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.     

基于衰减全反射式太赫兹时域光谱技术的食用油光谱特性研究

食用油是人类营养和能量的重要来源,为人体提供必需的脂肪酸,研究食用油在太赫兹波段光学特性,对食用油成分分析及品质评价具有重要价值。衰减全反射式太赫兹时域光谱技术是一种新型的太赫兹时域光谱技术,通过样品与倏逝波的相互作用,获取样品的太赫兹光谱。与透射式或反射式太赫兹时域光谱技术相比,该技术能有效地避免测量食用油等液体样品时样品池对光学参数的影响,并能获得样品的精确光学参数。分别利用透射式太赫兹时域光谱技术和衰减全反射式太赫兹时域光谱技术测量了大豆油的吸收光谱。结果表明,与透射式太赫兹时域光谱技术相比,衰减全反射式太赫兹时域光谱技术能更有效地提取大豆油的吸收系数、吸收峰分布等光学特性。进一步利用衰减全反射式太赫兹时域光谱技术研究了大豆油、核桃油、葡萄籽油在太赫兹波段的光学特性,获得了三种食用油在1~1.8 THz范围内的折射率谱和吸收光谱。利用密度泛函理论计算了食用油中四种主要成分(软脂酸、硬脂酸、油酸和亚油酸)在太赫兹波段的振动、转动模式,理论计算结果同实验测量结果吻合较好。研究表明,在太赫兹波段食用油的吸收峰与所含脂肪酸分子种类与含量有关,其主要来源为脂肪酸分子的低频振动和转动。研究成果对食用油成分定性定量分析及品质检测等具有指导意义。     

NMR properties of petroleum reservoir fluids

NMR well logging of petroleum reservoir require the measurement of the NMR response of water, oil, and gas in the pore space of rocks at elevated temperatures and pressures. The viscosity of the oil may range from less than 1 cp to greater than 10,000 cp. Also, the oil and gas are not a single component but rather a broad distribution of components. The log mean T1 and T2 relaxation time of dead (gas free) crude oils are correlated with viscosity/temperature and Larmor frequency. The relaxation time of live oils deviate from the correlation for dead crude oils. This deviation can be correlated with the methane content of the oil. Natural gas in the reservoir has components other than methane. Mixing rules are developed to accommodate components such as ethane, propane, carbon dioxide, and nitrogen. Interpretation of NMR logs uses both relaxation and diffusion to distinguish the different fluids present in the formation. Crude oils have a broad spectrum of components but the relaxation time distribution and diffusion coefficient distribution are correlated. This correlation is used to distinguish crude oil from the response of water in the pores of the rock. This correlation can also be used to estimate viscosity of the crude oil.     

The use of infrared spectroscopy in combination with chemometrics for quality control and authentication of edible fats and oils: A review

Edible fats and oils provide a significant contribution in our diet and daily life, as cooking or frying oil, or as components used in food, pharmaceutical, and cosmetics products. Fats and oils are characterized by specific values, including acid value, saponification value, iodine value, and peroxide value, as well as the oxidation products which occur during storage due to oxidative and hydrolytic deterioration. Currently, due to the high price of edible fats and oils, some unethical producers adulterate high-value edible oils like olive oil with low-priced oils like palm and corn oils; therefore the authentication analysis of edible fats and oils must be assured by introducing reliable and fast methods like infrared spectroscopy. Fourier transform infrared (FTIR) spectroscopy is an ideal technique for monitoring the quality control of fats and oils due to its property as a “fingerprint spectra technique,” which allows analysts to differentiate among fats and oils. FTIR spectra signals of fats and oils are very complex. Fortunately, a statistical technique called chemometrics can be used to handle the complex FTIR spectral data. Chemometrics in combination with FTIR spectroscopy has been widely used in many aspects of monitoring quality control of edible fats and oils including their authenticity.     

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。     

基于液芯光纤的激光诱导荧光食用油种类鉴别研究

组建了一套基于液芯光纤的激光诱导荧光食用油鉴别装置。研究了不同液芯光纤长度对食用油激光诱导荧光光谱的影响,分析了不同种类食用油激光诱导荧光光谱之间的差异。八种食用油共320份样本荧光数据在1 m长液芯光纤内采集,采用主成分分析方法对食用油荧光数据进行降维处理,利用偏最小二乘判别分析(PLS-DA)方法建立食用油种类的鉴别模型。结果表明,使用液芯光纤后,食用油荧光强度得到较大的增强。随着液芯光纤长度增加,食用油荧光特征峰逐渐增加并且食用油的激光诱导荧光光谱会产生红移现象,当液芯光纤长度超过80 cm后,红移趋于饱和。不同食用油的荧光光谱形状差异较大,可用于区分不同种类食用油。利用主成分1和主成分2绘制的主成分得分图显示,不同种类食用油呈现很好的聚集。当选用主成分数为10时,建立的PLS-DA食用油种类鉴别模型对训练集和预测集样本识别率均达到100%。说明本装置用于食用油种类的快速鉴别具有较高的准确性。     

