基于UVE变量筛选偏最小二乘的LIBS磷精矿浆定量分析

利用激光诱导击穿光谱(Laser Induced Breakdown Spectroscopy, LIBS)技术采集得到磷精矿浆的光谱,基于无信息变量消除(Uniformative Variables Elimination, UVE)方法筛选出与磷元素相关的波长变量,将选择后的波长作为自变量建立偏最小二乘(Partial Least Squares, PLS)回归模型,并与传统全谱PLS和GA-PLS(Genetic Algorithm-Partial Least Squares, GA-PLS)定标模型进行比较。相比全谱PLS,UVE-PLS定标模型的性能更优,其预测均方根误差(Root-mean-square Error of Prediction, RMSEP)由0.38%下降到0.26%,决定系数(R2)从0.59提高到0.72。相比GA-PLS定标模型,UVE方法可以克服GA(Genetic Algorithm, GA)在参量选择上存在随机性的弊端,筛选出的变量仅为全谱的8.76%,而且计算速度更快,分析精度也优于GA-PLS模型。

激光诱导击穿光谱技术相关物理机制研究进展

激光诱导击穿光谱技术(Laser-Induced Breakdown Spectroscopy,LIBS)是利用强脉冲激光与物质相互作用所产生的等离子体光谱来实现对物质组成元素定性和定量分析的一种新方法。在脉冲激光诱导等离子体的过程中,不同的激光参数(能量、脉宽、波长)、检测过程中的环境条件以及材料本身的特性等,对激光诱导等离子体的物理机制都有不同程度的影响,进而影响LIBS定量分析的结果。本文综述了现阶段LIBS技术中包括LIBS基本原理、激光参数区别、环境和材料特性差异所涉及的物理机制。为深入理解激光与物质相互作用、提升LIBS检测能力提供了依据。

激光感生击穿光谱技术(LIBS)的原理及影响因素

激光感生击穿光谱技术(LIBS)具有不需制备样品,快速分析,可进行实时控制的特点显示了巨大实际应用价值,文中介绍了激光感生击穿光谱技术(LIBS)的发展历史、研究现状及其原理。同时通过重复频率为20Hz,最高单脉冲能量为50mJ的纳秒激光(10ns,1064nm)研究了在不同激发条件下Cr和Co薄膜产生的光谱信号。得出对于Cr膜当激发能量小于10mJ时,信号差异不明显。但是当激发能量超过10mJ时将产生明显的变化。分析了激光特性、延迟时间、实验装置、环境气体的种类及压力、单/双脉冲、以及采用的理论分析方法对LIBS探测结果的影响。

用LIBS方法测量铝合金中的合金元素

将高能激光脉冲聚焦在合金样品表面形成样品的高温等离子体，用光栅光谱仪与增强型电感耦合装置（ICCD）分析等离子体的发射谱线来测定合金中的元素种类与浓度．实验以系列标准铝合金的光谱来标定Fe，Si，Cu的定量分析标准曲线，分析了铝合金中主要元素的测量精度与探测限．研究表明，该方法在合金元素质量分数大于0．01％时，测量相对误差在5％之内；在合金元素质量分数低于0．01％时，测量绝对误差在0．001％之内，对3种合金元素的检出限可达6×10^-5～10×10^-3。左右，且采用基体元素作为内标可进一步提高分析精度．

激光诱导击穿光谱(LIBS)光谱诊断与元素分析及激光功率、入射角度以及测试距离的改变对结果影响

激光诱导击穿光谱法(LIBS)在精准识别该样品元素的组成成分和含量的同时,也可以得到该特征元素等离子体的电子温度、粒子旋转温度等相关光谱诊断参数。该方法非接触式、低损伤阈值,借助高速高分辨率响应的CCD探测元件更可以实现实时动态测量。文章基于LIBS的相关原理,对一块事先标定好元素成分的合金进行光谱诊断的同时,发现在改变激光入射角度、激光入射功率和接收端面到测试样品的距离对实验结果将会产生重要的影响。由实验结果表明,利用LIBS不仅可以精准的分析测试对象的元素成分和含量,同时也定量分析了以上实验条件和参数的变化对实验结果的影响并给出相应的理论依据与解释。

利用LD温漂增强LIBS激光器温度适应性研究

为了实现野外环境下的小型LIBS系统对激光光源宽温的要求,利用LD光谱温漂特性、MgO∶LN宽温电光开关、集成谐振腔以及激光放大技术,拓宽了激光器的温度适应范围,降低激光器的温控精度。最后利用KTP,BBO晶体对输出的1064 nm激光进行四倍频试验。试验结果表明:利用LD光谱温漂特性,可以增强激光器的温度适应性。

