Self-Absorption Effects on Electron Temperature-Measurements Utilizing Laser Induced Breakdown Spectroscopy (LIBS)-Techniques

In the present work, we have studied the temporal evolution of aluminum alloy plasma produced by the fundamental (1064 nm) of a Q-switched Nd:YAG laser by placing the target material in air at atmospheric pressure. The four Al I-neutral lines at 308.21, 309.27, 394.40 and 369.15 nm as well as Al II-ionic lines at 281.61, 385.64 and 466.30 nm are used for the determination of the electron temperature Te using Saha-Boltzmann plot method. The neutral aluminum lines were found to suffer from optical thickness which manifested itself on the form of scattered points around the Saha-Boltzmann line. The isolated optically thin hydrogen Hα-line at 656.27 nm appeared in the spectra under the same experimental conditions was used to correct the Al I-lines which contained some optical thickness. The measurements were repeated at different delay times ranging from 1 to 5 μs. The comparison between the deduced electron temperatures from aluminum neutral lines before correction against the effect self-absorption to that after correction revealed a precise value in temperature. The results sure that, in case of the presence of self-absorption effect the temperature varies from (1.4067 - 1.2548 eV) as the delay time is varied from 0 to 5 μs. Whereas, in the case of repairing against the effect, it varies from (1.2826 - 0.8961 eV) for the same delay time variation.

Laser-Induced Breakdown Spectroscopy (LIBS) Applied in the Differentiation of <i>Arabica</i>and <i>Robusta</i>Coffee

Coffee is one of the most consumed and commercialized crops in the world, which is why there is a potential risk to find arabica coffee (an expensive variety) adulterated with robusta coffee (a cheaper variety). The currently used technique for certifying coffee, High Performance Liquid Chromatography (HPLC), requires the sample to be subjected to a chemical treatment prior to analysis;in addition, the equipment is bulky and can not be moved easily. Laser Induced Breakdown Spectroscopy (LIBS) is a technique which does not require that samples be subjected to a chemical pretreatment, and equipment is small and portable, this can save valuable time in coffee trading. The purpose of this research was to demonstrate that LIBS can be applied to solve various problems related with the coffee authentication. Green coffee pills with different concentrations of arabica and robusta varieties were analyzed by LIBS, the results were used in the construction of calibration curves for the detection of the degree of simulated adulteration in coffee. It was found that the relative intensities of Ca (392.4 nm), Sr (407.1 nm), N (500.5 nm) and Na (588.7 nm), as well as the intensity ratios of Ca II (392.4 nm)/N I (500.5 nm), Sr I (407.1 nm)/N I (500.5 nm)and N I (500.5 nm)/Na I (588.7 nm) can be used for this purpose. It is concluded that the differentiation of coffee and the detection of its adulteration is possible with the use of LIBS. Further, with the use of an Artificial Neural Network (ANN) of type Multilayer Perceptron, it was possible to correctly classify the spectra of arabica and robusta roasted coffee.

时间分辨动态LIBS测量方法

针对激光诱导击穿光谱(LIBS)研究对时间分辨动态光谱测量方法的需求,建立了基于多通道光纤束的动态LIBS测量方法。该方法首先利用不同长度的光纤组成多通道光纤束,对瞬态LIBS信号进行差异延迟,使按照特定时间序列发射的光谱信号同步到达探测器,而后采用面阵ICCD相机对同步到达的多通道光谱信号进行高时间分辨探测。该方法单次测量即可获得LIBS辐射不同时刻的时间分辨光谱。为了验证基于多通道光纤束的动态LIBS测量方法,研制了具有19个通道的光纤束,光纤束中包含的各个单根光纤长度呈等差数列排布,长度差设置为10 m,对应测量的时间间隔约为50 ns,单次测量记录的总时间长度近900 ns。分别基于短脉冲激光光源和标准光源,开展了系统时间响应和光谱响应特性研究,获得了系统的时间响应数据和光谱响应曲线。用YAG激光器的二倍频激光(532 nm)诱导Si产生等离子体辐射光谱,在线测量了辐射光谱的时间演化历程,获得了Si等离子体辐射过程中SiⅠ390.52 nm,SiⅡ385.51 nm,SiⅡ413.12 nm谱线从0~898 ns时间范围内19个时刻的光谱信息,获得了特征光谱的演化规律,验证了该测量方法的可行性。结果表明,利用该测量方法,单次测量可以获得瞬态LIBS辐射过程中19个时刻的光谱参数,具有很高的测量效率。对于实验成本较高、运行频率低的激光诱导等离子体实验研究,采用该方法可以大大降低了测量成本,有效提升等离子体时间分辨动态光谱测量能力。

