Determination of volatile compounds in Brazilian distilled cachaça by using comprehensive two-dimensional gas chromatography and effects of production pathways

Comprehensive two-dimensional gas chromatography (GC × GC) was applied to the study of cachaça production. Effects of bidistillation, and the use of charcoal filtration in the production of artisan cachaça, as well as the effects of multi-distillation on volatile products in commercial cachaça were investigated. Volatile compounds were collected and concentrated onto a polyacrylate solid-phase microextraction fibre, and analyzed using GC × GC on a non-polar (BPX5)–polar (BP20) column set. More than 100 compounds, comprising various homologous series were tentatively identified using MS library matching and comparison with retention indices. Phthalate organic contamination following the use of ion exchange resin for removal of copper ion was evident. Charcoal successfully removes this contamination product. Prediction of compounds within particular homologous series aids component identification.     

Molecular Distance‐Edge Vector (μ) and Chromatographic Retention Index of Alkanes

A new method of quantitative structure‐retention relationship (QSRR) is proposed for estimating and predicting gas chromatographic retention indices of alkanes by using a novel molecular distance‐edge vector, called μ vector, containing 10 elements. The QSRR model (Ml), between the μ vector and chromatographic retention indices of 64 alkanes, was developed by using multiple linear regression (MLR) with the correlation coefficient being R = 0.9992 and the root mean square (RMS) error between the estimated and measured retention indices being RMS = 5.938. In order to explain the equation stability and prediction abilities of the M1 model, it is essential to perform a cross‐validation (CV) procedure. Satisfactory CV results have been obtained by using one external predicted sample every time with the average correlation coefficient being R = 0.9988 and average RMS = 7.128. If 21 compounds, about one third drawn from all 64 alkanes, construct an external prediction set and the 43 remaining construct an internal calibration set, the second QSRR model (M2) can be created by using calibration set data with statistics being R = 0.9993 and RMS = 5.796. The chromatographic retention indices of 21 compounds in the external testing set can be predicted by the M2 model and good prediction results are obtained with R = 0.9988 and RMS = 6.508.     

Cyclam complexes of Cu(II) and Co(II) as stationary phases for gas chromatography

New macrocyclic stationary chemically bonded phases were synthesized and tested in gas chromatography conditions. The complexes of 1,4,8,11-tetraazacyclotetradecane with Cu(II) and Co(II) were bonded to the silica support through the (3-chloropropyl)triethoxysilane reactant. The packings obtained were analyzed by diffuse-reflectance ultraviolet–visible spectroscopy (DRUV–Vis), differential thermal gravimetry (DTG), porosimetry, and elementary analysis. Preliminary study of the novel silica gas chromatography (GC) stationary phases containing cyclam complexes was carried out using packed 1/8 in. i.d. columns. The study was conducted on: cyclic, linear and branched olefins, aromatic hydrocarbons and ethers. Characterization of interactions between the compounds mentioned and new stationary phases was based upon analysis of Kováts retention indices (I), difference between retention indices for two phases (ΔI), and molecular retention indices (ΔM_e). Results have shown that the new stationary phases interact sufficiently strongly with molecules of high electron density and can be applied in capillary gas chromatography for the analysis of light hydrocarbons.     

Nonsaponifiable lipid components of the pollen of elder (Sambucus nigra L.).

Pollen of the elder (Sambucus nigra L.) was extracted with chloroform-methanol. The extract was separated by column chromatography into the following groups of compounds: hydrocarbons (8.7%). polycyclic aromatic hydrocarbons (0.2%), complex esters (5.2%), triglycerides (18.7%), hydroxy esters (27.9%), free fatty acids and alcohols (16.8%), free sterols (6.8%), and triterpenic alcohols (4.0%). The nonsaponifiable components (hydrocarbons, fatty acids, alcohols, and sterols) were examined in detail using spectroscopic and chromatographic methods (IR spectroscopy, GC, and GC-MS). The identified compounds were characterized by their mass spectra and Kováts retention indices. The double bond positions and their configurations in unsaturated compounds are also reported.     

