The effect of sequential dual-gas testing on laser-induced breakdown spectroscopy-based discrimination: Application to brass samples and bacterial strains

Four Cu–Zn brass alloys with different stoichiometries and compositions have been analyzed by laser-induced breakdown spectroscopy (LIBS) using nanosecond laser pulses. The intensities of 15 emission lines of copper, zinc, lead, carbon, and aluminum (as well as the environmental contaminants sodium and calcium) were normalized and analyzed with a discriminant function analysis (DFA) to rapidly categorize the samples by alloy. The alloys were tested sequentially in two different noble gases (argon and helium) to enhance discrimination between them. When emission intensities from samples tested sequentially in both gases were combined to form a single 30-spectral line “fingerprint” of the alloy, an overall 100% correct identification was achieved. This was a modest improvement over using emission intensities acquired in argon gas alone. A similar study was performed to demonstrate an enhanced discrimination between two strains of Escherichia coli (a Gram-negative bacterium) and a Gram-positive bacterium. When emission intensities from bacteria sequentially ablated in two different gas environments were combined, the DFA achieved a 100% categorization accuracy. This result showed the benefit of sequentially testing highly similar samples in two different ambient gases to enhance discrimination between the samples.     

Adaptive approach for variable noise suppression on laser-induced breakdown spectroscopy responses using stationary wavelet transform

Spectral signals are often corrupted by noise during their acquisition and transmission. Signal processing refers to a variety of operations that can be carried out on measurements in order to enhance the quality of information. In this sense, signal denoising is used to reduce noise distortions while keeping alterations of the important signal features to a minimum. The minimization of noise is a highly critical task since, in many cases, there is no prior knowledge of the signal or of the noise. In the context of denoising, wavelet transformation has become a valuable tool. The present paper proposes a noise reduction technique for suppressing noise in laser-induced breakdown spectroscopy (LIBS) signals using wavelet transform. An extension of the Donoho's scheme, which uses a redundant form of wavelet transformation and an adaptive threshold estimation method, is suggested. Capabilities and results achieved on denoising processes of artificial signals and actual spectroscopic data, both corrupted by noise with changing intensities, are presented. In order to better consolidate the gains so far achieved by the proposed strategy, a comparison with alternative approaches, as well as with traditional techniques, is also made.     

Variable selection by modified IPW (iterative predictor weighting)-PLS (partial least squares) in continuous wavelet regression models

Variable selection is often used to produce more robust and parsimonious regression models. But when they are applied directly to the raw near-infrared spectra, it is not easy to select appropriate variables because background and noise will often overshadow or overlap the absorption bands of analyte. In this work, a new hybrid algorithm based on the selection of the most informative variables in the continuous wavelet transform (CWT) domain is described. The strategy is a combination of CWT and a procedure of modified iterative predictor weighting-partial least square (mIPW-PLS). After elimination of the background and noise in NIR spectra by CWT, the mIPW-PLS approach is used to select the most informative CWT coefficients. With the selected CWT coefficients, a PLS model is built finally for prediction. It is indicated that the extraction of most important variables in the CWT domain can effectively avoid the interference of background and noise, and result in a high quality of regression model with a very small number of variables and fewer PLS components.     

A PLS model based on dominant factor for coal analysis using laser-induced breakdown spectroscopy

Thirty-three bituminous coal samples were utilized to test the application of laser-induced breakdown spectroscopy technique for coal elemental concentration measurement in the air. The heterogeneity of the samples and the pyrolysis or combustion of coal during the laser–sample interaction processes were analyzed to be the main reason for large fluctuation of detected spectra and low calibration quality. Compared with the generally applied normalization with the whole spectral area, normalization with segmental spectral area was found to largely improve the measurement precision and accuracy. The concentrations of major element C in coal were determined by a novel partial least squares (PLS) model based on dominant factor. Dominant C concentration information was taken from the carbon characteristic line intensity since it contains the most-related information, even if not accurately. This dominant factor model was further improved by inducting non-linear relation by partially modeling the inter-element interference effect. The residuals were further corrected by PLS with the full spectrum information. With the physical-principle-based dominant factor to calculate the main quantitative information and to partially explicitly include the non-linear relation, the proposed PLS model avoids the overuse of unrelated noise to some extent and becomes more robust over a wider C concentration range. Results show that RMSEP in the proposed PLS model decreased to 4.47% from 5.52% for the conventional PLS with full spectrum input, while R ² remained as high as 0.999, and RMSEC&P was reduced from 3.60% to 2.92%, showing the overall improvement of the proposed PLS model.     

