激光诱导击穿光谱定量分析全血中的锂元素

锂（Li）盐作为一种精神科药物常被用于治疗重性抑郁障碍,然而长期服用Li盐会产生高中毒风险,及时监测患者血液中Li元素的浓度,对确保用药安全和临床治疗效果非常重要。激光诱导击穿光谱（Laser-induced breakdown spectroscopy, LIBS）作为一种快速分析技术,被广泛应用于实际场景下复杂基质的元素分析。本研究采用LIBS技术结合偏最小二乘法（Partial least squares, PLS）对血液基质中的Li元素进行定量分析。采用45组临床血液样品,分别构建血浆和全血基质下Li元素的定量分析模型,通过五折交叉验证方法对PLS算法中的潜变量数进行优化。结果表明,基于血浆基质构建的PLS定量分析模型预测决定系数（R2）为0.992,预测均方根误差（RMSEP）为0.204μg/mL,相对标准偏差（RSD）为2.14%;基于全血基质构建的PLS定量分析模型R2为0.984, RMSEP为0.728μg/mL, RSD为3.45%,因此,基于血浆定标值所建立的LIBS模型定量分析全血中锂元素的效果更佳。LIBS技术为临床血锂的快速检测评估提供了一种新的选择,具有...     

激光诱导击穿光谱(LIBS)结合机器学习算法快速测定石油焦中微量元素

石油焦中微量元素对其作为预焙阳极的性能起着决定性的作用。首先,通过基于LIBS光谱构建用于石油焦中铁(Fe)和铜(Cu)定量分析的PLS校正模型。然后,考察了不同光谱预处理(归一化、多元散射校正、标准正态变换、一阶导数和二阶导数)以及变量选择算法(粒子群优化算法和变量重要性投影)对PLS校正模型预测性能的影响。建立了一种基于激光诱导击穿光谱(Laser-induced breakdown spectroscopy, LIBS)结合偏最小二乘(Partial least squares, PLS)的石油焦中微量元素定量分析方法。结果显示,与其他PLS校正模型相比,基于二阶导数和变量重要性投影的PLS模型对Fe的预测性能最优,最优的交叉验证相关系数(R-squared cross validation,R²cv)为0.966 7,均方根误差(Root mean squared error cross validation, RMSEcv)为10.282 1 mg/kg,预测集的相关系数(R-squared prediction,R²p)为0.86...     

激光诱导击穿光谱技术结合偏最小二乘回归快速预测废钢中8种元素的含量北大核心CSCD

基于激光诱导击穿光谱(LIBS)技术,结合偏最小二乘回归(PLSR),建立了废钢中铬、镍、铜、硅、锰、钒、碳、钛等8种元素的定量分析模型。采用便携激光诱导击穿光谱废钢成分检测仪对12个钢铁标准样品进行扫描,对光谱数据进行剔除、平均、基线校正、归一化等预处理,以美国国家标准与技术研究院发射谱线数据库为参考依据,以筛选出的各元素建模波段的光谱数据作为模型输入,采用十折交叉验证方法,确定铬、镍、铜、硅、锰、钒、碳、钛的潜变量数分别为16,24,18,22,25,14,9,22,在优化的参数下分别对8种元素进行建模。结果显示:8种元素模型的相关决定系数为0.9571~0.9996,均方根误差为0.0034~0.0706,平均百分比误差为6.6764~75.645,残差平方和为0.0020~0.6532;除碳元素外,其余7种元素测定值的相对标准偏差(n=5)均不大于7.0%;模型用于预测实际废钢样品中锰、硅、铜元素的含量,所得结果与火花直读光谱法的基本一致。     

不同光谱预处理对激光诱导击穿光谱检测猪肉中铅含量的影响

为了研究适合激光诱导击穿光谱(LIBS)检测猪肉中重金属铅(Pb)元素含量的光谱预处理方法,将配制的84个猪肉腿肌样品分为校正集和预测集,以相关系数(R)、内部交叉验证均方差(RMSECV)和预测均方根误差(RMSEP)作为评价指标,比较了5种光谱预处理方法对偏最小二乘法(PLS)建模预测效果的影响.结果表明,多元散射校正(MSC)预处理效果最好,定标模型预测值与实验室分析元素检测值的相关系数(R)达到0.9908,RMSECV为0.302,RMSEP为0.282,主成分数为16,18个预测集样品的验证结果的平均相对预测误差(ARPE)为7.8％.说明MSC是LIBS检测猪肉Pb含量的有效光谱预处理方法,该研究为进一步实现食品中重金属快速定量分析提供了方法和数据参考.     

