the two-dimensional data of traditional integrated LIBS were extracted and analyzed by an artificial neural network (ANN), showing R²_v=0.6318 and the root mean square error of validation (RMSEV)=0.6234. For the time dimension, the two-dimensional data of time-decay LIBS were extracted and analyzed by ANN, showing R²_v=0.7366 and RMSEV=0.7855. These higher determination coefficients reveal that both the non-K emission lines of wavelength dimension and the spectral decay of time dimension could assist in quantitative detection of K. However, due to limited calibration samples, the two-dimensional models presented over-fitting. The three-dimensional data of time-resolved LIBS were analyzed by CNNs, which extracted and integrated the information of both the wavelength and time dimension, showing the R²_v=0.9968 and RMSEV=0.0785. CNN analysis of time-resolved LIBS is capable of improving the determination of K in soil.     

A rapid classification method of aluminum alloy based on laser-induced breakdown spectroscopy and random forest algorithm

As an important non-ferrous metal structural material most used in industry and production,aluminum(Al) alloy shows its great value in the national economy and industrial manufacturing.How to classify Al alloy rapidly and accurately is a significant, popular and meaningful task.Classification methods based on laser-induced breakdown spectroscopy(LIBS) have been reported in recent years. Although LIBS is an advanced detection technology, it is necessary to combine it with some algorithm to reach the goal of rapid and accurate classification. As an important machine learning method, the random forest(RF) algorithm plays a great role in pattern recognition and material classification. This paper introduces a rapid classification method of Al alloy based on LIBS and the RF algorithm. The results show that the best accuracy that can be reached using this method to classify Al alloy samples is 98.59%, the average of which is 98.45%. It also reveals through the relationship laws that the accuracy varies with the number of trees in the RF and the size of the training sample set in the RF. According to the laws, researchers can find out the optimized parameters in the RF algorithm in order to achieve,as expected, a good result. These results prove that LIBS with the RF algorithm can exactly classify Al alloy effectively, precisely and rapidly with high accuracy, which obviously has significant practical value.     

Rapid Detection of Oil Pollution in Soil by Using Laser-Induced Breakdown Spectroscopy

Detection of oil pollution in soil has been carried out using laser-induced breakdown spectroscopy(LIBS). A pulsed neodymium-doped yttrium aluminum garnet(Nd:YAG) laser(1,064 nm, 8 ns, 200 mJ) was focused onto pelletized soil samples. Emission spectra were obtained from oil-contaminated soil and clean soil. The contaminated soil had almost the same spectrum profile as the clean soil and contained the same major and minor elements. However, a C–H molecular band was clearly detected in the oil-contaminated soil, while no C–H band was detected in the clean soil. Linear calibration curve of the C–H molecular band was successfully made by using a soil sample containing various concentrations of oil. The limit of detection of the C–H band in the soil sample was 0.001 mL/g. Furthermore, the emission spectrum of the contaminated soil clearly displayed titanium(Ti) lines, which were not detected in the clean soil. The existence of the C–H band and Ti lines in oil-contaminated soil can be used to clearly distinguish contaminated soil from clean soil. For comparison, the emission spectra of contaminated and clean soil were also obtained using scanning electron microscope-energy dispersive X-ray(SEM/EDX) spectroscopy,showing that the spectra obtained using LIBS are much better than using SEM/EDX, as indicated by the signal to noise ratio(S/N ratio).     

Rapid identification of volatile organic compounds and their isomers in the atmosphere

Isomers are widely present in volatile organic compounds (VOCs), and it is a tremendous challenge to rapidly distinguish the isomers of VOCs in the atmosphere. In this work, laser-induced breakdown spectroscopy (LIBS) technology was developed to online distinguish VOCs and their isomers in the air. First, LIBS was used to directly detect halogenated hydrocarbons (a typical class of VOCs) and the characteristic peaks of the related halogens were observed in the LIBS spectra. Then, comparing the LIBS spectra of various samples, it was found that for VOCs with different molecular formulas, although the spectra are completely the same in elemental composition, there are still significant differences in the relative intensity of the spectral lines and other information. Finally, in light of the shortcomings of traditional LIBS technology in identifying isomers, machine learning algorithms were introduced to develop the LIBS technique to identify the isomers of atmospheric VOCs, and the recognition results were very good. It is proved that LIBS combined with machine learning algorithms is promising for online traceability of VOCs in the atmospheric environment.     

Quantitative analysis of steel and iron by laser-induced breakdown spectroscopy using GA-KELM

According to the multiple researches in the last couple of years, laser-induced breakdown spectroscopy(LIBS) has shown a great potential for rapid analysis in steel industry.Nevertheless, the accuracy and precision may be limited by complex matrix effect and selfabsorption effect of LIBS seriously. A novel multivariate calibration method based on genetic algorithm-kernel extreme learning machine(GA-KELM) is proposed for quantitative analysis of multiple elements(Si, Mn, Cr, Ni, V, Ti, Cu, Mo) in forty-seven certified steel and iron samples.First, the standardized peak intensities of selected spectra lines are used as the input of model.Then, the genetic algorithm is adopted to optimize the model parameters due to its obvious capability in finding the global optimum solution. Based on these two steps above, the kernel method is introduced to create kernel matrix which is used to replace the hidden layer's output matrix. Finally, the least square is applied to calculate the model's output weight. In order to verify the predictive capability of the GA-KELM model, the R-square factor(R~2), Root-meansquare Errors of Calibration(RMSEC), Root-mean-square Errors of Prediction(RMSEP) of GAKELM model are compared with the traditional PLS algorithm, respectively. The results confirm that GA-KELM can reduce the interference from matrix effect and self-absorption effect and is suitable for multi-elements calibration of LIBS.     

The Enhanced Effect of Optical Emission from Laser Induced Breakdown Spectroscopy of an Al-Li Alloy in the Presence of Magnetic Field Confinement

In this paper,the influence of magnetic field strength on laser-induced breakdown spectroscopy(LIBS) has been investigated for various pressures.The plasma plume was produced by employing Q-switch Nd:YAG laser ablation of an Al-Li alloy operating at a 1064 nm wavelength.The results indicated that the LIBS intensity of the Al and Li emission lines is boosted with an increase of magnetic strength.Typically,the intensity of the Al Ⅰ and Li Ⅰ spectral emissions can be magnified by 1.5-3 times in a steady magnetic field of 1.1 T compared with the field-free case.Also,in this investigation we recorded time-resolved images of the laser-produced plume by employing a fast ICCD camera.The results show that the luminance of the plasma is enhanced and the time of persistence is increased significantly,and the plasma plume splits into two lobes in the presence of a magnetic field.The probable reason for the enhancement is the magnetic confinement effect which increases the number density of excited atoms and the population of species in a high energy state.In addition,the electron temperature and density are also augmented by the magnetic field compared to the field-free case.