Quantitative Determination of Cr in Ink by Laser-induced Breakdown Spectroscopy(LIBS)Using ZnO as Adsorbent

Laser-induced breakdown spectroscopy(LIBS) technique was applied to detecting chromium in ink with ZnO as adsorbent, and the LIBS spectra were preprocessed by wavelet denoising. The laser energy and delay time were optimized depending on the signal-to-noise ratio(SNR) and intensity of three analysis atomic lines(Cr 425.43 nm, Cr 427.48 nm and Cr 428.97 nm). Compared with other analysis lines, atomic line of Cr 427.48 nm was selected as the analysis line for the quantitative analysis of Cr in ink as the calibration curve of it showed a better linear relationship (correlation coefficient R²=0.9778), and the relative error of Cr in the measured ink was 52.96%. Since the single spectral line used for calibration curve method is often influenced by matrix effect and other factors, partial least squares regression(PLS) as multivariate calibration method has been applied to predicting the concentration of Cr in ink, and the relative error of Cr in the measured ink was 10.48%. The result obtained from the PLS method was better than that from the calibration curve when comparing the relative error, demonstrating that, based on adsorbent, LIBS combined with PLS provides an effective, practical and convenient technique for the determination of trace element in aqueous solution.     

Experimental and kinetic modeling study of the laser-induced breakdown spectroscopy plume from metallic lead in argon

A kinetic model of the laser-induced breakdown spectroscopy (LIBS) plume of lead in argon has been developed to gain an understanding of the physical and chemical factors controlling the LIBS signature. This model includes processes involving ion chemistry, excitation, ionization, and other processes affecting the concentrations of argon and lead atoms (in 9 different electronic states) and their ions. A total of 15 chemical species and 90 reactions are included in the model. Experimental measurements of the temporal dependence of a number of lead emission lines in the LIBS plume of metallic lead have been made in argon and air. The modeling results are compared with these observations and with previous modeling of LIBS of lead in air.     

A new hybrid strategy for constructing a robust calibration model for near-infrared spectral analysis

A new hybrid algorithm is proposed for construction of a high-quality calibration model for near-infrared (NIR) spectra that is robust against both spectral interference (including background and noise) and multiple outliers. The algorithm is a combination of continuous wavelet transform (CWT) and a modified iterative reweighted PLS (mIRPLS) procedure. In the proposed algorithm the spectral interference is filtered by CWT at the first stage then mIRPLS is proposed to detect the multiple outliers in the CWT domain. Compared with the original IRPLS method, mIRPLS does not need to adjust variable parameters to achieve optimum calibration results, which makes it very convenient to perform in practice. The final PLS model is constructed robustly because both the spectral interference and multiple outliers are eliminated. In order to validate the effectiveness and universality of the algorithm, it was applied to two different sets of NIR spectra. The results indicate that the proposed strategy can greatly enhance the robustness and predictive ability of NIR spectral analysis.     

Simultaneous wavelength selection and outlier detection in multivariate regression of near-infrared spectra.

Near-infrared (NIR) spectrometry will present a more promising tool for quantitative measurement if the robustness and predictive ability of the partial least square (PLS) model are improved. In order to achieve the purpose, we present a new algorithm for simultaneous wavelength selection and outlier detection; at the same time, the problems of background and noise in multivariate calibration are also solved. The strategy is a combination of continuous wavelet transform (CWT) and modified iterative predictors and objects weighting PLS (mIPOW-PLS). CWT is performed as a pretreatment tool for eliminating background and noise synchronously; then, mIPOW-PLS is proposed to remove both the useless wavelengths and the multiple outliers in CWT domain. After pretreatment with CWT-mIPOW-PLS, a PLS model is built finally for prediction. The results indicate that the combination of CWT and mIPOW-PLS produces robust and parsimonious regression models with very few wavelengths.     