高精度煤质成分快速定量分析LIBS系统研究

煤质成分的快速、高精度定量分析是工厂对能源高效利用的重要环节。本文通过利用搭建的激光诱导击穿技术煤质快速分析仪,对所采集煤样工业特性固定碳(FixC),灰分(Ash),干燥无灰基的挥发分(Vdaf),热值(Q)进行了定量测量,并对测得的数据与实验室人工测量数据进行对比分析,检验得出该方法在煤质分析方面准确快速。通过对设备稳定性和动态精密度的测试,结果表明了快速煤质分析仪具有较高的稳定性,满足国标规定值。在预测灰分值分布跨度为5%~60%的煤样时,通过增加样品量,增加模型中对大灰分煤样的预测权重,实现预测均方根误差RMSEP<1%的预测精度,挥发分和全硫的RMSEP<1%,热值的RMSEP<0.18 MJ/kg。预测结果均达到工业分析要求,可以满足工业现场的应用需求,具有应用于煤质在线检测方面的广阔前景。

基于LIBS光谱实现燃煤企业碳排放量高精度快速预测

准确预测煤炭的碳排放数据是实现中国“双碳”目标的重要基础。在煤炭入炉前完成碳排放量数据和煤质指标的精确、快速预测,将转变目前“先排放,后检测”的碳排放数据计算方式,对落实“双碳”战略意义重大。以煤炭碳含量和煤质指标的精准预评估为研究目标,通过自行搭建激光诱导击穿光谱(Laser Induced Breakdown Spectroscopy,LIBS)系统和LIBS光谱统计分析,利用主成分分析-偏最小二乘(PCA-PLS)结合小样本算法对训练集进行回归训练,建立了一种煤炭的碳排放预测模型,并通过在新疆A电厂和山东B电厂中的实际应用,证明了LIBS系统在煤质指标分析中的可靠性。结果表明:所提出的预测方法与传统方法相比绝对误差最大为0.0256 t,表现出较好的碳排放预测能力。所提方法可以用于燃煤企业碳排放量的精准预测,为实现煤炭碳排放和煤质指标的预评估提供了一种较为高效的技术解决路径。

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.

Simultaneous Measurements of Coal Ash Composition by Laser-induced Breakdown Spectroscopy in Different Optical Collection

针对燃煤组分分布不均匀的特性，研究不同收光模式对激光诱导击穿光谱技术同步测量灰成分的影响。选用具有不同灰成分含量梯度的燃煤样品作为检测对象，对比分析同向收光和侧向收光下灰成分组成元素谱线信号探测的强度和稳定性及SiO2、Al2O3、Fe2O3、CaO、MgO和TiO2含量定量分析的精确度。研究结果表明，相同实验条件下同向收光模式的光谱信号稳定性和定量分析精确度更好，检验样品中各灰成分的预测值和参考值之间的拟合度均在0．986以上。而侧向收光模式下探测到的光谱信号强度更强，光谱探测下限可以达到190nm。

Laser Induced Breakdown Spectroscopy for Comparative Quantitative Analysis of Betel Leaves from Pakistan

Laser induced breakdown Spectroscopy(LIBS)was applied for the elemental analysis and exposure of the heavy metals in betel leaves in air.Pulsed Nd∶YAG(1064 nm)in conjunction with a suitable detector(LIBS 2000+,Ocean Optics,Inc)having the optical resolution of 0.06 nm was used to record the emission spectra from 220 to 720 nm.Elements like Al,Ba,Ca,Cr,Cu,P,Fe,K,Mg,Mn,Na,P,S,Sr,and Zn were found to present in the samples.The relative abundances of the observed elements were calculated through standard calibration curve method,integrated intensity ratio method,and weight percentage LIBS approach.LIBS findings were validated by comparing its results with the results obtained using a typical analytical technique of Inductively Coupled plasma-optical emission spectroscopy(ICP-OES).Limit of detection(LOD)of the LIBS system was also estimated for heavy metals.The experience gain through this work implies that LIBS could be highly applicable for testing the quality and purity of food products.

