Interlaboratory comparisons and improvements of methods for acid number determination in used motor oils

The results of two interlaboratory comparisons of acid number determinations in used motor oils are discussed. It is shown that the comparability of the measurement results is not as good as that required by known standards for petroleum products. The problem is motor oil contaminants which accumulated during use, and which are the source of a matrix effect in the acid number determination. The standard methods’ drawbacks are analyzed and some improvements are proposed. Repeatability and accuracy of the improved methods are evaluated. Received: 11 December 2001 Accepted: 15 February 2002     

Refractive index of standard oils as a function of wavelength and temperature

The refractive indices (n) of eight standard oils from Physikalisch Technische Bundesanstalt, Germany were determined with an accuracy of ±1×10⁻⁴ by using Abbe Refractometer. The measurements were performed at temperature 20°C in the spectral range 0.4–0.7 μm. The experimental data were fitted to the simple Cauchy dispersion formula and the results were found to be consistent within the limits of experimental error. In all cases, the refractive index decreased monotonically with increasing wavelength. The refractive indices (n) of these oils have been measured as a function of the temperature t (20°C up to 50°C) at λ=0.589 μm and were found to have linear temperature dependencies. The refractive indices of the studied oils and the uncertainty in their values are calculated at λ=0.589. The Lorentz–Lorenz (L–L) formula has been tested and it was found to be valid with a maximum deviation of 0.4% and was used to calculate the molecular polarizability θ.     

A RAPID APPROXIMATION FOR PREDICTING THE HYDROCARBON DISCOVERY RATE: PART 1. ASSESSING THE ACCURACY

The hydrocarbon discovery prediction problem is important to firms having to make decisions about the deployment of scarce exploration resources. Traditional methods for estimating the discovery rate rely on the completion of time consuming simulation experiments. A rapid approximation that does not require the completion of simulation exists and has been shown to have some promise as a prediction tool. This paper investigates the accuracy of the approximation method under a wide variety of distributional and drilling efficiency assumptions. The results indicate that the approximation produces predictions close to those of simulation under most of the tested conditions. This suggests that resource exploration firms could conveniently use the method for a wide variety of planning purposes without incurring the same costs in time and personnel required for simulation.     

Polygermoxanes suitable for biochemical purposes. Part I. Digermoxanes (low-viscosity oils)

In order to replace silicones in some of their biomedical applications, e.g. syringe lubrication, implants ets., a series of digermoxanes (R¹R²R³Ge)₂O (R = n–alkyl, aryl) were synthesized. These compounds are thermally stable oils; their viscosities, depending on the nature of substituents, lie in the range 1–72 cPo (mPa s) at 20°C.     

Determination of the boiling point distribution of sulfur compounds in light cycle oil using GC with a flame photometric detector and pyrolyzer

A method has been developed to determine the boiling point distribution of sulfur compounds in light cycle oils (LCO'S). The method chosen for this analysis was GC with a flame photometric detector (FPD) and pyrolyzer. Tests were carried out to evaluate the recovery efficiency, repeatability, and accuracy of the method. Repeatabilities within 2% were obtained. The recovery of benzothiophenes and dibenzothiophenes was close to 100%; this was important because these are the major sulfur components in LCO's. No hydrocarbon or solvent interferences were observed with the use of the pyrolyzer, even for a 95% solvent level. Comparison with results from other techniques showed that the method accurately determined the levels of sulfur compounds in the LCO boiling point range.     

Ultrasonic analysis of edible fats and oils

Low intensity ultrasound is a powerful analytical technique for investigating the physico-chemical properties of many biological and non-biological materials. In this article its application for the characterization of edible fats and oils is assessed. Ultrasound can be used to determine the dynamic rheology and composition of oils, the oil content and droplet size of emulsions and the solid fat content of partially crystalline emulsions. It is capable of rapid and precise measurements, is non-destructive and non-invasive, can be used on-line or off-line and is relatively inexpensive. Ultrasonic techniques will therefore prove a useful addition to the existing analytical techniques used to characterize fats and oils.     

