流场环境下复杂囊泡的动力学行为

采用非平衡态分子动力学方法研究了二维复杂囊泡在剪切流中的动力学行为. 模拟发现了复杂囊泡经典的翻滚(tumbling)、摇摆(trembling)和坦克履(tank-treading)行为, 还观察到由坦克履行为向平动行为(translating)的转变. 囊泡的平动行为与剪切率大小、复杂囊泡的形状密切相关. 当大囊泡均匀嫁接较多数目的小囊泡后, 其平动方式消失. 该研究有益于加深对囊泡在剪切流场中复杂性行为的理解.     

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.     

Optimal deteriorating items production inventory models with random machine breakdown and stochastic repair time

This study develops deteriorating items production inventory models with random machine breakdown and stochastic repair time. The model assumes the machine repair time is independent of the machine breakdown rate. The classical optimization technique is used to derive an optimal solution. A numerical example and sensitivity analysis are shown to illustrate the models. The stochastic repair models with uniformly distributed repair time tends to have a larger optimal total cost than the fixed repair time model, however the production up time is less than the fixed repair time model. Production and demand rate are the most sensitive parameters for the optimal production up time, and demand rate is the most sensitive parameter to the optimal total cost for the stochastic model with exponential distribution repair time.     

LIBS对钛合金焊缝中成分的原位统计分布分析表征

钛合金凭借其强度高、耐蚀性好、耐热性高等特点已经被广泛应用于航天、海洋、生物医药等诸多领域,其中Ti-6Al-4V（TC4）合金的耐热性、强度、塑性、韧性、成形性、可焊性、耐蚀性和生物相容性均较好,已成为钛合金工业中的王牌合金。钛合金在激光焊接时,加入表面活性剂可以增加焊缝熔深、提高焊接效率、改善焊缝微观组织的不均匀性,但是可能会改变熔合区和焊缝区中元素含量及其分布状态,从而可能会对材料的性能产生一定的影响。运用LIBS分析技术对TC4钛合金焊接试样表面进行面扫描同步获得多元素成分信息,同时结合原位统计分布分析方法（OPA）,实现了对钛合金母材、熔合区、焊缝成分及其分布状态的快速表征,为活性剂的选择和焊接后钛合金的材料性能提供一种新的评价手段。选取了两个使用不同活性剂进行焊接的TC4钛合金薄板试样,选取焊缝纵切面方向作为分析面,采用320目的氧化铝砂纸进行表面处理,利用LIBSOPA系统进行成分分布统计表征。首先,对激发光斑和剥蚀条件进行条件优化,最终选择200 μm的激发光斑、10个预剥蚀脉冲10个剥蚀脉冲进行实验,并建立了钛合金中C,Al,V,Fe,Si和Ti六个元素的校准曲线（其中Si元素主要来自活性剂）;然后对钛合金焊接样品进行了区域扫描,并对元素含量和分布状态进行了统计表征。同时,在钛合金焊接样品的不同部位进行分区取样,采用高频红外法分析C元素含量,并与LIBSOPA结果进行比对,两种测试方法结果吻合。元素Al,V,Fe,Si和Ti分布结果与微束X荧光光谱法对应性较好。运用LIBSOPA 技术实现了对钛合金母材、熔合区、焊缝中多元素的成分分布表征,为快速判定钛合金焊缝中成分及分布状态提供了全新的评价表征手段。