激光拉曼指纹图谱鉴别石油产品初探

利用激光拉曼指纹图谱对石油产品进行特性测试与分析。通过比较主要指纹峰的拉曼位移和相同拉曼位移处的拉曼强度比值,鉴别了不同种类的石油产品;对不同社会加油站相同型号汽油的拉曼光谱进行测试,检测了汽油的质量。该方法在油品鉴别和质量检测中取得了良好效果,具有快速、简便、灵敏度高、对样品无损伤等优点。     

基于激光拉曼光谱的水面油膜厚度测量方法研究

为了实现水体表面油膜厚度的快速非接触检测,基于激光拉曼光谱检测技术,搭建了水体表面油膜厚度拉曼光谱检测系统。以532 nm激光作为激发光源,以常见的柴油和汽油为例研究了不同油品的拉曼光谱特性,研究结果表明,油膜拉曼光谱响应特性与油品密切相关,相同油膜厚度情况下不同油品的拉曼光谱曲线有明显的差异,97#汽油在1 651 cm-1光谱强度要高于90#汽油。随着油膜厚度的增加,柴油316和1 451 cm-1光谱强度和汽油1 651 cm-1拉曼位移光谱强度增加,油拉曼光谱信号变强;根据油水界面拉曼光谱特征,设计了油膜厚度计算因子,实验证明随着油膜厚度增加,油膜厚度计算因子r_film呈下降趋势。可以将油膜厚度计算因子作为水体表面油膜厚度测量的一种依据。     

基于空间位移拉曼光谱的皮肤含水量无创检测

基于空间位移拉曼光谱原理,搭建了一套可以实现微小空间位移的装置,确定了最优的空间位移距离为300μm,用于穿透皮肤表层,减少皮肤表面水份、油脂等污染物的干扰,最终采集到皮肤内层的水份拉曼信号。该装置采用拉曼波数在3 390 cm^-1(水拉曼峰)和2 935 cm^-1(蛋白峰)处的强度之比确定组织中的水-蛋白比例,采用便携式光谱仪使设备便于移动,探头和光谱仪以光纤相连使探头可灵活操作,设计满足临床使用要求。实验中检测了7个人、每人10个共70个不同位置的皮肤光谱,将光谱进行去背景算法处理,然后得到精确的拉曼峰强度。以电学法皮肤水份测试仪测试结果作为对比,以组内相关系数作为一致性分析指标,由单个测量组内相关系数为0.889可以看出,基于空间位移拉曼光谱法的人体活体皮肤含水量检测具有较高可行性。     

拉曼及近红外吸收光谱的燃油混合物量化分析

生物柴油是典型的"绿色能源",具备良好的环保性和燃料特性,通常与柴油混合使用在柴油发动机上。但是目前世界各国柴油与生物柴油混合的比例标准参次不齐,没有一个统一的标准,并且不同比例的柴油/生物柴油混合物具有不同的燃烧性能,也会对柴油发动机产生一定程度的影响。为了能够快速、准确的测量柴油/生物柴油混合物中的生物柴油浓度,近红外光谱和拉曼光谱在燃油检测方面已经得到广泛的应用。利用拉曼及近红外光谱对柴油/生物柴油混合物中的生物柴油浓度进行了量化分析研究。首先采集了柴油/生物柴油混合燃油的拉曼光谱及近红外吸收光谱,然后利用平滑、基线校正、归一化等方法对采集到的光谱进行预处理。从光谱图中观察到,在柴油/生物柴油混合物的拉曼光谱和近红外光谱中都有C=O特征光谱区域,且该光谱区域的光谱峰都随生物柴油的浓度增加而越来越明显。拉曼光谱中,随生物柴油浓度变化的主要C=O特征光谱区域是在1 743 cm~(-1)位置处的特征峰,在近红外光谱中,随生物柴油浓度变化的主要C=O特征光谱区域是在4 659 cm~(-1)处的特征峰。然后分别根据强度比方法和偏最小二乘(PLS)回归方法建立了相应的混合燃油中生物柴油浓度预测模型。结合强度比方法建立特征峰强度比的生物柴油浓度预测模型,由混合燃油的拉曼光谱和近红外光谱建立的C=O特征峰线性预测模型相关系数分别为0.947 2和0.996 2;结合偏最小二乘(PLS)回归法建立特征光谱区域的生物柴油浓度预测模型,由混合燃油的拉曼光谱和近红外光谱特征区域建立的相应预测集相关系数(R~2)分别为0.981 5和0.991 2,相应的预测均方根误差(RMSE)分别为0.093 7和0.012 9。结果表明,在混合燃油中,使用近红外光谱中的C=O光谱区域建立的生物柴油浓度预测模型会得到更准确的预测结果。     