Laser-induced breakdown spectroscopy applied to the characterization of rock by support vector machine combined with principal component analysis

Laser-induced breakdown spectroscopy（LIBS） is a versatile tool for both qualitative and quantitative analysis.In this paper,LIBS combined with principal component analysis（PCA） and support vector machine（SVM） is applied to rock analysis.Fourteen emission lines including Fe,Mg,Ca,Al,Si,and Ti are selected as analysis lines.A good accuracy（91.38% for the real rock） is achieved by using SVM to analyze the spectroscopic peak area data which are processed by PCA.It can not only reduce the noise and dimensionality which contributes to improving the efficiency of the program,but also solve the problem of linear inseparability by combining PCA and SVM.By this method,the ability of LIBS to classify rock is validated.

基于聚类分析的土壤重金属分体式LIBS检测方法研究

土壤是人类赖以生存的物质基础,它的特性与人们的生产生活密切相关,传统土壤重金属检测方法如原子吸收光谱法、电感耦合等离子体质谱法分析能力较弱且价格昂贵,因此亟需一种开发低成本易操作的土壤多种元素同时定量分析方法。激光诱导击穿光谱(LIBS)技术因其分析快速、多元素同时分析等优点被广泛关注,但由于其体积较大不便于携带并且大多应用于实验室分析,为了满足现场检测的需求,研制了一台分体式现场LIBS检测仪,其设计是将仪器分为探测头和机箱两部分并通过包塑管进行连接,采用微型二极管泵浦激光器,脉冲能量可达100mJ,波长1064nm,重复频率为1~10Hz;此外采用多通道高分辨率光谱仪,提高LIBS的分析性能;为了减小辐射背景干扰,利用FPGA实现μs级延迟时间功能。对其应用在11种土壤获取光谱数据,实验设置脉冲能量为100mJ,延迟时间设为1μs,积分时间2ms,每个样品采集10个不同位置的光谱,每个位置测量20次,共采集200个光谱数据,为减少噪声干扰,对每个样品的光谱数据进行均值预处理后再进行Beads算法基线校正,利用PCA主成分分析得到贡献率最大的3个主成分分量,再通过Kmeans++算法对不同地区不同类型的11种土壤进行聚类分析,将相同类别的土壤代入偏最小二乘(PLSR)算法,每个元素选取两个特征谱线以及上下各10个点来增强光谱信息,选择一种样品作为预测对Cu、Cr、Ni、Co、Cd五种土壤重金属元素进行定量分析。结果表明,与未进行聚类分析相比,此方法可明显提高元素的拟合相关系数,五种重金属元素的相关系数分别从0.953、0.992、0.989、0.982、0.99提高至0.999、0.998、0.9995、0.9965、0.993,相关系数均达到0.99及以上满足LIBS线性分析要求,其预测结果与实际含量之间的平均相对误差分别从83.45%、16.03%、22.94%、43.91%、125.768%提高至1.14%、0.99%、0.895%、1.879%、1.862%,可以发现经过聚类分析后,其预测误差大大降低,均在5%以内,具有较好的分析性能,五种元素的相关系数和预测误差相比于直接进行PLSR方法均有提升。PCA与Kmeans++结合的方法能够更准确的进行聚类,在降维后进行聚类可以减少噪声和冗余信息的影响,加快计算速度,减少异常点对聚类效果的影响提高鲁棒性。

Quantitative analysis of C, Si, Mn, Ni, Cr and Cu in low-alloy steel under ambient conditions via laser-induced breakdown spectroscopy