液相射流中中Al元素单双脉冲LIBS研究(英文)

为了综合比较单双脉冲激光诱导击穿光谱技术(LIBS)在液体中重金属元素的检测效果,利用自建的液相射流单-双脉冲LIBS技术装置,对AlCl3水溶液中的Al元素LIBS特性进行测量和分析。实验中使用两台532nm Nd∶YAG激光器作为激发光源,等离子体辐射信号通过光谱仪和ICCD进行采集。实验研究了单脉冲下Al(396.15nm)发射谱线的谱线强度随激光能量、ICCD门延时、门宽之间的变化关系,获得了最优化实验参数激光能量为50mJ,ICCD门延迟为1 200ns,门宽为150ns。在相同的实验条件下,实验考察了Al(369.15nm)发射谱线的谱线强度随双脉冲之间的延时,激光总能量,ICCD门延时的变化关系,获得了最优化实验参数为两双脉冲之间的延时为1 000ns,激光总能量为50mJ,ICCD门延时为1 100ns。单脉冲和双脉冲条件下获得重金属Al的LIBS检测限分别为26.79和10.80ppm,双脉冲LIBS技术使元素检测限下降2倍多。实验结果表明双脉冲可以提升LIBS技术的探测灵敏度,为LIBS技术应用于水体中重金属快速检测提供了依据。

Characteristics of laser-induced breakdown spectroscopy of liquid slag

Rapid online analysis of liquid slag is essential for optimizing the quality and energy efficiency of steel production. To investigate the key factors that affect the online measurement of refined slag using laser-induced breakdown spectroscopy(LIBS), this study examined the effects of slag composition and temperature on the intensity and stability of the LIBS spectra. The experimental temperature was controlled at three levels: 1350℃, 1400℃, and 1450℃. The results showed that slag composition and temperature significantly affected the intensity and stability of the LIBS spectra. Increasing the Fe content and temperature in the slag reduces its viscosity, resulting in an enhanced intensity and stability of the LIBS spectra. Additionally, 42 refined slag samples were quantitatively analyzed for Fe, Si, Ca, Mg, Al, and Mn at 1350℃, 1400℃, and 1450℃.The normalized full spectrum combined with partial least squares(PLS) quantification modeling was used, using the Ca Ⅱ 317.91 nm spectral line as an internal standard. The results show that using the internal standard normalization method can significantly reduce the influence of spectral fluctuations. Meanwhile, a temperature of 1450℃ has been found to yield superior results compared to both 1350℃ and 1400℃, and it is advantageous to conduct a quantitative analysis of the slag when it is in a “water-like” state with low viscosity.

LIBS技术的沉积物中重金属元素Zn的分析研究

随着经济的发展,海洋、河流污染日益严重,沉积物是判断海洋、河流重金属污染程度的重要窗口,实际调查中也迫切需要能对沉积物污染程度快速检测的技术。激光诱导击穿光谱技术(LIBS)具有实时、样品预处理简单、多种元素同时检测等优点,是一种可用于在线分析沉积物中重金属元素的有效手段。应用实验室研发的便携式LIBS装置开展了沉积物中Zn元素的检测,该装置采用Nd∶YAG脉冲激光器作为激发光源,用单通道微型光纤光谱仪进行分光检测,装置整体尺寸为371 mm×192 mm×294 mm,可方便的进行现场测量。为实现LIBS技术对沉积物的定量分析,首先在实验室对沉积物的LIBS数据进行预处理,对八种沉积物样品进行干燥、过筛、混匀和压片处理后进行测量,通过对比采用四种不同标准化方法处理后光谱的相对标准偏差(RSD),确定最佳光谱标准化方法为结合等离子体特征的标准化,采用该方法后的RSD降至未标准化处理光谱的五分之一;之后分别采用单变量分析方法和带动量因子的自适应学习率三层BPNN算法进行定量分析, BPNN算法的训练相关系数R2达到0.99,预测误差为3.2%,相比单变量定量分析方法预测结果改善了一倍。同时,针对现场快速分析,对比了不同干燥时间下沉积物光谱强度变化, 12 min后信号强度随干燥时间的变化不大,因此确定现场探测对沉积物的干燥时间为12 min。利用该装置在胶州湾海域六个不同站位进行了现场沉积物采集和测量试验,在甲板上对现场采集的沉积物样品快速烘干后进行LIBS探测,并采用上述实验室建立的定量方法对Zn元素进行浓度预测,与带回实验室采用原子吸收分光光度法(AAS)的检测结果相比, LIBS探测结果的平均误差为8.32%。验证了该装置应用于现场沉积物快速测量的可行性,同时证明了结合等离子体特征的标准化方法以及BPNN用于沉积物中Zn元素浓度预测的适用性。