基于拉曼光谱的食用植物油快速鉴别

提出了一种基于拉曼光谱的食用植物油快速鉴别方法。基于已知类别的食用植物油样本进行建模,首先对原始拉曼谱图进行基线校正和标准归一化等预处理,并选取食用油不饱和度特征的两处拉曼峰值作为特征向量,计算训练样本特征空间上各个植物油类别的中心坐标;然后,将食用植物油测试样本的拉曼谱图经过相同预处理和特征提取,获取测试样本的特征向量,计算其与各类别中心坐标的欧式距离,根据类中心最小距离法,取欧式距离最小的那一类作为预测样本的类别。针对7类43个食用植物油样本的实验结果表明,采用食用油不饱和度两点描述法进行特征提取,各类别样本聚集效果比PCA好,类间距更大。上述鉴别方法可以准确地实现食用植物油品种的快速分类。     

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.     

Effect of oxygen on the NMR relaxation properties of crude oils

Nuclear magnetic resonance relaxation measurements of bulk fluids provide a sensitive probe of the dynamics of molecular motion. Dissolved oxygen can interfere with this technique as its paramagnetic nature leads to a reduction of the paramagnetic relaxation times of the fluids. We studied this effect for the relaxation properties of crude oils that are in general characterized by a distribution of relaxation times. The samples were stock tank oils that have been exposed to air. We comparedT ₁ andT ₂ relaxation time distributions and their correlation functions of the initial (oxygenated) samples with those from the deoxygenated samples. Oxygen was removed from the oils with a freeze-thaw technique. As expected, the effect of oxygen is most apparent in oils with long relaxation times. In these oils the effect of oxygen can be described by an additional relaxation rate 1/T _1,2 ^ox to the transverse and longitudinal relaxation rates that is sample dependent but does not vary within the relaxation time distribution of the oil. Values of 1/T _1,2 ^ox for different crude oils were found to be in the range of 2.5 to 8.3 s. For crude oils that have components with relaxation times less than 100 ms, no significant oxygen effect is observed.     

Mobile Low-Field 1H NMR Spectroscopy Desktop Analysis of Biodiesel Production

Biodiesel produced mainly by the base-catalyzed transesterification of vegetable oils or animal fats with a short chain alcohol, has become an attractive alternative to petroleum-based diesel fuel. Even though high-field ¹H nuclear magnetic resonance (NMR) is a reliable method for biodiesel quality control, it is restricted by its poor mobility and expensive superconducting coils. As an alternative, this study presents a mobile low-field ¹H NMR spectrometer for the analysis of biodiesel samples derived from different feedstock oils. The low-field ¹H NMR spectra of all the compounds coexisting in a typical transesterification reaction such as rapeseed oil, rapeseed biodiesel, methanol, and glycerol, could be clearly differentiated. Field-dependent characteristic parameters such as relaxation times are provided. The degree of saturation of the different biofuels samples could be reliably estimated via integration of the resolved signals of the spectra. The obtained results agreed well with those measured at high-field ¹H NMR. Since this compositional information is directly related to the biodiesel properties, the presented mobile low-field ¹H NMR device built from permanent magnets arrayed in a Halbach geometry, constitutes an excellent alternative tool for biodiesel quality control.     

基于人工神经网络的傅里叶变换中红外光谱法对食用油油烟种类识别研究

随着餐饮业的发展,餐饮烟气已经成为某些城市三大空气污染源之一。由于餐饮烟气对人体健康威胁很大,近年来对餐饮烟气的研究愈来愈热。餐饮烟气中包含有大量食用油加热过程中裂解而产生的不饱和烃类,危害着人类健康。不同食用油裂解出来的成分以及含量有所不同,通过构建一定的分类识别数学模型,从而实现对食用油分类识别。采用自主研发的傅里叶变换红外光谱仪,采集了不同食用油油烟烟气红外光谱数据。同时构建了主成分分析(PCA)分别结合概率神经网络(PNN)以及误差反向传播人工神经网络(BPANN)的分类识别算法。将两种分类识别算法对不同食用油油烟烟气的傅里叶变换红外光谱数据进行分析。通过样本数据对数学模型进行训练,将训练好的数学模型对未知光谱数据进行分析,来确定产生油烟烟气的食用油种类。实验结果表明,两种算法都能对不同的油烟种类进行较好地分类识别。在全波段识别时,识别率分别达到90.25%和97.0%。通过对烟气光谱数据的吸收波段进行分析,提取大气窗口并且具有较强可挥发性有机物(VOCs)吸收特征的波段(1 300～700 cm-1以及3 000～2 600 cm-1);将吸光度数据分成两个分离的吸收波段,两种算法在3 000～2 600 cm-1波段都有较好的识别效果,PCA-PNN算法识别率为90.25%,PCA-BPANN算法识别率为92.25%。可见,两种人工神经网络算法都能有效对食用油烟种类进行识别。     