A diode-pumped solid-state laser （DPSSL） with a high energetic stability and long service life is applied to ablate the steel samples instead of traditional Nd：YAG laser pumped by a xenon lamp, and several factors, such as laser pulse energy, repetition rate and argon flow rate, that influence laser-induced breakdown spectroscopy （LIBS） analytical performance are investigated in detail. Under the optimal experiment conditions, the relative standard deviations for C, Si, Mn, Ni, Cr and Cu are 3.3%-8.9%, 0.9%-2.8%, 1.2%-4.1%, 1.7%-3.0%, 1.1%-3.4% and 2.5%-8.5%, respectively, with the corresponding relative errors of 1.1%-7.9%, 1.0%-6.3%, 0.4%-3.9%, 1.5%-6.3%, 1.2%-4.0% and 1.2%-6.4%. Compared with the results of the traditional spark discharge optical emission spectrometry technique, the analytical performance of LIBS is just a little inferior due to the less stable laser-induced plasma and smaller amount of ablated sample by the laser. However, the precision, detection limits and accuracy of LIBS obtained in our present work were sufficient to meet the requirements for process analysis. These technical performances of higher stability of output energy and longer service life for DPSSL, in comparison to the Q-switch laser pumped by xeon lamp, qualify it well for the real time online analysis for different industrial applications.

Application of Laser Induced Breakdown Spectroscopy in Early Detection of Red Palm Weevil:(Rhynchophorus ferrugineus)Infestation in Date Palm

The Kingdom of Saudi Arabia is one of the leading date producing countries. Unfortunately, this important fruit crop is under great threat from the red palm weevil （RPW） （Rhynchophorus ferrugineus）, which is a highly invasive pest. Several techniques, including visual inspection, acoustic sensors, sniffer dogs, and pheromone traps have been tried to detect the early stages of a RPW infestation; however, each method has suffered certain logistical and implementation issues. We have applied laser induced breakdown spectroscopy （LIBS） for the early detection of RPW infestation. Through the analysis of the observed LIBS spectra of different infested and healthy samples, we have found presence of Ca, Mg, Na, C, K elements and OH, CN molecules. The spectra also reveal that with the population growth of the pest, the intensity of Mg and Ca atomic lines in LIBS spectra increases rapidly. Similar behavior is observed in the molecular lines of LIBS spectra. The obtained results indicate that the LIBS technique can be used for the early detection of RPW infestation without damaging the date palms.

Determination of Iron in Water Solution by Time-Resolved Femtosecond Laser-Induced Breakdown Spectroscopy

The influence of the energy of femtosecond laser pulses on the intensity of Fe I （371.99 nm） emission line and the continuous spectrum of the plasma generated on the surface of Fe^3＋ water solution by a Ti： sapphire laser radiation with pulse duration 〈45 fs and energies up to 7 mJ is determined. A calibration curve was obtained for Fe3＋ concentration range from 0.5 g/L to the limit of detection in water solution, and its saturation was detected for concentrations above 0.25 g/L, which is ascribed to self-absorption. The 3σ- limit of detection obtained for Fe in water solution is 2.6 mg/L in the case of 7 mJ laser pulse energy. It is found that an increase of laser pulse energy insignificantly affects on LOD in the time-resolved LIBS and leads to a slight improvement of the limit of detection.

Characterization of the Delamination Defects in Marine Steel Using Laser-Induced Breakdown Spectroscopy

In this paper, two types of comparison analyses, bulk analysis and defect analysis, were carried out for marine steel. The results of laser-induced breakdown spectroscopy （LIBS） were compared with those of spark optical emission spectrometry （Spark-OES） and scanning electron microscopy/energy dispersion spectroscopy （SEM/EDS） in the bulk and defect analyses. The comparison of the bulk analyses shows that the chemical contents of C, Si, Mn, P, S and Cr obtained from LIBS agree well with those determined using Spark-OES. The LIBS is slightly less precise than Spark-OES. Defects were characterized in the two-dimensional distribution analysis mode for Al, Mg, Ca, Si and other elements. Both the LIBS and SEM/EDS results show the enrichment of Al, Mg, Ca and Si at the defect position and the two methods agree well with each other. SEM/EDS cannot provide information about the difference in the chemical constituents when the differences between the defect position and the normal position are not significant. However, LIBS can provide this information, meaning that the sensitivity of LIBS is higher than that of SEM/EDS. LIBS can be used to rapidly characterize marine steel defects and provide guidance for improving metallurgical processes.