基于遗传算法和偏最小二乘法的土壤激光诱导击穿光谱定量分析研究

在空气环境下,采用激光诱导击穿光谱(LIBS)技术对土壤成分进行检测,建立了基于遗传算法(GA)和偏最小二乘法(PLS)的定量分析模型。将配制的58个土壤样品分为定标集、监控集和预测集,对11种组分Mn,Cr,Cu,Pb,Ba,Al2O3,Ca O,Fe2O3,Mg O,Na2O和K2O的含量分别进行预测。结果表明,GA作为一种谱线选择的预处理方法,可以有效减少用于PLS建模的光谱谱线的数目,从而简化模型。对于土壤中的大部分组成成分,GA-PLS模型能够显著改善传统PLS模型的预测能力。以Mn元素为例,浓度预测均方根误差(RMSEP)从0.0215%降低至0.0167%,平均百分比误差(MPE)从8.10%降低至5.20%。本研究为进一步提高土壤的LIBS定量分析准确度提供了方法参考。     

基于激光诱导击穿光谱技术结合随机森林算法快速定量分析土壤中重金属元素

土壤中重金属的检测对土壤污染分析及监控具有重要意义.本研究建立了一种基于激光诱导击穿光谱(Laser induced breakdown spectroscopy,LIBS)技术结合随机森林(Random forest,RF)算法快速定量分析土壤中重金属元素的方法.采用激光诱导击穿光谱仪对22组土壤样品的LIBS光谱进...     

基于激光诱导击穿光谱对钛元素自吸收效应的分析

为了减小谱线自吸收效应对样品物质中元素定量分析带来的干扰,提高激光诱导击穿光谱技术(LIBS)对钢铁中微量元素的检测准确度和精度,以攀钢生铁标准样品作为研究对象,选取Fe(Ⅰ)438.4 nm、Fe(Ⅰ)347.6 nm作为内标线,以原子线Ti(Ⅰ)506.5 nm、离子线Ti(Ⅱ)334.9 nm作为分析线,对Ti元素谱线的自吸收效应进行校正,分别建立内定标曲线,并建立了相应的量化模型。先通过指数函数拟合定标曲线来表征自吸收效应,然后对自吸收效应进行校正。自吸收校正后,Ti两组定标曲线的决定系数R²分别从0.882增加到0.994、0.881增加到0.917,分别提高了12.7%和4.0%。定量分析时,2^#和5^#样品用于验证,结果显示两验证样品中Ti预测浓度的相对误差都降低到了10%以内,预测浓度的相对误差分别减少了72.01%、97.10%,测量精度得到明显提高,并且自吸收校正后的预测浓度近似于等于标准浓度。实验表明,通过指数函数拟合定标曲线的方式来量化自吸收效应,并对其进行校正的方法可以提升对Ti的分析精度,方法为...     

激光诱导击穿光谱技术/多元二次非线性回归分析土壤中的铬元素

利用激光诱导击穿光谱(LIBS)技术对土壤中铬元素的含量进行了定量分析研究.由于土壤成分复杂,光谱谱线存在较严重的重叠干扰,若采用一元回归方法分析常得不到理想结果.为了更充分有效地利用光谱中信息,以土壤中Cr Ⅰ 425.43 nm和Fe Ⅰ 425.07 nm谱线的积分强度为自变量,Cr元素浓度为因变量,建立交叉降维近似多元非线性回归、多元二次非线性回归和平方降维近似多元非线性回归模型.对比分析表明,当添加Cr和Fe元素特征谱线强度交叉项影响时,所建立的多元二次非线性回归模型效果最佳,预测浓度与实际参考浓度之间线性关系达到0.9943,预测4个验证样品的相对误差分别为3.57％,0.76％,7.66％和2.24％.     

