Synthesis of a mixed carboxylate–phosphinate AAZTA-like ligand and relaxometric characterization of its Gd complex

The synthesis of the new polydentate ligand AAZ2A2P^Et derived from the heptadentate polyaminocarboxylic ligand AAZTA (6-amino-6-methylperhydro-1,4-diazepine-N,N′,N″,N″-tetraacetic acid) in which two acetate groups were replaced by methyleneethylphosphinic pendant arms is reported. The relaxometric behavior of the corresponding mono-aquo Gd^III complex was also investigated.     

Chemometrics in fuel science: demonstration of the feasibility of chemometrics analyses applied to physicochemical parameters to screen solvent tracers in Brazilian commercial gasoline

Samples of commercial gasoline, from the National Program of Fuel Quality Monitoring of the National Petroleum Agency, were collected from gas stations located in the Midwestern state of Sao Paulo, Brazil, and analyzed by several physicochemical standard methods established by ANP Resolution no. 309. Also, important information related to tampering was analyzed with the marker solvent. Statistical analysis and exploratory chemometric were employed to discriminate the presence of markers of solvents in commercial gasoline. The results showed that statistical and chemometric parameters such as atmospheric distillation temperatures T10 and T90, RON, benzene and saturated and aromatic hydrocarbons satisfactorily describe the presence of marker solvent, usually with a probability exceeding 70%. Furthermore, after optimizing the SIMCA algorithm, sensitivity in the training set with cross‐validation leave‐one‐out (83.8%) and the set of prediction (77.1%) were revealed. The proposed method will become indispensable and recommended for discriminating samples of fuels for commercial applications in routine monitoring programs and quality control. Copyright © 2011 John Wiley & Sons, Ltd.     

GC Fingerprints Coupled to Pattern-Recognition Multivariate SIMCA Chemometric Analysis for Brazilian Gasoline Quality Studies

ASTM D6729 gas chromatographic fingerprinting coupled to pattern-recognition multivariate soft independent modeling of class analogy (SIMCA) chemometric analysis provides an original and alternative approach to screening Brazilian commercial gasoline quality. SIMCA, was performed on gas chromatographic fingerprints to classify the quality of representative commercial gasoline samples selected by hierarchical cluster analysis and collected over a 5 month period from gas stations in São Paulo State, Brazil. Following an optimized ASTM D6729 gas chromatographic-SIMCA algorithm, it was possible to correctly classify the majority of commercial gasoline samples. The method could be employed for rapid monitoring to discourage adulteration.     

Screening Brazilian commercial gasoline quality by hydrogen nuclear magnetic resonance spectroscopic fingerprintings and pattern-recognition multivariate chemometric analysis

The identification of gasoline adulteration by organic solvents is not an easy task, because compounds that constitute the solvents are already in gasoline composition. In this work, the combination of Hydrogen Nuclear Magnetic Resonance (¹H NMR) spectroscopic fingerprintings with pattern-recognition multivariate Soft Independent Modeling of Class Analogy (SIMCA) chemometric analysis provides an original and alternative approach to screening Brazilian commercial gasoline quality in a Monitoring Program for Quality Control of Automotive Fuels. SIMCA was performed on spectroscopic fingerprints to classify the quality of representative commercial gasoline samples selected by Hierarchical Cluster Analysis (HCA) and collected over a 6-month period from different gas stations in the São Paulo state, Brazil. Following optimized the ¹H NMR-SIMCA algorithm, it was possible to correctly classify 92.0% of commercial gasoline samples, which is considered acceptable. The chemometric method is recommended for routine applications in Quality-Control Monitoring Programs, since its measurements are fast and can be easily automated. Also, police laboratories could employ this method for rapid screening analysis to discourage adulteration practices.     

The behaviour of some selenoglycollic acid derivatives in aqueous solutions and spectrophotometric determination of constants of the system Pd(II)/ethylene-bis- selenoglycollic acid

Interactions between ethylselenoglycollic, selenoglycollic and ethylene-bis- selenoglycollic acids and some “soft”, “borderline” and “hard” metallic ions have been studied. The interactions of [PdCl₄]_aq²⁻ with the three ligands were verified conductometrically and spectrophotometrically. The stability constants β₁ and β₂ for the system [PdCl₄]^2-- ethylene-bis-selenoglycollic acid have been determined at 25°C at ionic strength 3.0 M (NaCl). The stoichiometric ionization constant of the mentioned acid was also studied.     