激光拉曼光谱法无损鉴别人参及其伪品

利用激光拉曼光谱技术并结合二阶导数拉曼光谱,对人参及其拟伪品峨参、北沙参、桔梗进行了鉴别。人参及其伪品均在拉曼光谱中出现了1 460,1 130,1 086,942,483cm-1等拉曼振动峰,根据这些拉曼位移可以判断出在人参及其伪品中都含有糖类物质。北沙参的拉曼谱图中出现了不同于其他三种药材的2 206cm-1的拉曼特征峰。峨参中出现了1 050和1 869cm-1相对应的链状酯类化合物的拉曼振动峰。桔梗中出现了1 227,600,691cm-1等明显不同于其他三种药材的拉曼振动峰。利用这些拉曼振动峰的差异可将人参及其伪品进行很好的区分。再利用二阶导数拉曼光谱图对人参及其伪品的鉴别结果进行进一步的补充说明。此鉴别方法与常规的光谱法相比具有更直接、快速,并且具有不破坏样品的原性质的特点。     

激光拉曼光谱检测灵芝孢子油

采用激光拉曼光谱分析比较了灵芝孢子油、橄榄油、葵花籽油及鱼肝油的光谱特征,结果显示激光拉曼光谱法可以用于快速检测灵芝孢子油：灵芝孢子油具有位于1 563 cm-1处峰强较弱线宽较宽的特征拉曼峰,而且位于1 445和1 660 cm-1两处拉曼峰的相对强度比与其他油不同。同时运用激光拉曼光谱法分析了变质的灵芝孢子油和廉价的灵芝孢子油,发现暴露在空气中一段时间后的灵芝孢子油的活性成分基本被氧化了,市场上廉价的灵芝孢子油可能是由变质的灵芝孢子油、葵花籽油、或其他廉价植物油混合掺杂而成的。     

中草药绞股蓝的傅里叶变换红外和拉曼光谱分析

利用傅里叶变换红外和拉曼光谱法直接、快速地测定了中草药绞股蓝样品 ,并对所测样品的红外、拉曼光谱图进行比较。结果表明 ,红外光谱图中各吸收峰位置与拉曼光谱图中各散射特征峰位置相对应 ,其关系互补。采用傅里叶变换红外和拉曼光谱分析法 ,对中草药绞股蓝的成份研究和特征波谱的鉴别 ,能为合理利用绞股蓝资源和寻找绞股蓝新的有效成分提供依据     

诺氟沙星与DNA的拉曼光谱研究

报道了诺氟沙星(NFX)及诺氟沙星胶囊内容物的FT-Raman光谱和在银胶基底上的表面增强拉曼光谱(SERS),归属了各个振动;研究了诺氟沙星与DNA的相互作用的SERS,结果表明:胶囊内容物的拉曼光谱图与对照品的拉曼光谱图的特征振动峰:C-F键的伸缩振动,C=C伸缩振动,O-C-O的对称伸缩振动峰值未发生变化,发生变化主要是分子骨架振动峰,诺氟沙星胶囊的辅料对拉曼光谱无实质影响,可建立拉曼光谱法检测诺氟沙星药物的分析方法;诺氟沙星可以在没有金属离子的存在下与DNA直接作用,与DNA相互作用的主要键合模式是插入作用,NFX分子中的平面结构插入DNA的双螺旋碱基平面,为深入了解喹诺酮类抗生素的抗菌机理提供可靠依据.     

