Flow produced in a conical container by a rotating endwall

Numerical calculations have been carried out for flow in a truncated cone generated by rotation of one endwall. For both convergent (radius increasing with approach to the rotating endwall) and divergent geometries, vortex breakdown is suppressed beyond a certain angle of inclination of the sidewall. At the same time Moffat eddies of increasing strength and extent appear in the corner between the sidewall and the non-rotating endwall. For the divergent geometry, a zone of recirculation appears on the sidewall and eventually merges with the Moffat eddies. The flow phenomena identified from streamline patterns are consistent with the calculated variation of pressure around the periphery of the computational domain.     

CuSO_4溶液中Cu元素浓度的激光诱导击穿光谱测量研究

利用激光诱导击穿光谱技术对CuSO4溶液中的Cu元素浓度进行实验测量。利用配置的七种浓度的CuSO4溶液,采用统计探索性数据分析方法给出了Cu元素定标曲线,其拟合度系数R2大于0.98,激光诱导击穿光谱的平均相对偏差值为6.9%,Cu元素的平均最小检测限为12ppm。利用去一交互检验方法采用分析谱线CuⅠ324.75nm和CuⅠ327.40nm对应的七种溶液的平均测量相对误差分别为6.52%和5.86%。当Cu元素浓度在10ppm时实验相对误差较大,其值为10.3%,而浓度达到2 000ppm时相对误差值减小,仅为1.1%,说明LIBS技术在溶液较低元素浓度检测方面的准确度有待提高。研究结果表明激光诱导击穿光谱技术在环境水污染重金属元素检测方面具有潜在的应用前景。     

阶梯AlGaN外延新型Al0.25Ga0.75N/GaNHEMTs器件实验研究

本文报道了作者提出的阶梯AlGaN外延层新型AlGaN/GaN HEMTs结构的实验结果. 实验利用感应耦合等离子体刻蚀(ICP)刻蚀栅边缘的AlGaN外延层, 形成阶梯的AlGaN 外延层结构, 获得浓度分区的沟道2DEG, 使得阶梯AlGaN外延层边缘出现新的电场峰, 有效降低栅边缘的高峰电场, 从而优化了AlGaN/GaN HEMTs器件的表面电场分布. 实验获得了阈值电压-1.5 V的新型AlGaN/GaN HEMTs器件. 经过测试, 同样面积的器件击穿电压从传统结构的67 V提高到新结构的106 V, 提高了58%左右; 脉冲测试下电流崩塌量也比传统结构减少了30%左右, 电流崩塌效应得到了一定的缓解.     

纳秒激光诱导等离子体发射光谱中的自吸收效应

为了减小激光诱导等离子体发射光谱中光谱线的自吸收效应,提高激光光谱分析技术对物质中高含量元素的检测水平,实验采用了一种平面反射镜装置约束等离子体,比较了有或无平面反射镜装置时光谱线的线型变化。实验表明,在无平面反射镜装置时,样品元素Al,Mg和Mn的光谱线半高全宽度分别为0.16,0.24,0.058nm,而采用由四块平面反射镜组成的装置在空间上约束激光等离子体时分别为0.11,0.13,0.047nm。结果表明,光谱线的自吸收明显减小,谱线线型变得比较锐且强度显著提高。通过观测等离子体照片,测量等离子体温度和电子密度,分析讨论了激光光谱自吸收效应降低的原因。     

Breakdown potential modelling of austenitic stainless steel

The breakdown potential is a crucial factor in the study of pitting corrosion resistance of stainless steel. This work aims to demonstrate the advantage of different chemometric techniques to estimate the breakdown potential of austenitic stainless steel. In order to predict pitting corrosion behaviour of stainless steel, a total of 60 samples of this alloy were subjected to electrochemical tests varying chloride ion concentration, pH and temperature. The experimental values of the breakdown potential, in addition to the tested environmental factors, were used to construct the predictive models based on support vector machines and artificial neural networks. A multiple‐comparison study based on statistic tests was applied to determine the optimal configuration for each technique. According to the results, support vector machines became a suitable and reliable technique to be applied in the modelling of the breakdown potential of austenitic stainless steels. This technique outperformed the models based on artificial neural networks and provided a useful tool to compare the pitting corrosion resistance of stainless steel in different environmental conditions without recourse to polarization tests. Therefore, this model presented a relevant meaning in science and engineering applications. Copyright © 2014 John Wiley & Sons, Ltd.     