Screening Brazilian C gasoline quality: application of the SIMCA chemometric method to gas chromatographic data

A total of 2400 samples of commercial Brazilian C gasoline were collected over a 6-month period from different gas stations in the S?o Paulo state, Brazil, and analysed with respect to 12 physicochemical parameters according to regulation 309 of the Brazilian Government Petroleum, Natural Gas and Biofuels Agency (ANP). The percentages (v/v) of hydrocarbons (olefins, aromatics and saturated) were also determined. Hierarchical cluster analysis (HCA) was employed to select 150 representative samples that exhibited least similarity on the basis of their physicochemical parameters and hydrocarbon compositions. The chromatographic profiles of the selected samples were measured by gas chromatography with flame ionisation detection and analysed using soft independent modelling of class analogy (SIMCA) method in order to create a classification scheme to identify conform gasolines according to ANP 309 regulation. Following the optimisation of the SIMCA algorithm, it was possible to classify correctly 96% of the commercial gasoline samples present in the training set of 100. In order to check the quality of the model, an external group of 50 gasoline samples (the prediction set) were analysed and the developed SIMCA model classified 94% of these correctly. The developed chemometric method is recommended for screening commercial gasoline quality and detection of potential adulteration.     

Screening Brazilian Commercial Gasoline Quality by ASTM D6733 GC and Pattern-Recognition Multivariate SIMCA Chemometric Analysis

The combination of ASTM D6733 gas chromatographic fingerprinting data with pattern-recognition multivariate soft independent modeling of class analogy (SIMCA) chemometric analysis provides an original and alternative approach to screening Brazilian commercial gasoline quality in a monitoring program for quality control of automotive fuels. SIMCA was performed on chromatographic fingerprints to classify the quality of the gasoline samples. Using SIMCA, it was possible to correctly classify 94.0% of commercial gasoline samples, which is considered acceptable. The method is recommended for quality-control monitoring. Quality control and police laboratories could employ this method for rapid monitoring.     

Carbon nuclear magnetic resonance spectroscopic fingerprinting of commercial gasoline: Pattern-recognition analyses for screening quality control purposes

In this work, the combination of carbon nuclear magnetic resonance (¹³C NMR) fingerprinting with pattern-recognition analyses provides an original and alternative approach to screening commercial gasoline quality. Soft Independent Modelling of Class Analogy (SIMCA) was performed on spectroscopic fingerprints to classify representative commercial gasoline samples, which were selected by Hierarchical Cluster Analyses (HCA) over several months in retails services of gas stations, into previously quality-defined classes. Following optimized ¹³C NMR-SIMCA algorithm, sensitivity values were obtained in the training set (99.0%), with leave-one-out cross-validation, and external prediction set (92.0%). Governmental laboratories could employ this method as a rapid screening analysis to discourage adulteration practices.     

Development, optimization and validation of gas chromatographic fingerprinting of Brazilian commercial gasoline for quality control

Three-step development, optimization and validation strategy for GC fingerprints of Brazilian commercial gasoline is described. A suitable chromatographic system was selected first. The following step was to improve acceptable chromatographic resolution with reduced analysis time, which is recommended for routine applications. Optimization was carried out using full three-level factorial designs. Optimal conditions were obtained for flow rate, oven ramps, injection volume and split ratio. Finally, several validation parameters were performed. Therefore, a feasible and reliable fingerprint was established to identify Brazilian commercial gasoline quality. This strategy can also be applied to develop fingerprints for quality control of other fuels.     

Screening Brazilian Automotive Gasoline Quality through Quantification of Saturated Hydrocarbons and Anhydrous Ethanol by Gas Chromatography and Exploratory Data Analysis

In this paper a set of Brazilian commercial gasoline representative samples from São Paulo State, selected by HCA, plus six samples obtained directly from refineries were analysed by a high-sensitive gas chromatographic (GC) method ASTM D6733. The levels of saturated hydrocarbons and anhydrous ethanol obtained by GC were correlated with the quality obtained from Brazilian Government Petroleum, Natural Gas and Biofuels Agency (ANP) specifications through exploratory analysis (HCA and PCA). This correlation showed that the GC method, together with HCA and PCA, could be employed as a screening technique to determine compliance with the prescribed legal standards of Brazilian gasoline.