Paulo R. B. Guimarães

Simultaneous determination of copper and iron in automotive gasoline by X-ray fluorescence after pre-concentration on cellulose paper.

This paper proposes an alternative analytical method using energy dispersive X-ray fluorescence (EDXRF) to determine Fe and Cu in gasoline samples. In the proposed procedure, samples were distilled and the distillation residues were spotted on cellulose paper disk to form a uniform thin film and to produce a homogeneous and reproducible interface to the XRF instrument. The disks were dried at 60 degrees C for 20min and copper and iron were determined directly in the solid phase at 6.40 and 8.04keV, respectively. The calibration curves showed linear response in the 20-800mugL(-1) concentration range of each metal. The precisions (repeatability) calculated from 15 consecutive measurements and defined as the coefficient of variation of solutions containing 100mugL(-1) of Fe and Cu were 7.8 and 8.1%, respectively. The limits of detection (LOD), defined as the analyte concentration that gives a response equivalent to three times the standard deviation of the blank (n=10), were found to be 10 and 15mugL(-1) for Fe and Cu, respectively. The proposed method was applied to copper and iron determination in gasoline samples collected from different gas stations.

Indirect determination of chloride and sulfate ions in ethanol fuel by X-ray fluorescence after a precipitation procedure

This paper proposes an alternative analytical method using energy dispersive X-ray fluorescence (EDXRF) to determine chloride and sulfate ions in ethanol fuel samples after precipitation procedure. The preconcentration methodology involved the precipitation of the analytes as silver chloride and barium sulfate followed by filtration through a paper filter, which demonstrated to be a convenient substrate for EDXRF measurements. The elements were determined directly on the filters using silver and barium lines for the indirect determination of chloride and sulfate ions, respectively. The precisions calculated from 20 consecutive measurements and defined as the coefficient of variation of standard solutions containing 1.0 microg mL(-1) of Cl(-) and SO(4)(2-) were 7.3% and 5.9%, respectively. The limits of detection (LOD), defined as the analyte concentration that gives a response equivalent to three times the standard deviation of the blank (n=10), were found to be 25 microg L(-1) and 30 microg L(-1) for Cl(-) and SO(4)(2-), respectively. The proposed method was applied to chloride and sulfate ions determination in hydrated ethanol fuel samples collected from different gas stations.

Correlation of PVR, Octane Numbers and Distillation Curve of Gasoline with Data from a Thermal Wave Interferometer

Abstract The ASTM standard methods for experimental determination of gasoline properties, such as octane numbers and Reid vapour pressure (PVR) are, in general, expensive, time consuming and cumbersome. Therefore, the study and development of faster and cheaper methods is of great industrial and scientific interest, particularly when one thinks of large numbers of gasoline samples to be tested. However, gasoline is a mixture of hydrocarbons and presents very complex chemical properties that require the use of several analytical techniques, and so the development of any new method will need to be validated through a series of statistical techniques. This contribution is aimed at the validation of a Thermal Wave Interferometer (IOT), conceived and developed by Vargas et al. at the Norte Fluminense State University — UENF, for the determination of octane numbers (MON and RON), distillation curve and PVR of gasoline and gasohol. The IOT determines these properties through a mathematical correlation of the thermal diffusivity of the components present in the gasoline, or gasohol, sample. This IOT validation study involved the use of a multivariate regression technique, namely SIMCA (Soft Independent Modelling of Class Analogy) for the classification of sample data and identification of outliers and the development of new correlation models for the prediction of gasoline octane numbers. In this study 97 samples of various types of commercial gasoline and gasohol, the latter containing up to 30% v/v of ethanol, were prepared and had their corresponding octane numbers (MON and RON) determined through the CFR motor method and their thermal diffusivities determined through the IOT. These experimental data were then correlated and a PLS (partial least squares) model, based on 89 thermal diffusivity variables, was developed for the prediction of the AKI, a parameter which is the mean value of the octane numbers (MON and RON) of a sample, i.e. AKI = (MON+RON)/2. Better results were obtained when the model was built for distillation curve points (Initial boiling point, 10% evaporated) and PVR data, and the thermal diffusivity data (30-870s) were centred at the mean value and smoothed, giving an RMSEC =1.832 and an RMSEV=2.270. These results indicate that the IOT is a promising, fast and cheap method for the prediction of AKI, provided the user takes into account the inherent errors of the experimental method. Thus, the IOT may be very useful as a tool for undertaking screening analysis, i.e., selection of gasoline, or gasohol, samples that must be submitted to the more expensive and time consuming CFR motor method.

Selection of optimal operating conditions based on minimum energy consumption for an acrylonitrile recovery unit

ABSTRACT The selection of the optimal operating conditions for an industrial acrylonitrile recovery unit was conducted by the systematic application of the response surface methodology, based on the minimum energy consumption and products specifications as process constraints. Unit models and plant simulation were validated against operating data and information. A sensitivity analysis was carried out in order to identify the set of parameters that strongly affect the trajectories of the system while keeping products specifications. The results suggest that energy savings of up to 10% are possible by systematically adjusting operating conditions.