Integrated analytical methodologies for the study of corrosion processes in archaeological bronzes

The investigations on structure and micro-chemical composition of archaeological metal alloys are needed in archaeometry. The aim of this study is devoted both to acquire information about their provenance and production technology, and to improve our understanding about the corrosion processes. In this paper we present the study of the corrosion phenomena of bronze samples, laboratory-made according to binary, ternary and quaternary alloys typical of Roman archaeometallurgical production through an integrated methodology based on the use of non or micro invasive physical techniques. Among the analysed samples, two were artificially aged through burial in the archaeological site of Tharros, along the west coast of Sardinia (Italy). The corrosion products, typical of the bronzes in archaeological sites near the sea, have been characterized by non invasive and micro-destructive measurements. In particular, the corrosion patinas were examined through optical microscopy, scanning electron microscopy and microanalysis, X-ray fluorescence and laser ablation spectroscopy. The use of integrated technologies allowed us to determine both the elemental composition and surface morphology of the patina, highlighting the correlation between patina nature and chemical composition of the burial context. Moreover, data obtained by the laser-induced breakdown spectroscopy along the depth profile on the samples, have yielded information about the stratigraphic layers of corrosion products and their growth. Finally, the depth profiles allowed us to verify both the chemical elements constituting the patina, the metal ions constituting the alloy and the occurrence of migration phenomena from bulk to the surface.     

Influence of variable selection on partial least squares discriminant analysis models for explosive residue classification

Using a series of thirteen organic materials that includes novel high-nitrogen energetic materials, conventional organic military explosives, and benign organic materials, we have demonstrated the importance of variable selection for maximizing residue discrimination with partial least squares discriminant analysis (PLS-DA). We built several PLS-DA models using different variable sets based on laser induced breakdown spectroscopy (LIBS) spectra of the organic residues on an aluminum substrate under an argon atmosphere. The model classification results for each sample are presented and the influence of the variables on these results is discussed. We found that using the whole spectra as the data input for the PLS-DA model gave the best results. However, variables due to the surrounding atmosphere and the substrate contribute to discrimination when the whole spectra are used, indicating this may not be the most robust model. Further iterative testing with additional validation data sets is necessary to determine the most robust model.     

Time-resolved optical emission spectroscopic measurements of He plasma induced by a high-power CO2 pulsed laser

Laser-induced breakdown spectroscopy of helium plasma, initially at room temperature and pressures ranging from 12 to 101 kPa was investigated using a transverse excitation atmospheric CO₂ pulsed laser (λ = 9.621 and 10.591 μm, a full width at half maximum of 64 ns, and an intensity from 1.5 to 5.36 GW cm⁻²). The helium breakdown spectrum is mainly due to electronic relaxation of excited He, He⁺ and H. Plasma characteristics were examined in detail on the emission lines of He and He⁺ by the time-integrated and time-resolved optical emission spectroscopy technique. Optical breakdown threshold intensities, ionization degree and plasma temperatures were obtained. An auxiliary metal mesh target was used to analyze the temporal evolution of the species in the plasma. The results show a faster decay of the continuum emission and He⁺ species than in the case of neutral He atoms. The velocity and kinetic energy distributions for He and He⁺ species were obtained from time-of-flight measurements. Electron density in the laser-induced plasma was estimated from the analysis of spectral data at various times from the laser pulse incidence. Temporal evolution of electron density has been used for the estimation of the three-body electron-ion recombination rate constant.     

Diagnosis of lubricating oil by evaluating cyanide and carbon molecular emission lines in laser induced breakdown spectra

To prevent engine failure it is essential to change lubricating oil regularly before it loses its protective properties. It is also necessary to monitor the physical and chemical conditions of the oil to reliably determine the optimum oil-change intervals. The present work focuses on studying evolution of the cyanide (CN) and carbon (C₂) molecular spectral emission lines in the laser induced breakdown spectra of lubricating oil as a function of its consumption. The intensities of these molecular bands have been taken as indicator of engine oil degradation at certain mileage. Furthermore, the percentage of decay of CN and C₂ integral intensity values at the corresponding mileage was calculated in order to relate it to the degree of consumption of the motor oil. Such percentage decay of the CN and C₂ integral intensities have been found to increase gradually with increasing mileage which is accompanied with increasing depletion of engine oil. The results of using LIBS technique in the present measurements proved that it is possible to have a direct, straightforward and easy method for prediction of lubricating oil degree of consumption. This may facilitate scheduling the proper time and/or mileage intervals for changing the oil to avoid any possibility of engine failure.     

Identification and discrimination of bacterial strains by laser induced breakdown spectroscopy and neural networks

A method based on laser induced breakdown spectroscopy (LIBS) and neural networks (NNs) has been developed and applied to the identification and discrimination of specific bacteria strains (Pseudomonas aeroginosa, Escherichia coli and Salmonella typhimurium). Instant identification of the samples is achieved using a spectral library, which was obtained by analysis using a single laser pulse of representative samples and treatment by neural networks. The samples used in this study were divided into three groups, which were prepared on three different days. The results obtained allow the identification of the bacteria tested with a certainty of over 95%, and show that only a difference between the bacteria can cause identification. Single-shot measurements were sufficient for clear identification of the bacterial strains studied. The method can be developed for automatic real time, fast, reliable and robust measurements and can be packaged in portable systems for non-specialist users.