Simple mobile single-sided NMR apparatus with a relatively homogeneous B0 distribution

This work presents a simple design for a mobile single-sided nuclear magnetic resonance (NMR) apparatus with a relatively homogeneous static magnetic field (B₀) distribution. In the proposed design, the B₀ magnetic field of the apparatus is synthesized using only two permanent magnet blocks, i.e., a cube (main) magnet and a small shim magnet placed above the main magnet. The magnetic flux of the shim magnet partially cancels out that of the main magnet, subsequently creating a smooth B₀ profile above the shim magnet where low-resolution NMR experiments are performed. Compared with many previously published designs, this straightforward design simplifies the construction of the apparatus and simultaneously generates a B₀ field parallel to the apparatus surface, allowing the use of a simple loop-type radiofrequency (RF) coil. Additionally, an apparatus prototype is constructed according to the proposed design. Weighing only 1.8 kg, the constructed apparatus has a compact structure and can be held in the palm of a hand. The apparatus generates a B₀ strength of about 0.0746 T. Within a B₀ field deviation of 3 mT, the region with a relatively homogeneous B₀ distribution extends to about 11 mm above the shim magnet. The proposed apparatus can detect a clear Hahn echo or Carr-Purcell-Meiboom-Gill (CPMG) echoes of a pencil eraser block or a bottle of oil placed on the apparatus in 5 s with signal averaging using an RF transmitter power of only 19 W; the detection range of the apparatus exceeds 6 mm. The strength of the residual static magnetic field gradient of the apparatus is roughly estimated at 0.58 T/m. Applying different CPMG echo spacings in this residual static gradient leads to various transverse relaxation time (T₂) contrasts for liquids with distinct viscosities such as water and oil. Two nondestructive inspection applications of the apparatus, including correlating the concentrations of magnetic nanoparticle solutions with their measured transverse relaxation rates (R₂) and monitoring the outgassing from an opened bottle of oxygen-supersaturated water by measuring its longitudinal relaxation rate (R₁), are also demonstrated.     

In situ fluid typing and quantification with 1D and 2D NMR logging

In situ nuclear magnetic resonance (NMR) fluid typing has recently gained momentum due to data acquisition and inversion algorithm enhancement of NMR logging tools. T(2) distributions derived from NMR logging contain information on bulk fluids and pore size distributions. However, the accuracy of fluid typing is greatly overshadowed by the overlap between T(2) peaks arising from different fluids with similar apparent T(2) relaxation times. Nevertheless, the shapes of T(2) distributions from different fluid components are often different and can be predetermined. Inversion with predetermined T(2) distributions allows us to perform fluid component decomposition to yield individual fluid volume ratios. Another effective method for in situ fluid typing is two-dimensional (2D) NMR logging, which results in proton population distribution as a function of T(2) relaxation time and fluid diffusion coefficient (or T(1) relaxation time). Since diffusion coefficients (or T(1) relaxation time) for different fluid components can be very different, it is relatively easy to separate oil (especially heavy oil) from water signal in a 2D NMR map and to perform accurate fluid typing. Combining NMR logging with resistivity and/or neutron/density logs provides a third method for in situ fluid typing. We shall describe these techniques with field examples.     

Diffusion and spatially resolved NMR in Berea and Venezuelan oil reservoir rocks.

Conventional and spatially resolved proton NMR and relaxation measurements are used in order to study the molecular motions and the equilibrium and nonequilibrium diffusion of oils in Berea sandstone and Venezuelan reservoir rocks. In the water-saturated Berea a single line with T*2 congruent to 150 microseconds is observed, while the relaxation recovery is multiexponential. In an oil reservoir rock (Ful 13) a single narrow line is present while a distribution of relaxation rates is evidenced from the recovery plots. On the contrary, in the Ful 7 sample (extracted at a deeper depth in a different zone) two NMR components are present, with 3.5 and 30 KHz linewidths, and the recovery plot exhibits biexponential law. No echo signal could be reconstructed in the oil reservoir rocks. These findings can be related to the effects in the micropores, where motions at very low frequency can occur in a thin layer. From a comparison of the diffusion constant in water-saturated Berea, D congruent to 5*10(-6) cm2/sec, with the ones in model systems, the average size of the pores is estimated around 40 A. The density profiles at the equilibrium show uniform distribution of oils or of water, and the relaxation rates appear independent from the selected slice. The nonequilibrium diffusion was studied as a function of time in a Berea cylinder with z axis along H0, starting from a thin layer of oil at the base, and detecting the spin density profiles d(z,t) with slice-selection techniques. Simultaneously, the values of T1's were measured locally, and the distribution of the relaxation rates was observed to be present in any slice.(ABSTRACT TRUNCATED AT 250 WORDS)     