共轴双脉冲激光诱导击穿光谱和最小二乘支持向量机法定量分析植物油中铬

利用共轴双脉冲激光诱导击穿光谱( DP-LIBS)技术对植物油(大豆油、花生油和玉米油)中的重金属铬( Cr)含量进行定量分析。采用Ava-Spec双通道高精度光谱仪采集样品的LIBS光谱,然后通过其LIBS谱线图确定了CN分子谱线(421.49 nm)、Ca原子谱线(422.64 nm)及Cr的3条原子谱线(425.39、427.43和428.87 nm),根据上述谱线建立了Cr元素的单变量定标模型和最小二乘支持向量机(LS-SVM)校正模型,并用验证样品对它们进行检验。研究结果表明,对于单变量定标法,大豆油、花生油及玉米油验证样品的平均预测相对误差(PRE)分别为12.57%,12.11%和13.72%;对于三变量LS-SVM法,其定标样品真实值与预测值之间的拟合度 R2分别为0.9785,0.9792和0.9654,验证样品的平均 PRE 分别为8.92%,8.33%和10.98%;对于五变量LS-SVM法(增加两基体元素谱线变量),其定标样品真实值与预测值之间的拟合度R2分别为0.9895,0.9901和0.9855,验证样品的平均PRE分别为7.46%,8.96%和8.95%。由此可知,LS-SVM校正模型性能优于单变量定标法,且五变量LS-SVM校正模型性能优于三变量LS-SVM校正模型;采用LS-SVM法及引入合适的基体元素谱线( CN、Ca)能有效减小定量分析误差,提高LIBS技术对植物油中Cr含量预测的精度。     

Characterization of jewellery products by laser-induced breakdown spectroscopy

The suitability of laser-induced breakdown spectroscopy (LIBS) for the characterization of jewellery products is demonstrated by the development of a method based on the use of an Nd-YAG laser (operating at 532 nm) which induces ablation of the material and the production of a plasma whose emission reaches 1/8 m spectrograph (connected to a coupled charge detector (CCD)) through an optic fiber. The treatment of the instrumental signal provides enough analytical information, both for identifying and quantifying the major metals present in this type of material. The method proposed has been developed both by multivariate optimization and calibration procedures with application of the appropriate quality criteria. The chemometric analysis of the data and the use of PLS regression for calibration guarantee the ruggedness of the proposed method. The study of the emission spectra allows characterization of the most common noble metals (gold and silver) as well as other metals present in jewellery pieces.     

Qualitative and quantitative investigation of chromium-polluted soils by laser-induced breakdown spectroscopy combined with neural networks analysis

Laser-induced breakdown spectroscopy (LIBS) has been applied to the analysis of three chromium-doped soils. Two chemometric techniques, principal components analysis (PCA) and neural networks analysis (NNA), were used to discriminate the soils on the basis of their LIBS spectra. An excellent rate of correct classification was achieved and a better ability of neural networks to cope with real-world, noisy spectra was demonstrated. Neural networks were then used for measuring chromium concentration in one of the soils. We performed a detailed optimization of the inputs of the network so as to improve its predictive performances and we studied the effect of the presence of matrix-specific information in the inputs examined. Finally the inputs of the network—the spectral intensities—were replaced by the line areas. This provided the best results with a prediction accuracy and precision of about 5% in the determination of chromium concentration and a significant reduction of the data, too. Awarded a poster prize on the occasion of the Euro-Mediterranean Symposium on Laser-induced Breakdown Spectroscopy (EMSLIBS 2005), Aachen, Germany, 6–9 September 2005.     

Multivariate analysis of remote laser-induced breakdown spectroscopy spectra using partial least squares,principal component analysis,and related techniques

Quantitative analysis with laser-induced breakdown spectroscopy traditionally employs calibration curves that are complicated by chemical matrix effects. These chemical matrix effects influence the laser-induced breakdown spectroscopy plasma and the ratio of elemental composition to elemental emission line intensity. Consequently, laser-induced breakdown spectroscopy calibration typically requires a priori knowledge of the unknown, in order for a series of calibration standards similar to the unknown to be employed. In this paper, three new Multivariate Analysis techniques are employed to analyze the laser-induced breakdown spectroscopy spectra of 18 disparate igneous and highly-metamorphosed rock samples. Partial Least Squares analysis is used to generate a calibration model from which unknown samples can be analyzed. Principal Components Analysis and Soft Independent Modeling of Class Analogy are employed to generate a model and predict the rock type of the samples. These Multivariate Analysis techniques appear to exploit the matrix effects associated with the chemistries of these 18 samples.     

Fast vacuum slag analysis in a steel works by laser-induced breakdown spectroscopy

Samples taken from the liquid slag layer in a vacuum degasser station of a steel works are analyzed after solidification by laser-induced breakdown spectroscopy (LIBS) without any further sample preparation. The mass fractions of the major components of the vacuum slags are in the range of 50–60% for CaO, 0.5–12% for SiO₂ and 20–40% for Al₂O₃. The species are distributed heterogeneously in the solid samples having diameters of 35 mm. Furthermore the color and structure of the samples is varying significantly. A fast spatial averaging of representative sample areas is realized by spatial laser beam shaping. Multivariate calibration and its validation is carried out with calibration and validation sets of production samples which are analyzed by X-ray fluorescence measurements or as borate beads for reference. The laser-induced breakdown spectroscopy instrument is installed in the steel works at a distance of about 10 m from the vacuum degasser. The laser-induced breakdown spectroscopy analysis runs automatically after the sample placement and it takes 80 s including data transfer to the host computer of the steel works. Operational tests are carried out to demonstrate the feasibility of a fast slag analysis in the harsh environment of the vacuum degasser plant.     