以液体喷流方式利用LIBS定量分析水溶液中的Al元素

为了提高激光诱导击穿光谱技术用于水溶液中痕量金属检测的稳定性和灵敏度,采用液体喷流的方式,利用激光诱导击穿光谱技术对不同浓度的Al溶液进行了检测和分析。通过对实验系统的激光能量、探测延时等的优化,以Al元素的396.15nm谱线作为分析线,得到水溶液中的Al元素的检测限(LOD)为18.65ppm。这一结果比王传辉等人(参见文献1)的检测灵敏度要高。

Mechanisms and efficient elimination approaches of self-absorption in LIBS

Laser-induced breakdown spectroscopy(LIBS) is a promising analytical spectroscopy technology based on spectroscopic analysis of the radiation emitted by laser-produced plasma.However, for quantitative analysis by LIBS, the so-called self-absorption effects on the spectral lines, which affect plasma characteristics, emission line shapes, calibration curves, etc, can no longer be neglected. Hence, understanding and determining the self-absorption effects are of utmost importance to LIBS research. The purpose of this review is to provide a global overview of self-absorption in LIBS on the issues of experimental observations and adverse effects,physical mechanisms, correction or elimination approaches, and utilizations in the past century.We believe that better understanding and effective solving the self-absorption effect will further enhance the development and maturity of LIBS.

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.

激光诱导击穿光谱(LIBS)在铝合金废料分选中的应用

简要介绍了激光诱导击穿光谱法(LIBS)的发展历程以及在铝合金废料分选中的应用。

Review of preferentially selective lithium extraction from spent lithium batteries: Principle and performance

Lithium,as the lightest and lowest potential metal,is an ideal "battery metal" and the core strategic metal of the new energy industry revolution.Recovering lithium from spent lithium batteries(LIBs)has become one of the significant approaches to obtaining lithium resources.At present,the lithium extraction being generally placed at the last step of the spent LIBs recovery process has puzzles such as high acid consumption,low Li recovery purity and low recovery efficiency.Selective lithium extraction at the first step of the recovery process can effectively solve those puzzles.Since lithium leaching is a non-spontaneous reaction requiring additional energy to achieve,it is found that these methods can be divided into five ways according to the different types of energy driving the reaction occurring:(ⅰ)electric energy driving lithium extraction;(ⅱ) chemical energy driving lithium extraction;(ⅲ) mechanical energy driving lithium extraction;(ⅳ) thermal energy driving lithium extraction;(ⅴ) other energy driving lithium extraction.Through the analysis of the principle,reaction process and results of recovering lithium methods can provide a few directions for scholars’ subsequent research.It is necessary to speed up the exploration of the principle of these methods.It is expected that this study could provide a reference for the research on the selective lithium extraction.

A data selection method for matrix effects and uncertainty reduction for laser-induced breakdown spectroscopy

Severe matrix effects and high signal uncertainty are two key bottlenecks for the quantitative performance and wide applications of laser-induced breakdown spectroscopy(LIBS).Based on the understanding that the superposition of both matrix effects and signal uncertainty directly affects plasma parameters and further influences spectral intensity and LIBS quantification performance,a data selection method based on plasma temperature matching(DSPTM)was proposed to reduce both matrix effects and signal uncertainty.By selecting spectra with smaller plasma temperature differences for all samples,the proposed method was able to build up the quantification model to rely more on spectra with smaller matrix effects and signal uncertainty,therefore improving final quantification performance.When applied to quantitative analysis of the zinc content in brass alloys,it was found that both accuracy and precision were improved using either a univariate model or multiple linear regression(MLR).More specifically,for the univariate model,the root-mean-square error of prediction(RMSEP),the determination coefficients(R^(2))and relative standard derivation(RSD)were improved from 3.30%,0.864 and 18.8%to 1.06%,0.986 and 13.5%,respectively;while for MLR,RMSEP,R^(2)and RSD were improved from 3.22%,0.871 and 26.2%to 1.07%,0.986 and 17.4%,respectively.These results prove that DSPTM can be used as an effective method to reduce matrix effects and improve repeatability by selecting reliable data.

