我国冶金分析定量检测仪器的发展趋势

为了了解我国分析仪器的发展,推动冶金分析领域定量检测技术的进步,文章以北京分析测试学术报告会暨展览会(BCEIA)在国内的展示成果为依托,选择电感耦合等离子体发射光谱(ICP-OES)、电感耦合等离子体质谱(ICP-MS)、X射线荧光光谱(XRF)、激光诱导击穿光谱(LIBS)等基础定量检测仪器为主要分析对象,归纳总结了这些仪器的发展过程、基本原理和主要结构。从分析检测人员的视角,讨论了该检测仪器的优势特点及应用效果;展望了定量分析检测技术的发展趋势;提出了以定量检测仪器为基础的新型高端科学仪器的发展前景。又以激光剥蚀电感耦合等离子体质谱(LA-ICP-MS)、辉光放电质谱(GD-MS)、电子探针X射线显微分析仪(EPMA)等拓展联用检测仪器为例,介绍了设备的主要特点及应用,最终总结出LA-ICP-MS为固体样品中微量元素分析的常用技术,GD-MS技术是痕量元素分析的重要手段,EPMA技术因具有与其他仪器结合包容性高的优点,虽然在使用过程中存在一定的缺陷,但已成为通用的分析手段。而我国定量分析检测技术正朝着现场化、专用化及标准化的方向发展。     

基于DP-LIBS铁合金中碳元素特征谱线的研究

采用双脉冲和单脉冲激光,对空气中标准铁合金样品中碳元素的激光诱导实验,研究两种方式下形成的光谱。双脉冲激光诱导击穿光谱采用两束激光,在第一束激光脉冲的基础上加入第二束高压激光脉冲,对等离子体进行二次激发。通过对比研究发现:双脉冲激发技术延长了原子特征辐射的有效时间,提高了获取信号的信噪比,增强了发射光谱的信号强度,提高了信号的稳定性。此外,通过分析影响双脉冲信号增强程度的因素,研究了脉冲宽度和延迟时间以及激发能级对光谱增强程度的影响。     

无监督数据挖掘辅助激光诱导击穿光谱用于铜冶炼光谱结构解析

在有色冶炼领域,元素成分检测是保证冶炼质量的重要一环。目前国内有色冶炼企业多采用X射线荧光光谱法进行检测,该方法需要样品制备,造成冶炼状态无法实时反馈,严重影响冶炼过程优化。研究了无监督数据挖掘算法辅助激光诱导击穿光谱技术用于铜冶炼光谱结构解析。实验中,首先选择4种铜冶炼物料作为实验样品,然后利用激光诱导击穿光谱技术(LIBS)激发样品获得18750个光谱数据,通过盲源分离技术对所有光谱进行分析,最终提取得到3个特征光谱。进一步研究发现,3个特征光谱与Cu、Fe、Ca元素光谱有一一对应关系。在此基础上,提出了LIBS光谱的定量化评价指标,量化结果表明分解模型对18750个光谱都能达到很高的评分,说明铜冶炼光谱能够良好地被3个特征光谱重构,即铜冶炼光谱存在显著的光谱结构。以上结论在实际应用中具有重要研究价值,可用于光谱快速评价、异常光谱剔除、光谱信号提纯、元素谱线选取、样品定性/半定量分析等,为LIBS技术应用于在线铜冶炼成分分析奠定基础。     

激光诱导击穿光谱在冶金在线分析中的应用研究进展

化学成分在线直接测量是冶金分析长久以来的追求,也被誉为冶金分析面临的三大难题之一。激光诱导击穿光谱技术因其在无需复杂样品制备、直接快速、非接触等方面展现的独有技术优势,备受研究上的关注。文章综述了激光诱导击穿光谱在选矿、熔融金属在线检测方面的研究进展,总结了当前存在的主要问题,并对未来发展进行了展望。     

A novel strategy for quantitative analysis of soil pH via laser-induced breakdown spectroscopy coupled with random forest

pH is one of the significant properties of soil,and is closely related to the decomposition of soil organic matter,anion-cation balance,growth of plants and many other soil processes.In the present work,laser-induced breakdown spectroscopy(LIBS) technique coupled with random forest(RF) was proposed to quantify the pH of soil.First,LIBS spectra of soil was collected,and some common elements in soil were identified based on the National Institute of Science and Technology database.Then,in order to obtain a better predictive result,the influence of different input variables(full spectrum,different spectral ranges,the intensity of characteristic bands and characteristic lines) on the predictive performance of RF calibration model was explored with the evaluation indicators of root mean square error(RMSE) and coefficient of determination(R2),the characteristic bands of four elements(AI,Ca,Mg and Si) were determined as the optimal input variables.Finally,the predictive performance of RF calibration model was compared with partial least squares calibration model with the optimal input variables and model parameters,and RF calibration model showed a better predictive performance,and the four evaluation indicators of R_p~2,RMSEP,mean absolute error and mean relative error were 0.9687,0.1285,0.1114 and 0.0136,respectively.It indicates that LIBS technique coupled with RF algorithm is an effective method for pH determination of soil.     