Ambient Gas Breakdown Behavior in an Excimer Laser-Ablated Plasma

Gas breakdown in an excimer laser-ablated plasma occurs to a greater extent in an argon atmosphere than in an air or helium atmosphere. A simple relationship between the ambient gas breakdown and the physical properties of the metal target was deduced from experimental data for argon gas breakdown using a 763.9-nm argon line and aluminum, copper, iron, lead, and zinc targets.     

Emission spectra of an argon inductively coupled plasma in the vacuum ultraviolet: background spectra from 85 to 200 nm

The background spectra emitted from an argon ICP discharge have been recorded over the spectral range 85 to 200 nm. These vacuum ultraviolet spectra were acquired by coupling the ICP to a 0.5-m Seya-Namioka vacuum monochromator, through a helium purged side-arm. Background features observed include emission from the resonance lines of ArI, and emission from gas impurities such as oxygen, nitrogen, carbon and hydrogen.     

一种新的小波滤波方法在化学谱图信号滤噪中的应用

仪器分析测定中，噪声的存在往往影响分析的准确度和仪器的检出限。小波变换多分辨分析的特性使得它成为一种很好的滤噪方法。基于小波分解后信号与噪声的小波系数随尺度变化规律不同的特性，提出了一种新的滤波滤方法-空域相关法，即通过不同尺度上相关系数模值与小波系数模模值的比较，达到滤波滤的目的。本文提出的方法具有无需人为选定无需人为选定滤噪阈值和小波函数、方法简单、失真度小等优点，可以大在提高信号的信噪比。模拟数据和ICP-AES实验数据证明了该方法的有效性。     

Detection of trace concentrations of helium and argon in gas mixtures by laser-induced breakdown spectroscopy

We report what we believe to be the first demonstration of the detection of trace quantities of helium and argon in binary and ternary gas mixtures with nitrogen by laser-induced breakdown spectroscopy (LIBS). Although significant quenching of helium transitions due to collisional deactivation of excited species was observed, it was found that losses in analytical sensitivity could be minimized by increasing the laser irradiance and decreasing the pressure at which the analyses were performed. In consequence, limits of detection of parts-per-million and tens of parts-per-million and linear dynamic ranges of several orders of magnitude in analyte concentration were obtained. The results of this study suggest that LIBS may have potential applications in the detection of other noble gases at trace concentrations.     

Numerical Prediction of the Noise Emission from a Turbulent Argon Thermal-Plasma Jet Issuing into Ambient Air

This paper attempts to predict the noise emission characteristics of a turbulent argon thermal-plasma jet issuing into ambient air. The flow, temperature and concentration fields and turbulence characteristics of the turbulent plasma jet are computed at first, and then the noise emission from the plasma jet to a sideline far-field observer is calculated using the approach proposed by Fortuné and Gervais (AIAA J. 37(1999)1055) for predicting the noise emission from a turbulent, hot but non-ionized, air jet after some modification. The diffusion of ambient air into the turbulent argon plasma jet is handled using the turbulence-enhanced combined–diffusion-coefficient method. Velocity fluctuation correlations (aerodynamic noise source) in the plasma jet are calculated still using the K-ɛ two-equation turbulence model, but the temperature-velocity fluctuation correlations (entropic noise source) within the jet are calculated by solving a second-order turbulent Reynolds heat-flux transport equation in order to better deal with the contribution of temperature fluctuation to the noise emission. It is shown that among the contributions of aerodynamic noise source, entropic noise source and their mixed effect, the entropic noise source (i.e. the temperature-velocity fluctuation correlations) is dominant for the noise emission from the turbulent plasma jet to the sideline observer. The noise intensity increases with increasing plasma jet temperature or velocity. The predicted noise frequency spectrum characteristics and noise intensity levels are shown to be reasonably consistent with available experimental data.     