Overview of multi-stage charging strategies for Li-ion batteries

To reduce the carbon footprint in the transportation sector and improve overall vehicle efficiency,a large number of electric vehicles are being manufactured.This is due to the fact that environmental concerns and the depletion of fossil fuels have become significant global problems.Lithium-ion batteries(LIBs)have been distinguished themselves from alternative energy storage technologies for electric vehicles(EVs) due to superior qualities like high energy and power density,extended cycle life,and low maintenance cost to a competitive price.However,there are still certain challenges to be solved,like EV fast charging,longer lifetime,and reduced weight.For fast charging,the multi-stage constant current(MSCC) charging technique is an emerging solution to improve charging efficiency,reduce temperature rise during charging,increase charging/discharging capacities,shorten charging time,and extend the cycle life.However,there are large variations in the implementation of the number of stages,stage transition criterion,and C-rate selection for each stage.This paper provides a review of these problems by compiling information from the literature.An overview of the impact of different design parameters(number of stages,stage transition,and C-rate) that the MSCC charging techniques have had on the LIB performance and cycle life is described in detail and analyzed.The impact of design parameters on lifetime,charging efficiency,charging and discharging capacity,charging speed,and rising temperature during charging is presented,and this review provides guidelines for designing advanced fast charging strategies and determining future research gaps.

Detection and quantification of Pb and Cr in oysters using laser-induced breakdown spectroscopy

The quantitative determination of heavy metals in aquatic products is of great importance for food security issues.Laser-induced breakdown spectroscopy(LIBS)has been used in a variety of foodstuff analysis,but is still limited by its low sensitivity when targeting trace heavy metals.In this work,we compare three sample enrichment methods,namely drying,carbonization,and ashing,for increasing detection sensitivity by LIBS analysis for Pb and Cr in oyster samples.The results demonstrate that carbonization can remove a significant amount of the contributions of organic elements C,H,N and O;meanwhile,the signals of the metallic elements such as Cu,Pb,Sr,Ca,Cr and Mg are enhanced by3–6 times after carbonization,and further enhanced by 5–9 times after ashing.Such enhancement is not only due to the more concentrated metallic elements in the sample compared to the dried ones,but also the unifying of the matter in carbonized and ashed samples from which higher plasma temperature and electron density are observed.This condition favors the detection of trace elements.According to the calibration curves with univariate and multivariate analysis,the ashing method is considered to be the best choice.The limits of detection of the ashing method are 0.52 mg kg-1 for Pb and0.08 mg kg-1 for Cr,which can detect the presence of heavy metals in the oysters exceeding the maximum limits of Pb and Cr required by the Chinese national standard.This method provides a promising application for the heavy metal contamination monitoring in the aquatic product industry.

Estimating the State of Health for Lithium-ion Batteries:A Particle Swarm Optimization-Assisted Deep Domain Adaptation Approach

The state of health(SOH)is a critical factor in evaluating the performance of the lithium-ion batteries(LIBs).Due to various end-user behaviors,the LIBs exhibit different degradation modes,which makes it challenging to estimate the SOHs in a personalized way.In this article,we present a novel particle swarm optimization-assisted deep domain adaptation(PSO-DDA)method to estimate the SOH of LIBs in a personalized manner,where a new domain adaptation strategy is put forward to reduce cross-domain distribution discrepancy.The standard PSO algorithm is exploited to automatically adjust the chosen hyperparameters of developed DDA-based method.The proposed PSODDA method is validated by extensive experiments on two LIB datasets with different battery chemistry materials,ambient temperatures and charge-discharge configurations.Experimental results indicate that the proposed PSO-DDA method surpasses the convolutional neural network-based method and the standard DDA-based method.The Py Torch implementation of the proposed PSO-DDA method is available at https://github.com/mxt0607/PSO-DDA.

改进的谱峰拟合光谱标准化方法定量分析废钢中元素

为了解决因设备和环境因素导致激光诱导击穿光谱(LIBS)技术在定量测量时的较高波动性问题,提出了基于改进的沃伊特函数拟合的光谱标准化方法。首先通过高精度激光器采集废钢样品的LIBS光谱数据,然后通过标准等离子体条件(标准等离子温度、电子数密度、待测元素总密度)得到标准光谱强度与实际谱线强度、半峰全宽等因素之间的关系式,并基于近似沃伊特函数对相关的谱峰进行拟合,获得标准化的重要参数,完成对样品的标准化模型的建立。结果表明,将该标准化方法用于废钢中铜、镍、硅、铬、锰元素的定量预测,得到的相关系数(R^(2))、预测均方根误差(RMSEP)和平均相对误差(ARE)的平均值分别为0.9814,0.063,6.3%,有效降低了波动影响,增强了分析精度,能够在工业中对废钢元素进行快速检测。