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.     

磁场环境下铝电解熔融铝液成分激光诱导击穿光谱原位测量分析

铝电解车间具有高温、强磁、多粉尘等环境特点,当前生产过程中熔融原铝的成分检测主要是人工取样然后离线分析,化验过程及结果具有较大的滞后性,故将激光诱导击穿光谱(LIBS)技术应用于铝电解车间铝液成分原位、实时测量具有重要意义。实验采用Nd:YAG脉冲激光器,多通道光纤光谱仪和电感耦合器件(CCD)探测器组成的激光诱导击穿光谱测量系统对电流为400kA电解槽中熔融铝液的主要成分铁、硅进行了探测,对原铝中部分元素的特征谱线进行了归属分析。考察了激光能量在磁场环境下的衰减变化及谱线梯度变迁规律,结果表明,距离电解槽边缘约2m处激光能量衰减达最大。分析了磁场对测试系统的影响,并建立了定标曲线,铁和硅两种元素按照内标法建立的定标曲线拟合度分别为93.50%和97.10%,采用该模型进行了测试实验,并用国标GB/T 7999—2015中光电直读发射光谱(OES)测试的相关指标验证测试结果的重复性与允许差。实验证明,LIBS技术在电解铝行业在线检测方面具有较好的应用前景,但是测试的稳定性与重复性也是面临的一个重要问题。     

Effect of distances between lens and sample surface on laser-induced breakdown spectroscopy with spatial confinement

Spatial confinement can significantly enhance the spectral intensity of laser-induced plasma in air.It is attributed to the compression of plasma plume by the reflected shockwave.In addition,optical emission spectroscopy of laser-induced plasma can also be affected by the distance between lens and sample surface.In order to obtain the optimized spectral intensity,the distance must be considered.In this work,spatially confined laser-induced silicon plasma by using a Nd:YAG nanosecond laser at different distances between lens and sample surface was investigated.The laser energies were 12 mJ,16 mJ,20 mJ,and 24 mJ.All experiments were carried out in an atmospheric environment.The results indicated that the intensity of Si (I) 390.55 nm line firstly rose and then dropped with the increase of lens-to-sample distance.Moreover,the spectral peak intensity with spatial confinement was higher than that without spatial confinement.The enhancement ratio was approximately 2 when laser energy was 24 mJ.     

Discrimination of organic solid materials by LIBS using methods of correlation and normalized coordinates

The methods of linear and rank correlation and normalized coordinates (MNC) have been applied to the identification of organic solid materials with a very similar chemical composition by laser-induced breakdown spectroscopy (LIBS). The present study evaluated these three statistical methods using an Echelle spectrometer coupled with an intensified charge-coupled device (ICCD). Moreover, three instrumental parameters (laser pulse energy, delay time and integration time) were evaluated in terms of their influence on the signal-to-noise ratio of carbon and hydrogen emission lines. The probability of a right identification can be estimated by means the described methods in this paper. Methods of correlation provide better identification and discrimination than normalized coordinates at a 95% confidence level.     

共轴双光束LIBS检测土壤中Pb的参数优化

为了提高共轴双光束激光诱导击率光谱(DB-LIBS)检测土壤中重金属元素的检测精度,对试验装置进行了参数优化。试验时,以土壤中重金属Pb为例,首先对双光束与单光束作用效果进行对比,单束激光脉冲工作能量均为120mJ,得到双光束作用下土壤中Pb的特征光谱强度明显比单光束作用下增强了2~3倍。然后,分别设置两束激光之间的脉冲延迟时间为0、50和100ns,在每个激光脉冲延迟时间下,设置光谱采集延迟时间从2.6~5.2μs以步长为0.2μs递增,分别对样品的光谱进行采集,获取Pb元素在405.78nm处的特征光谱信息。通过对特征光谱强度和信背比的综合比较,得到最佳的激光脉冲延迟时间为50ns、光谱采集延迟时间为4.6μs,在此条件下,光谱强度的相对标准偏差为0.10。由此表明,参数优化有利于提高共轴DB-LIBS装置的检测精度。