Development of a Laboratory Cement Quality Analysis Apparatus Based on Laser-Induced Breakdown Spectroscopy

Determination of the chemical composition of cement and ratio values of clinker plays an important role in cement plants as part of the optimal process control and product quality evaluation. In the present paper, a laboratory laser-induced breakdown spectroscopy （LIBS） apparatus mainly comprising a sealed optical module and an analysis chamber has been designed for possible application in cement plants for on-site quality analysis of cement. Emphasis is placed on the structure and operation of the LIBS apparatus, the sealed optical path, the temperature controlled spectrometer, the sample holder, the proper calibration model established for minimizing the matrix effects, and a correction method proposed for overcoming the ＇drift＇ obstacle. Good agreement has been found between the laboratory measurement results from the LIBS method and those from the traditional method. The absolute measurement errors presented here for oxides analysis are within 0.5%, while those of ratio values are in the range of 0.02 to 0.05. According to the obtained results, this laboratory LIBS apparatus is capable of performing reliable and accurate, composition and proximate analysis of cement and is suitable for application in cement plants.

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 R_c^2?=?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 R_v^2?=?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 R_v^2?=?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 R_v^2?=?0.9968 and RMSEV?=?0.0785. CNN analysis of time-resolved LIBS is capable of improving the determination of K in soil.

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.

A highly-sensitive automatic transient laser-induced breakdown spectroscopy system with high temporal and spatial resolution

A highly-sensitive automatic transient laser-induced breakdown spectroscopy （LIBS） system is designed and integrated. It successfully avoids the delay time selecting problem in the conventional LIBS system, and realizes the LIBS data acquisition with high spatiotemporal resolution automatically. Multiple transient spectra can be obtained in each measurement, which will provide more information for spectral research. The water-vapour and liquid-water Raman scattering spectra are captured by this system, and the comparison of experimental water-vapour Raman scattering spectrum with theoretical data verifies the reliability of the LIBS system. Based on this system, the air laser induced air breakdown spectra are captured and analysed. The system is also useful for the research on water-vapour Raman Lidar remote sensing.

Parameters Optimization of Laser-Induced Breakdown Spectroscopy Experimental Setup for the Case with Beam Expander

Improvement of measurement precision and repeatability is one of the issues currently faced by the laser-induced breakdown spectroscopy （LIBS） technique, which is expected to be capable of precise and accurate quantitative analysis. It was found that there was great potential to improve the signal quality and repeatability by reducing the laser beam divergence angle using a suitable beam expander （BE）. In the present work, the influences of several experimental parameters for the case with BE are studied in order to optimize the analytical performances： the signal to noise ratio （SNR） and the relative standard deviation （RSD）. We demonstrate that by selecting the optimal experimental parameters, the BE-included LIBS setup can give higher SNR and lower RSD values of the line intensity normalized by the whole spectrum area. For validation purposes, support vector machine （SVM） regression combined with principal component analysis （PCA） was used to establish a calibration model to realize the quantitative analysis of the ash content. Good agreement has been found between the laboratory measurement results from the LIBS method and those from the traditional method. The measurement accuracy presented here for ash content analysis is estimated to be 0.31%, while the average relative error is 2.36%.

Comparison of Calibration Curve Method and Partial Least Square Method in the Laser Induced Breakdown Spectroscopy Quantitative Analysis

The Laser Induced Breakdown Spectroscopy (LIBS) is a fast, non-contact, no sample preparation analytic technology;it is very suitable for on-line analysis of alloy composition. In the copper smelting industry, analysis and control of the copper alloy concentration affect the quality of the products greatly, so LIBS is an efficient quantitative analysis tech- nology in the copper smelting industry. But for the lead brass, the components of Pb, Al and Ni elements are very low and the atomic emission lines are easily submerged under copper complex characteristic spectral lines because of the matrix effects. So it is difficult to get the online quantitative result of these important elements. In this paper, both the partial least squares (PLS) method and the calibration curve (CC) method are used to quantitatively analyze the laser induced breakdown spectroscopy data which is obtained from the standard lead brass alloy samples. Both the major and trace elements were quantitatively analyzed. By comparing the two results of the different calibration method, some useful results were obtained: both for major and trace elements, the PLS method was better than the CC method in quantitative analysis. And the regression coefficient of PLS method is compared with the original spectral data with background interference to explain the advantage of the PLS method in the LIBS quantitative analysis. Results proved that the PLS method used in laser induced breakdown spectroscopy was suitable for simultaneous quantitative analysis of different content elements in copper smelting industry.