拉曼光谱法快速鉴别黄芩中药材

本文利用付里叶变换拉曼光谱法和计算机辅助比对软件对 1 2个不同产地、不同种植方式及不同采集时间的中药材黄芩进行了快速鉴别 ,结果表明可以由拉曼光谱的特征频率与强度鉴别不同种植方式的黄芩样品。此鉴别方法与常规的光谱法相比具有更直接、快速 ,不破坏样品的原性质的特点 ;与传统的药材鉴别方法相比更准确 ;与民间传统的鉴别方法相比更具有科学性。     

部分临床药物的拉曼光谱研究

针对目前临床药物拉曼光谱的缺乏和药物检测领域的现状,利用拉曼光谱技术对抗生素、抗组织胺、血凝酶和止吐剂等几类常用临床药物进行了拉曼光谱的测量和研究。通过观测上述具有良好拉曼活性的药物样品拉曼光谱,不仅确定了样品拉曼峰的位移、强度和线宽,还探索了其包络的线形等光谱特性。通过分析和比较拉曼光谱图,找出各药物间的异同; 对于那些由于拉曼活性低或拉曼光谱的复杂样品,虽然暂时无法识别,但也进行了尝试性的测量或提出了测量建议。研究表明: 小分子药物的光谱特征很明显,拉曼峰分布较广, 对其进行光谱识别简单易行; 而大分子都表现出较弱的光谱特征峰, 常常伴随复杂的包络,不仅导致了对其光谱识别的困难, 也很难准确确定特征峰位置。对于不同药物,提出了用拉曼光谱测量和分析其药物成分的可行性,并通过分析其拉曼光谱的特性, 为医学工作者识别和分析药物成分提供了实验证据。不仅为建立药物的拉曼光谱数据库奠定了基础。还使业界看到了快速识别和检测药物的前景,从而促进拉曼光谱技术在药物检测上的运用。     

部分动植物油的拉曼光谱研究

利用拉曼光谱技术分别研究了植物油和动物脂肪油的光谱特性。通过自适应迭代惩罚最小二乘法的基线校正方法, 对所测得的拉曼光谱进行了数据处理,获得了它们的微观信息。进而通过选取其中部分油的拉曼光谱,进行了植物油的光谱、动物脂肪油的光谱以及动物脂肪油和植物油之间的光谱比较和分析,从而发现了多种植物油光谱(包括多个频移范围内的频移大小以及强度大小)的差异,也发现了动物脂肪油与植物油的拉曼光谱间的差异。不但提供了辨识不同食用油的光谱依据,也证明了拉曼光谱是一种识别不同油品的有效方法。     

Identification of waste cooking oil and vegetable oil via Raman spectroscopy

This paper made a qualitative identification of ordinary vegetable oil and waste cooking oil based on Raman spectroscopy. Raman spectra of 73 samples of four varieties oil were acquired through the portable Raman spectrometer. Then, a partial least squares discriminant analysis (PLS‐DA) model and a discrimination model based on characteristic wave band ratio were established. A classification variable model of olive oil, peanut oil, corn oil and waste cooking oil that was established through the PLS‐DA model could identify waste cooking oil accurately from vegetable oils. The identification model established based on selection of waveband characteristics and intensity ratio of different Raman spectrum characteristic peaks could distinguish vegetable oils from waste cooking oil accurately. Research results demonstrated that both ratio method and PLS‐DA could identify waste cooking oil samples accurately. The identification model based on characteristic waveband ratio is simpler than PLS‐DA model. It is widely applicable to identification of waste cooking oil. Copyright © 2016 John Wiley & Sons, Ltd.     