Investigation of optimized experimental parameters including laser wavelength for boron measurement in photovoltaic grade silicon using laser-induced breakdown spectroscopy

The quantification of boron and other impurities in photovoltaic grade silicon was investigated using the LIBS technique with attention to the laser wavelength employed, temporal parameters, and the nature of the ambient gas. The laser wavelength was found to have a moderate effect on the performance of the process, while the type of purge gas and temporal parameters had a strong effect on the signal-to-background ratio (SBR) of the boron spectral emission, which was used to determine the boron concentration in silicon. The three parameters are not independent, meaning that for each different purge gas, different optimal temporal parameters are observed. Electron density was also calculated from Stark broadening of the 390.5 nm silicon emission line in order to better understand the different performances observed when using different gases and gating parameters. Calibration curves were made for boron measurement in silicon using certified standards with different purge gases while using the temporal parameters which had been optimized for that gas. By comparing the calibration curves, it was determined that argon is superior to helium or air for use as the analysis chamber purge gas with an UV laser.     

微流控电泳芯片中化学发光信号的分段门限小波降噪

采用分段门限小波降噪(STWD)方法对化学信号中的异方差噪声进行降噪处理.用STWD法和统一门限小波降噪法同时处理两种模拟信号(其中之一包含异方差噪声).结果显示,优化参数的STWD法能够更有效地提高降噪效果.采用STWD法对微流控芯片化学发光检测信号中的异方差噪声进行处理,取得了满意的降噪效果.     

基于多光谱特征融合技术的面粉掺杂定量分析方法

提出了一种基于拉曼光谱技术(Raman)和激光诱导击穿光谱技术(LIBS)的多光谱特征融合技术(MFFT),利用拉曼光谱中分子组分信息和激光诱导击穿光谱中原子组分信息之间的互补特性,采用自适应小波变换(AWT)-竞争性自适应加权(CARS)-偏最小二乘回归(PLS)建模技术,获取了面粉体系更为全面的特征信息。在多光谱特征融合技术中,首先采用AWT-CARS方法分别提取拉曼光谱和激光诱导击穿光谱中的特征变量,然后将两者的特征变量融合为一个向量,采用PLS方法构建MFFT模型,实现了面粉掺杂物的定量分析。通过对二氧化钛、硫酸铝钾等面粉掺杂体系建模分析,考察MFFT模型的有效性。结果表明,与单一拉曼光谱技术或激光诱导击穿光谱技术建立的预测模型相比,MFFT模型显著提升了模型的预测性能,二氧化钛和硫酸铝钾预测模型的线性相关系数分别从相对较差的Raman模型的0.884、0.877提升到0.981、0.980,其预测均方根误差分别从相对较差的Raman模型的0.151、0.154降低到0.069、0.068。表明多光谱特征融合技术可以准确提取Raman光谱中的分子信息和LIBS光谱中的元素信息,使其互为补充、互为校正,进而有效克服面粉基质对掺杂组分定量分析的干扰,显著提高模型的预测精度。     

Removal of major interference sources in aqueous near-infrared spectroscopy techniques

This work describes a hybrid procedure for eliminating major interference sources in aqueous near-infrared (NIR) spectra, that include aqueous influence, noise, and systemic variations irrelevant to concentration. The scheme consists of two parts: extension of wavelet prism (WPe) and orthogonal signal correction (OSC). First, WPe is employed to remove variations due to aqueous absorbance and noise; then OSC is applied to remove systemic spectral variations irrelevant to concentration. Although water possesses strong absorption bands that overshadow and overlap the absorption bands of analytes, along with noise and systematic interference, successful calibration models can be generated by employing the method proposed here. We show that the elimination of major interference sources from the aqueous NIR spectra results in a substantial improvement in the precision of prediction, and reduces the required number of PLS components in the model. In addition, the strategy proposed here can be applied to various analytical data for quantitative purposes as well.     

