Effects of spatially inhomogeneous atomic interactions on Bose–Einstein condensates in optical lattices

An interplay of optical lattices and nonlinear impurities in controlling the dynamics of Bose–Einstein condensate bright solitons is investigated using an effective potential approach. The ability of pushing the solitons into or away from the impurity region by changing both lattice and impurity parameters is suggested. A possibility for the existence of stable fundamental gap solitons, which appear to satisfy an inverted Vakhitov–Kolokolov criterion, is examined.     

Sample preparation methods for subsequent determination of metals and non-metals in crude oil—A review

In this review sample preparation strategies used for crude oil digestion in last ten years are discussed focusing on further metals and non-metals determination. One of the main challenges of proposed methods has been to overcome the difficulty to bring crude oil samples into solution, which should be compatible with analytical techniques used for element determination. On this aspect, this review summarizes the sample preparation methods for metals and non metals determination in crude oil including those based on wet digestion, combustion, emulsification, extraction, sample dilution with organic solvents, among others. Conventional methods related to wet digestion with concentrated acids or combustion are also covered, with special emphasis to closed systems. Trends in sample digestion, such as microwave-assisted digestion using diluted acids combined with high-efficiency decomposition systems are discussed. On the other hand, strategies based on sample dilution in organic solvents and procedures recommended for speciation analysis are reported as well as the use of direct analysis in view of the recent importance for crude oil field. A compilation concerning sample preparation for crude oil provided by official methods as well as certified reference materials available for accuracy evaluation is also presented and discussed.     

石油磺酸盐体系中相微乳液研究

宽分子量分布的石油磺酸盐在低浓度时有正丁醇、正构烷烃、盐存在的情况下能成中相微乳液。研究了盐浓度、烷烃种类、醇浓度对该体系中相微乳液的形成及特性影响,得到中相微乳液的特性参数;最佳含盐量Ｓ＾＊、增溶参数σ、盐宽△Ｓ、界面张力γ等,并从理论上进行了探讨。采用模拟驱油装置测定了体系的驱油效率,对优化驱油体系设计具有重要意义。     

Solid phase extraction of petroleum carboxylic acids using a functionalized alumina as stationary phase

Petroleum essentially consists of a mixture of organic compounds, mainly containing carbon and hydrogen, and, in minor quantities, compounds with nitrogen, sulphur, and oxygen. Some of these compounds, such as naphthenic acids, can cause corrosion in pipes and equipment used in processing plants. Considering that the methods of separation or clean up the target compounds in low concentrations and in complex matrix use large amounts of solvents or stationary phases, is necessary to study new methodologies that consume smaller amounts of solvent and stationary phases to identify the acid components present in complex matrix, such as crude oil samples. The proposed study aimed to recover acid compounds using the solid phase extraction method, employing different types of commercial stationary ion exchange phases (SAX and NH(2)) and new phase alumina functionalized with 1,4-bis(n-propyl)diazoniabicyclo[2.2.2]octane chloride silsesquioxane (Dab-Al(2)O(3)), synthesized in this work. Carboxylic acids were used as standard mixture in the solid phase extraction for further calculation of recovery yield. Then, the real sample (petroleum) was fractionated into saturates, aromatics, resins, and asphaltenes, and the resin fraction of petroleum (B1) was eluted through stationary ion exchange phases. The stationary phase synthesized in this work showed an efficiency of ion exchange comparable to that of the commercial stationary phases.     

微型反应器液相产物中C1～C5烃分析系统及方法研究

本介绍了一个适于终沸点为４００℃或更主的微型反应器液相产物中Ｃ１－Ｃ５烃全组成分析的专用分析系统和分析方法。系统由六通阀、预柱和分析柱组成，所有组件均置于同一色谱炉内，采用ＦＩＤ检测外标法定量。分析结果相对标准偏差小于１０％。半年来的应用结果表明，该系统及方法具有操作简便，定量结果准确，适用范围宽，连续运行周期长等特点，可以用于各类宽镏分样品中Ｃ１－Ｃ５烃的全组成分析。     

Rapid in situ determination of total oil concentration in water using ultraviolet fluorescence and light scattering coupled with artificial neural networks

Real-time measurement of total oil concentration in complex samples is required in wastewater discharge streams from ships and processing industries. A novel technology has been developed for the accurate quantification of a variety of single oils and their mixtures. Four major types of oils (lube oils 2190 and 9250, diesel fuel marine (DFM), and jet fuel (JP5)), each of which consisted of a dozen subtypes of oil samples, were examined to obtain both fluorescence and light scattering spectra as a function of concentration of single oils and mixtures. Tremendous variations in both fluorescence and scattering were observed among oil types, subtypes, and mixtures. The spectral response of an oil mixture was not the simple summation of respective single oils. To account for all these variations, a multivariate, nonlinear calibration method is applied to associate instrumental responses with oil concentrations using artificial neural networks (ANNs). The neural network architecture has been established by optimizing network parameters such as epochs, the number of neurons in the hidden layer, and learning rates in order to achieve the maximum accuracy of oil concentration measurements. It is demonstrated that the simultaneous, combined use of fluorescence and light scattering significantly improves the accuracy of measurement for oil samples. The newly developed technique permits the reliable, real-time determination of the total concentration of various oils and mixtures in water.     