拉曼光谱结合模式识别方法用于大豆原油掺伪的快速判别

大豆原油是我国的战略储备物资,然而目前储油市场上频繁出现大豆原油掺混的现象严重影响了食用油储备安全。基于此,通过大豆原油与部分植物精炼油拉曼谱图的特征差异,并结合主成分分析-支持向量机(PCA-SVM)模式识别建立了大豆原油是否掺伪的快速判别方法。以28个大豆原油、46个精炼油、110个掺伪油的拉曼谱图为模型样本;选择位于780～1 800 cm-1波段的谱图,预处理方法同时采用Y轴强度校正、基线校正和谱图归一化法;在此基础上应用PCA法提取特征变量,即以贡献率最高前7个主成分为变量进行SVM分析。SVM校正模型的建立是以随机选取的20个大豆原油和75个掺伪油样组成校正集,以8个大豆原油和35个掺伪油样组成验证集,分别运用并比较四种核函数算法建立的大豆原油SVM分类模型,并采用网格搜索法(grid-search)优化模型的参数,以四种模型的分类性能作为评判标准。结果表明：应用线性核函数算法构建的SVM分类模型可以很好地完成掺伪大豆原油的判别,校正集识别准确率达到100%,预测结果的误判率为0,判别下限为2.5%。结果表明应用拉曼光谱结合化学计量学能够用于大豆原油掺伪的快速鉴别。拉曼光谱简便、快速、无损、几乎没有试剂消耗,适合现场检测,从而为大豆原油的掺伪分析提供了一种新的备选方法。     

Quantitative detection of adulterated olive oil by Raman spectroscopy and chemometrics

Commercially available extra virgin olive oils are often adulterated with some other cheaper edible oils with similar chemical compositions. A set of extra virgin olive oil samples adulterated with soybean oil, corn oil and sunflower seed oil were characterized by Raman spectra in the region 1000–1800 cm⁻¹. Based on the intensity of the Raman spectra with vibrational bands normalized by the band at 1441 cm⁻¹ (CH₂), external standard method (ESM) was employed for the quantitative analysis, which was compared with the results achieved by support vector machine (SVM) methods. By plotting the adulterant content of extra virgin olive oil versus its corresponding band intensity in the Raman spectrum at 1265 cm⁻¹, the calibration curve was obtained. Coefficient of determination (R²) of each curve was 0.9956, 0.9915 and 0.9905 for extra virgin olive oil samples adulterated with soybean oil, corn oil and sunflower seed oil, respectively. The mean absolute relative errors were calculated as 7.41, 7.78 and 9.45%, respectively, with ESM, while they were 5.10, 6.96 and 4.55, in the SVM model, respectively. The prediction accuracy shows that the ESM based on Raman spectroscopy is a promising technique for the authentication of extra virgin olive oil. The method also has the advantages of simplicity, time savings and non‐requirement of sample preprocessing; especially, a portable Raman system is suitable for on‐site testing and quality control in field applications. Copyright © 2011 John Wiley & Sons, Ltd.     

Nuclear magnetic resonance of some oils

The author subjected some oils to nuclear magnetic resonance in order to obtain information on their structure and to compare their behaviour at NMR. Saturation curves were obtained and the longitudinal and transverse relaxation times of the resonance of these oils were investigated. Relations were derived for calculating the number of resonating hydrogen nuclei per unit volume of oil, both by direct study of the signals on a cathode ray oscilloscope and by recording the differential of the absorption curve of NMR. The number of hydrogen nuclei per unit volume and mass of the oils was calculated. Equations were derived for the longitudinal relaxation time of glycerine and castor oil. Relations were also found from which qualitative conclusions could be drawn as to the average molecule mass of the oils and the mean distance of the resonating hydrogen nuclei of the different oils. Castor oil, bearing oil 207, paraffin oil, transformer oil B, one lubricating oil of commercial quality and methyl silicon oil were investigated and glycerine was used as the normal of the relaxation time and signal intensity. In addition, the intensities of the NMR signals of some naphtha oils, immersion oil and some polymer oils were measured.The author used an arrangement for observing and recording the NMR signal with an autodyne detector, which has been described in another paper. The sensitivity curve of the autodyne detector was measured and respected in the calculations.     