光谱滤波法提高激光诱导击穿光谱对蔬菜中元素Pb的检测精度

激光诱导击穿光谱(Laser induced breakdown spectroscopy, LIBS)原始光谱中包含较多噪声信号, 为探究不同滤波方法对LIBS光谱预处理的影响, 本研究以实验室Pb污染处理的蔬菜为研究对象, 采集波长范围在400.45~410.98 nm的LIBS谱线信息, 分别利用相邻平均(Adjacent averaging)、Savitzky-Golay(S-G)滤波器、快速傅里叶变换(Fast Fourier transformation, FFT)对采集的LIBS光谱进行平滑、去噪, 并结合偏最小二乘法(PLS)定量分析模型对光谱处理效果进行评价.结果表明, S-G平滑效果最优, 当S-G滤波器窗口宽度为15, 拟合阶次为3时, PLS定量模型效果最佳, 其验证集均方根误差(RMSEP)为0.26、平均相对误差(ARE)为3.7%.结果表明, 选择适合的滤波方法有助于提高LIBS光谱质量以及检测模型的精度.     

Thermodynamic and transport properties of argon/carbon and helium/carbon mixtures in fullerene synthesis

The equilibrium composition and thermodynamic and transport properties of argon; carbon and helium/carbon mixtures are calculated in the temperature range 300–20,000 K. The curves for the composition of mixtures of 50%, carbon in argon or helium are shown fir a pressure of 1.33 × 10⁴ Pa. The calculations for the heat capacity at constant pressure (C_p) and transport coefficients are validated with other studies, for the cases or pure argon and pure helium at a pressure of 10⁵ Pa. The properties of mixtures with various proportions of carbon in argon and helium are calculated. Results are presented at pressures of 105 and 1.33 × 10⁴ Pa, typical of reactors for the synthesis of fullerenes and nanotubes. It is observed that the properties of carbon and mixtures of carbon with a buffer gas (argon or helium) are very different from those of the buffer gas, thus the need to consider this effect in simulations. In general, the mixtures follow trends intermediate to those of the pure gases from which they are composed except for the thermal conductivity which shows a deviation from this tendency in the region between 11,500 and 19,000 K for argon/carbon mixtures and between 8,000 and 12,000 K for helium/carbon mixtures. Also, the electrical conductivity of mixtures of low carbon concentration is very close to that ofpure carbon. A datafile containing the transport properties of mixtures for pressures between 10⁴ and 10⁵ Pa is available free of charge from the authors.     

Inter-pulse delay optimization in dual-pulse laser induced breakdown vacuum ultraviolet spectroscopy of a steel sample in ambient gases at low pressure

Time-integrated spatially-resolved Laser Induced Breakdown Spectroscopy (LIBS) has been used to investigate spectral emissions from laser-induced plasmas generated on steel targets. Instead of detecting spectral lines in the visible/near ultraviolet (UV), as investigated in conventional LIBS, this work explored the use of spectral lines emitted by ions in the shorter wavelength vacuum ultraviolet (VUV) spectral region. Single-pulse (SP) and dual-pulse LIBS (DP-LIBS) experiments were performed on standardized steel samples. In the case of the double-pulse scheme, two synchronized lasers were used, an ablation laser (200 mJ/15 ns), and a reheating laser (665 mJ/6 ns) in a collinear beam geometry. Spatially resolved and temporally integrated laser induced plasma VUV emission in the DP scheme and its dependence on inter-pulse delay time were studied. The VUV spectral line intensities were found to be enhanced in the DP mode and were significantly affected by the inter-pulse delay time. Additionally, the influence of ambient conditions was investigated by employing low pressure nitrogen, argon or helium as buffer gases in the ablation chamber. The results clearly demonstrate the existence of a sharp ubiquitous emission intensity peak at 100 ns and a wider peak, in the multi-microsecond range of inter-pulse time delay, dependent on the ambient gas conditions.