Biodiesel classification by base stock type (vegetable oil) using near infrared spectroscopy data

The use of biofuels, such as bioethanol or biodiesel, has rapidly increased in the last few years. Near infrared (near-IR, NIR, or NIRS) spectroscopy (>4000 cm⁻¹) has previously been reported as a cheap and fast alternative for biodiesel quality control when compared with infrared, Raman, or nuclear magnetic resonance (NMR) methods; in addition, NIR can easily be done in real time (on-line). In this proof-of-principle paper, we attempt to find a correlation between the near infrared spectrum of a biodiesel sample and its base stock. This correlation is used to classify fuel samples into 10 groups according to their origin (vegetable oil): sunflower, coconut, palm, soy/soya, cottonseed, castor, Jatropha, etc. Principal component analysis (PCA) is used for outlier detection and dimensionality reduction of the NIR spectral data. Four different multivariate data analysis techniques are used to solve the classification problem, including regularized discriminant analysis (RDA), partial least squares method/projection on latent structures (PLS-DA), K-nearest neighbors (KNN) technique, and support vector machines (SVMs). Classifying biodiesel by feedstock (base stock) type can be successfully solved with modern machine learning techniques and NIR spectroscopy data. KNN and SVM methods were found to be highly effective for biodiesel classification by feedstock oil type. A classification error (E) of less than 5% can be reached using an SVM-based approach. If computational time is an important consideration, the KNN technique (E = 6.2%) can be recommended for practical (industrial) implementation. Comparison with gasoline and motor oil data shows the relative simplicity of this methodology for biodiesel classification.     

Global approach for the selection of high temperature comprehensive two-dimensional gas chromatography experimental conditions and quantitative analysis in regards to sulfur-containing compounds in heavy petroleum cuts

Extending the knowledge on sulfur-containing compounds is crucial for the petroleum industry because they contribute to atmospheric pollution by combustion. Most of them are concentrated in heavy petroleum cuts, such as vacuum gas oils (VGOs). However, the resolution of the existing analytical methods does not allow a quantitative speciation of S-compounds contained in VGOs. Therefore, a high temperature GC×GC chromatograph hyphenated to a SCD was implemented in this study to obtain a quantitative S-compounds speciation. Firstly, various thermally stable stationary phases, in particular the new ionic liquid IL59 and Mega Wax-HT, were investigated in 1D-GC as a way to reduce the number of columns sets to be used in GC×GC. Consequently, several normal and reversed configurations of these columns were selected and tested in GC×GC. Then, a decision method was applied to facilitate the choice of the best combination of columns. Finally, the most adapted methods led to an innovative group type quantification and to a quantitative distribution of heavy sulfur species contained in a VGO sample. These results represent a major step towards the study of S-compounds in heavy petroleum cuts.     

What is the Criterion for Selecting Alkaline/Surfactaint/Polymer Flooding Formulation: Phase Behavior or Interfacial Tension

An experimental study on determination of alkaline, surfactant, polymer (ASP) flooding systems using natural mixed carboxylate was conducted to examine the decisive factor for ASP flooding, phase behavior or interfacial tension. The volume and color of middle phase liquid were observed, the transient interfacial tension at different salt and alkaline concentrations were measured and, finally, coreflood test in laboratory were made. The results showed the flooding system with larger volume and brown color of middle phase emulsion sometimes not to obtain better oil recovery efficiency. The primary and more important phenomenon affecting the oil recovery is a lower or ultralow minimum interfacial tension value at the crude oil/soluble phase interface.     

Behaviour of chemical modifiers in the determination of arsenic by electrothermal atomic absorption spectrometry in petroleum products

Most comparative studies on the efficiency of chemical modifiers have been conducted in aqueous media. In the present work, we proposed a detailed study of the use of different chemical modifiers for direct determination of arsenic in complex organic matrices by electrothermal atomic absorption spectrometry (ETAAS). Palladium, rhodium, tungsten, silver, lanthanum and a mixture of palladium and magnesium were tested. The figures of merit used for evaluation and comparison were acquired in the optimal conditions for each modifier, established by multivariate optimization of the main variables based on Doehlert designs. Singular features were observed for the chemical behaviour of some modifiers in organic matrices compared to aqueous media, such as the worse performance of Pd + Mg modifier and no notice of severe tube corrosion from La application. Lanthanum was chosen as the best chemical modifier for the present application, according to predefined criteria. Lanthanum showed the minimum limit of detection, characteristic concentration and blank signal among all tested species and no effect of the concomitants usually present in petrochemical feedstocks. Using a 200 mg L⁻¹ lanthanum solution as a chemical modifier, the average relative standard deviations of 7 and 16% (at 3-15 μg L⁻¹ level) and characteristic concentrations of 0.47 and 0.77 μg L⁻¹ for naphtha and petroleum condensates, respectively, were observed.