The study of the relationship between the new topological index A(m) and the gas chromatographic retention indices of hydrocarbons by artificial neural networks

The newly developed topological indices A_m1-A_m3 and the molecular connectivity indices ^mX were applied to multivariate analysis in structure-property correlation studies. The topological indices calculated from the chemical structures of some hydrocarbons were used to represent the molecular structures. The prediction of the retention indices of the hydrocarbons on three different kinds of stationary phase in gas chromatography can be achieved applying artificial neural networks and multiple linear regression models. The results from the artificial neural networks approach were compared with those of multiple linear regression models. It is shown that the predictive ability of artificial neural networks is superior to that of multiple linear regression method under the experimental conditions in this paper. Both the topological indices ²X and A_m1 can improve the predicted results of the retention indices of the hydrocarbons on the stationary phase studied.     

Retention Characteristics of Peptides in RP-LC: Peptide Retention Prediction

A review of recent results of the use of chromatographic retention data in peptide identification and in the development of procedures for peptide retention prediction is presented. In recent years, reversed phase LC (RP-LC) has become an important tool in the separation of peptides in MS analysis. A challenging problem in a further expansion of RP-LC applications is the use of already available retention information for the identification purposes simultaneously with MS–MS identification. This overview focuses on the retention characteristics suggested in LC. We will discuss the application of the retention index concept in LC, which is widely used in GC to characterize retention of organic compounds. The use of retention indices as retention characteristics of analytes in LC was first suggested at the end of 1970s, however the application of retention indices is still somewhat rare today. There are several reasons for this. One is the relatively high sensitivity and variability of retention indices to the change of parameters of chromatographic systems. Another is the chemical restrictions in the search of the universal set of reference compounds suitable for retention scaling. Several methods were suggested for the prediction of the retention times of peptides. A frequently used approach is based on the additivity scheme and calculation of the elution time through the summation of retention coefficients of amino acids constituting the peptide. Such an approach allows fairly accurate predictions of the retention time of peptides made up of not more then 15–20 amino acid residues. Additional correction factors were suggested to improve predictions including corrections for the peptide length, peptide hydrophobicity, sequence of amino acids, etc. Suggested procedures are discussed in detail. Application of predicted retention times in the identification of peptides is considered. Current status of LC retention data collections is presented.     

Model for predicting comprehensive two-dimensional gas chromatography retention times

A model for approximating the relative retention of solutes in comprehensive two-dimensional gas chromatography (GCxGC) is presented. The model uses retention data from standard single-column temperature-programmed separations. The one-dimensional retention times are first converted into retention indices and then these indices are combined in a simple manner to generate a retention diagram. A retention diagram is an approximation of the two-dimensional chromatogram that has retention order and spacing in both dimensions similar to that found in the experimental chromatogram. If required, the retention diagram can be scaled to more closely resemble the two-dimensional chromatogram. The model has been tested by using retention time data from single-column gas chromatography-mass spectrometry and valve-based GCxGC. A total of 139 volatile organic compounds (VOCs) were examined. Approximately half of the VOCs had a single functional group and a linear alkyl chain (i.e., compounds with the structure Z-(CH(2))(n)-H). The retention diagrams had primary retention orders that were in excellent agreement with the GCxGC chromatograms. The relative secondary retention order for compounds with similar structures was also accurately predicted by the retention diagram. However, the relative secondary retention for compounds with dissimilar structures, such as acyclic alcohols and multi-substituted alkylbenzenes, were less accurately modeled. This study demonstrates how readily available single-column retention time data can be used to provide an a priori estimate of the relative retention of solutes in a GCxGC chromatogram. Such a capability is useful for screening possible combinations of stationary phases.     

Strategy for the identification of key odorants: Application to shrimp aroma

The GC-SNIF technique was used to obtain the olfactograms of shrimps, and their impact odorants were identified by MS hyphenated to the GC/olfactometric system and by comprehensive two-dimensional GC hyphenated to a time-of-flight MS. Confirming these identifications by their linear retention indices required application of a new strategy to compare retention indices between both instruments and with the in-house database. The aldehydes were confirmed by using their pentafluorophenylhydrazone derivatives, and 2-ethyl-3,5-dimethyl pyrazine had to be resolved from co-eluting compounds and then identified by multidimensional GC hyphenated to an MS and a sniff port. In both shrimp products, the most important odorants were trimethylamine, 2-acetyl-1-pyrroline, and 2-ethyl-3,5-dimethyl pyrazine, together with common carbonyl compounds.     