Quantitative analysis of essential oils from rosemary in virgin olive oil using Raman spectroscopy and chemometrics

In this work, virgin olive oil mixed with essential oils from rosemary has been analyzed by means of Raman spectroscopy. First of all, experimental design has been employed in order to define the Raman spectroscopy's parameters, final measuring conditions were: acquisition time of 30 s, five accumulations, and the intensity of the laser power at 75 mW. The Raman spectra were initially measured at full range (150–3000 cm⁻¹), but a narrower window assured faster accumulations and more accurate predictions. The calibration solutions of eucalyptol and camphor in olive oil were prepared following a central composite design and different spectra pre‐processing algorithms were evaluated. To conclude, essential oils obtained by means of Supercritical Fluid Extraction, Ultrasounds, and hydrodistillation were mixed with virgin olive oil and quantified with Raman spectroscopy. Predicted concentrations of the olive oil mixtures were compared with concentrations obtained for the same samples by a Comprehensive Two‐Dimensional Gas Chromatographic (GC × GC) method. Copyright © 2011 John Wiley & Sons, Ltd.     

基于稀疏非负矩阵分解和支持向量机的海洋溢油近红外光谱鉴别分析

提出一种海洋溢油近红外光谱特征提取与种类鉴别新方法.海面溢油种类鉴别对现场应急处置方案的制定和可疑溢油源的追踪具有重要意义.采用傅里叶变换近红外光谱仪测定汽油、柴油、煤油三类模拟海洋溢油样本的近红外光谱,基于稀疏非负矩阵分解算法对光谱进行特征提取,采用五重交义检验,对210个样本进行训练,建立基于支持向量机的溢油光谱定...     

基于激光拉曼检测技术的输油管道原油鉴别方法

为降低长距离原油输送过程中混油产生的损失, 需定时检测管线原油成分以确定是否出现混油事故。常规检测输油管线原油成分需从现场管线中取样后, 再进行室内检测, 该类技术操作复杂且易受环境因素的影响, 未能实时反映管道混油后油品成分变化。文中应用激光拉曼光谱对原油识别检测进行了实验研究, 试验选取辽河油田不同区块2种原油, 通过特征峰及图谱分析, 实现不同类型原油的识别。结果表明, 2 800 cm-1~3 000 cm-1区域特征峰是激光拉曼证明烷烃存在的重要标志, 该段拉曼谱图特征峰的不同代表了烷烃组分的差异性, 可以有效区分不同类型的原油。该方法的进一步研究, 有望形成一套油品快速、实时检测的技术方法。     

姜油细胞原位拉曼光谱研究

提出一种用拉曼光谱原位分析新鲜姜油细胞中姜油主成分的方法。用徒手切片制备新鲜姜样品,该样品置于DXR 激光共焦显微拉曼光谱仪下,用20倍物镜观察到油细胞,将激光聚焦在该油细胞上,获得了姜油细胞中姜油的拉曼光谱,共21条谱峰。不同油细胞上获得的拉曼光谱非常相似。获得了姜精油的拉曼光谱,与姜精油拉曼光谱的37条谱峰比较,油细胞有19条谱峰与之有对应关系。为了解释油细胞精油及姜精油的拉曼光谱,用密度泛函理论计算了姜烯的拉曼光谱。姜精油拉曼光谱有31条谱峰,油细胞中有19条谱峰与计算光谱有对应关系。该研究提供了一种拉曼光谱技术与密度泛函理论计算结合的快速容易的精油质量控制方法。     

荧光光谱法快速鉴别花生油、芝麻油和调和油

比较分析了不同品种、同品种不同厂家、不同批次的市售花生油、芝麻油、调和油的分子荧光光谱差异特征,结合系统聚类分析法进行品种鉴别。结果表明:3种食用植物油的荧光光谱图具有各自不同特征,同一品种不同厂家的谱图存在一定的差异,同品种同厂家不同批次的也有微小差异。提取荧光谱图特征信息,利用系统聚类和三维聚类识别模式,从宏观上简便、直观、快速地鉴别3种食用植物油的品种。