Evaluation of gas chromatography-tandem quadrupole mass spectrometry for the determination of organochlorine pesticides in fats and oils

A gas chromatography-tandem quadrupole mass spectrometry multi-residue method for the analysis of 19 organochlorine pesticides in fats and oils has been developed. Gel permeation chromatography was employed to remove lipid material prior to GC-MS/MS analysis. Average recoveries of the pesticides spiked at 10 and 50 microg kg(-1) into fish oil, pork fat, olive oil and hydrogenated vegetable oil were typically in the range 70-110% with relative standard deviations generally less than 10%. Calculated limits of detection are between 0.1 and 2.0 microg kg(-1) and results obtained for the analysis of proficiency test materials are in good agreement with assigned values. The higher selectivity of the GC-MS/MS compared to electron capture detection and GC-MS in selective ion monitoring mode allowed unambiguous identification and confirmation of all the target pesticides at low microg kg(-1) levels in fats and oils in a single analysis.     

Characterization of some essential oils and their key components: Thermoanalytical techniques

The present study was aimed at determining the kinetics of evaporation and establishing vapor pressure curves for both single and multi-component systems by thermogravimetry (TG) and differential scanning calorimetry (DSC). Essential oils (e.g. lavender oil, orange oil, clove oil and eucalyptus oil, etc.) are typically multi-component systems consisting of various volatile pure components (e.g. linalyl acetate, limonene, cinnamaldehyde, etc.) which resemble single component systems. In this study linalyl acetate was taken as the calibration compound for TG. The vapor pressure curves for the pure substances were plotted using TG and vapor pressure plots for clove oil and eucalyptus oil were constructed using DSC. The thermodynamic and kinetic parameters of the pure compounds were compared to that of the multi-component systems to quantitatively and qualitatively measure the influence of different compounds on each other. The k-value from the vapor pressure data for linalyl acetate was calculated as 112006 Pa kg^0.5mol^0.5s^-1 m^-2 K^-0.5. The vapor pressure values were used to determine the Antoine constants using the SPSS 10.0 software.This revised version was published online in November 2005 with corrections to the Cover Date.     

Establishing structure-property correlations and classification of base oils using statistical techniques and artificial neural networks

The present paper describes various classification techniques like cluster analysis, principal component (PC)/factor analysis to classify different types of base stocks. The API classification of base oils (Group I-III) has been compared to a more detailed NMR derived chemical compositional and molecular structural parameters based classification in order to point out the similarities of the base oils in the same group and the differences between the oils placed in different groups. The detailed compositional parameters have been generated using and nuclear magnetic resonance (NMR) spectroscopic methods. Further, oxidation stability, measured in terms of rotating bomb oxidation test (RBOT) life, of non-conventional base stocks and their blends with conventional base stocks, has been quantitatively correlated with their NMR and elemental (sulphur and nitrogen) data with the help of multiple linear regression (MLR) and artificial neural networks (ANN) techniques. The MLR based model developed using NMR and elemental data showed a high correlation between the ‘measured’ and ‘estimated’ RBOT values for both training (R=0.859) and validation (R=0.880) data sets. The ANN based model, developed using fewer number of input variables (only NMR data) also showed high correlation between the ‘measured’ and ‘estimated’ RBOT values for training (R=0.881), validation (R=0.860) and test (R=0.955) data sets.     

Headspace Solid-phase Microextraction–Gas Chromatographic–Mass Spectrometric Analysis of the Essential Oils of Two Traditional Chinese Medicines, Angelica pubescens and Angelica sinensis

Angelica pubescens and Angelica sinensis belong to the Umbelliferae family and both are used as traditional Chinese medicines. In the present study, headspace solid-phase microextraction (HS-SPME) with gas chromatography-mass spectrometry (GC-MS) was used for the analysis of the volatile constituents present in their roots. Eighty-seven compounds in Angelica pubescens and thirty-six compounds in Angelica sinensis were identified by GC-MS. Their relative contents were calculated by the peak area ratio. HS-SPME was compared to steam distillation (SD) by analyzing the volatile constituents of Angelica sinensis root. A good agreement between results obtained with both techniques was found. As a conclusion, HS-SPME is a powerful tool for determining the volatile constituents present in the TCMs.