GC behaviour of symmetrical n-dialkyl sulphides under isothermal and temperature programming conditions

Retention indices were determined for a homologous series of n-dialkyl sulphides on three stationary phases (SE-30, OV-17 and XE-60) under isothermal and linear temperature programming conditions. Under these two different GC conditions, equations were derived for each of the three stationary phases which showed the dependence of retention index on the number of carbon atoms and the boiling points for a homologous series of n-dialkyl sulphides. The equation for the correlation isothermal retention index was shown to be applicable to the identification of n-dialkyl sulphides using linear temperature programming. It was found that the GC behaviour of n-dialkyl sulphides makes these compounds suitable for use as a standard series instead of n-alkanes for the calculation of retention indices in GC analysis in which detectors insensitive to n-alkanes are employed. The use of the homologous series of n-dialkyl sulphides for the calculation of sulphide retention indices can be great practical importance in the microanalysis of natural compounds. We have used this method successfully in the analysis of pesticides containing S-atoms.     

Identification of unknown compounds on the basis of retention index data in comprehensive two-dimensional gas chromatography

The identification of unknown compounds in complex samples is very difficult. Comprehensive two-dimensional gas chromatography (GC x GC) provides very good resolution and improved identification reliability. Mass spectrometry is a powerful identification tool and retention index data are another good approach to this end. In this study, a second-order polynomial was used to calculate retention index data based on n-alkanes beyond the region of the 'isovolatile' curve in GC x GC, and the results in the 2nd dimension were validated by using the same stationary phase column in one-dimensional GC. To test the usefulness of the method, volatile compounds in a tobacco leaf extract fraction were analyzed using GC x GC, and 60 compounds were identified on the basis of their retention indices.     

毛细管气相色谱/傅立叶变换红外光谱分析高温煤焦油中的重油馏分

 在原有工作基础上,采用毛细管气相色谱/傅立叶变换红外光谱-色谱保留指数(GC/FTIR-RI)联合解析技术,研究了高温煤焦油重油馏分的化学组成。分别从重油馏分F7(300～330℃)和F8(330～360℃)中分离并鉴定出70和61种化合物,了解到不同配煤工艺对煤焦油组成与性能的影响,从而获得了一些有意义的结果,为煤焦油的集中加工和新产品开发提供了重要依据     

香水百合香气成分的气相色谱保留指数三维定量构效关系研究

采用比较分子场分析（CoMFA）和比较分子相似性指数分析（CoMSIA）方法,研究了香水百合中38种香气成分分子结构与气相色谱保留指数值之间的定量构效关系。用外部测试集验证法和留一交叉验证法对模型的稳健性和预测能力进行了检验,并通过CoMSIA模型和CoMFA模型的分子场三维等势图研究了这些化合物分子中不同化学结构对保留指数值的影响。检验结果表明,所建立的CoMSIA模型和CoMFA模型都具有较好的稳健性和预测能力,且能够合理解释结构对保留指数值的影响,可应用于对香水百合香气成分的色谱保留指数值的预测。与CoMFA模型相比,CoMSIA模型的预测准确度更高,在香水百合香气成分的色谱定量构效关系研究中,显然有更好的应用前景。     

Polycyclic Aromatic Hydrocarbons Formation from Fuel and Additives Combustion

A study has been made of the effect of additives to the fuel of a turbulent diffusion flame on the formation of soot and polycyclic aromatic hydrocarbons (PAHs). Fuels containing a polystyrene thickener doped with benzene proved to have many advantages over unthickened fuels. Most significant were an increase in the burning time and the flash point. Nevertheless, polystyrene and benzene additives to a considerable extent increased the formation of soot and PAHs. The analysis of PAHs in this study was made by capillary gas chromatography (GC) and capillary gas chromatography/mass spectrometry (GC/MS). A total of 42 individual compounds were characterized by their retention indices and mass spectra.