基于太赫兹时域光谱的食用油过氧化值定量分析研究

针对目前太赫兹光谱技术在食用油品质检测方面存在定性多、定量难的问题,提出一种基于衰减全反射（ATR）式太赫兹时域光谱（THz-TDS）技术的食用油过氧化值定量分析方法。首先采集不同种类、不同氧化程度食用油样本的太赫兹时域光谱图,筛选有效信号波段并提取得到光学常数,经预处理算法校正后的光学常数,结合多种化学计量学方法建立定量分析模型,实现快速、无损预测食用油的过氧化值。70个实验样本包括大豆油、菜籽油和玉米,过氧化值覆盖范围0.41~10.23 mmol·kg-1,且样本的过氧化值均匀分布。采用TeraView公司生产配有ATR检测模块的TeraPulse 4000太赫兹脉冲光谱系统采集样本THz-TDS信号,根据THz-TDS谱图信号特征筛选有效波段10~86.78 cm-1用于建模分析。通过快速傅里叶变换得到频域信号并从中提取光学常数：折射率和吸收系数,采用Savitzky-Golay7点卷积平滑分别对折射率和吸收系数进行预处理,去除干扰信号。运用SPXY算法按照3∶1比例划分校正集和预测集样本,结合主成分回归法、偏最小二乘法两种化学计量学分析方法,分别建立基于折射率和基于吸收系数的过氧化值分析模型。对模型评价指标均方根误差和相关系数进行分析,基于折射率的过氧化值分析模型采用偏最小二乘算法建模预测精度最理想,选取最优主成分数为6时,其校正集均方根误差RMSEC为0.168%、决定系数R2为0.981,预测集均方根误差RMSEP为0.231%、决定系数r2为0.977;基于吸收系数的过氧化值分析模型则采用主成分回归算法建模预测模型稳健度最好,选取最优主成分数为10时,其校正均方根误差RMSEC为0.192%、校正集决定系数R2为0.979,预测均方根误差RMSEP为0.262%、预测集决定系数r2为0.97。该研究结果的得出,验证了THz-TDS技术用于食用油过氧化值定量分析的可行性,为食用油的品质评价找到一种高精度、性能稳定、快速无损的检测方法。     

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。     

植物油的1H NMR和13C NMR的测定

油酸和亚油酸,是人体必需的营养成份,具有抗癌,防止动脉硬化,降脂减压等作用,因而它们在治疗一些癌症及减肥降血脂等方面取得了较好的疗效^[1-3]。通常油酸,亚油酸和其他脂肪酸以甘油酯的形式,大量地存在于植物油中。本文用¹H NMR测定了5种植物油各组峰面积积分,按文献[4]扣除法,整理了各组峰的积分值,计算出油脂中每摩尔所含各功能团的个数,不饱和度,酯化度等数据。此外,还记了豆油和茶油的¹³C NMR谱,从这两种谱图相关谱线积分值推算出各功能团与甲基基团的比率与¹H NMR谱所得结果接近。并计算出,上述两种油中所含脂肪酸甘油酯和各种不饱和脂肪酸甘油酯的克分子百分数。对测得CCH₂C基团质子自旋晶格弛豫时间T₁进行分析后,给出一经验公式来予以拟合,计算结果与测定值吻合。这一事实说明,油脂中各种组分克分子百分数的计算是可以信赖的。     

Analysis of Argan Oil Adulteration Using Infrared Spectroscopy

The determination of argan oil adulteration by other vegetable oils is a real analytical challenge. The authentication of argan oil needs fast and simple analytical techniques for quality control and testing. This study focuses on the detection and quantification of argan oil adulteration with different edible oils, using midinfrared spectroscopy with chemometrics. Chemometric treatment of MIR spectra has been assessed for the classification and quantification of argan oil adulteration with sunflower or soybean oils. The potential of MID spectroscopy combined with partial least squares regression (PLS) as a rapid analytical technique for the quantitative determination of adulterants in argan oil has been demonstrated. A PLS model has been established to predict the concentration of soybean and sunflower oil as adulterants in the calibration range between 0% and 30% (w/w) in argan oil with good prediction performances in the external validation.     

岩心孔隙介质中流体的核磁共振弛豫

弛豫时间是核磁共振研究中的一个重要参数,岩心孔隙介质流体的弛豫过程是自由流体弛豫机制、表面弛豫机制和流体的扩散弛豫机制共同作用的结果,它包含了丰富的孔隙和流体本身的信息. 弛豫时间和自扩散系数的测量及对弛豫时间的分析是核磁共振技术应用于岩心分析和石油勘测的重要内容.