A partial least squares and wavelet-transform hybrid model to analyze carbon content in coal using laser-induced breakdown spectroscopy

A partial least squares (PLS) and wavelet transform hybrid model are proposed to analyze the carbon content of coal by using laser-induced breakdown spectroscopy (LIBS). The hybrid model is composed of two steps of wavelet analysis procedures, which include environmental denoising and background noise reduction, to pretreat the LIBS spectrum. The processed wavelet coefficients, which contain the discrete line information of the spectra, were taken as inputs for the PLS model for calibration and prediction of carbon element. A higher signal-to-noise ratio of carbon line was obtained after environmental denoising, and the best decomposition level was determined after background noise reduction. The hybrid model resulted in a significant improvement over the conventional PLS method under different ambient environments, which include air, argon, and helium. The average relative error of carbon decreased from 2.74 to 1.67% under an ambient helium environment, which indicated a significantly improved accuracy in the measurement of carbon in coal. The best results obtained under an ambient helium environment could be partly attributed to the smallest interference by noise after wavelet denoising. A similar improvement was observed in ambient air and argon environments, thereby proving the applicability of the hybrid model under different experimental conditions.     

Quantitative analysis of alloys and glasses by a calibration-free method using laser-induced breakdown spectroscopy

Space-, time- and spectrally resolved optical diagnostics of laser ablation plasma has provided the opportunity to realize calibration-free analyses of solid materials. In general, this variant of optical emission spectroscopy of pulsed plasma allows the plasma matrix effects to be overcome, yielding satisfactorily precise and accurate quantitative results on elemental composition of materials without using calibration curves, certified reference materials, and internal standards. Such analysis is very close to be nondestructive due to the minimum possible ablated mass, a feature which is very important in many applications, especially for unique museum exhibits and jeweler samples. In this paper, the use of the method for the analysis of elements in bronze, brass and gold alloys, glass samples, and archaeological findings is demonstrated. The results presented confirm the suitability of the approach for routine applications of our instrumentation, while at the same time simplifying the overall analytical procedure.     

Vacuum ultraviolet laser-induced breakdown spectroscopy analysis of polymers

Laser-induced breakdown spectroscopy (LIBS) in the vacuum ultraviolet range (VUV, λ < 200 nm) is employed for the detection of trace elements in polyethylene (PE) that are difficult to detect in the UV/VIS range. For effective laser ablation of PE, we use a F₂ laser (wavelength λ = 157 nm) with a laser pulse length of 20 ns, a pulse energy up to 50 mJ, and pulse repetition rate of 10 Hz. The optical radiation of the laser-induced plasma is measured by a VUV spectrometer with detection range down to λ = 115 nm. A gated photon-counting system is used to acquire time-resolved spectra. From LIBS measurements of certified polymer reference materials, we obtained a limit of detection (LOD) of 50 µg/g for sulphur and 215 µg/g for zinc, respectively.The VUV LIBS spectra of PE are dominated by strong emission lines of neutral and ionized carbon atoms. From time-resolved measurements of the carbon line intensities, we determine the temporal evolution of the electronic plasma temperature, T_e. For this, we use Saha–Boltzmann plots with the electron density in the plasma, N_e, derived from the broadening of the hydrogen H-α line. With the parameters T_e and N_e, we calculate the intensity ratio of the atomic sulphur and carbon lines at 180.7 nm and at 175.2 nm, respectively. The calculated intensity ratios are in good agreement with the experimentally measured results.     

Multivariate analysis of laser-induced breakdown spectroscopy chemical signatures for geomaterial classification

A large suite of natural carbonate, fluorite and silicate geological materials was studied using laser-induced breakdown spectroscopy (LIBS). Both single- and double-pulse LIBS spectra were acquired using close-contact benchtop and standoff (25 m) LIBS systems. Principal components analysis (PCA) and partial least squares discriminant analysis (PLS-DA) were used to identify the distinguishing characteristics of the geological samples and to classify the materials. Excellent discrimination was achieved with all sample types using PLS-DA and several techniques for improving sample classification were identified. The laboratory double-pulse LIBS system did not provide any advantage for sample classification over the single-pulse LIBS system, except in the case of the soil samples. The standoff LIBS system provided comparable results to the laboratory systems. This work also demonstrates how PCA can be used to identify spectral differences between similar sample types based on minor impurities.