Advances in two-dimensional GC with glass capillary columns

A versatile two-dimensional gas chromatograph is described, consisting of 2 separate ovens, one intermediate trap, an auxiliary inlet, and the necessary hardware to effect off-line switching according to the principle of Deans. The unit has been designed for use with high resolution glass capillary columns. The performance of individual instrumental components was critically evaluated. Results showed that low dead volume glass to metal connections were required in the manifold and detector lines to minimize extra-column effects. The mass of the intermediate trap must be low to allow rapid heating. Operational parameters are discussed and examples of some applications are shown.     

Classification of bacteria by pyrolysis-capillary column gas chromatography-mass spectrometry and pattern recognition

Pyrolysis followed by capillary column gas chromatography-mass spectrometry has been applied to the classification of five bacterial species of the genus Flacobacterium. Data were subjected to computerized pattern recognition using the ARTHUR software package. The results indicate that classification potential is greatly improved by the use of mass fragmentography. Other factors such as growth media, harvesting and storage conditions were found to be relatively unimportant.     

Use of computerized pattern recognition in the study of the cuticular hydrocarbons of imported fire ants. II. Comparison of the cuticular hydrocarbon patterns between different colonies of Solenopsis richteri

Gas chromatography (GC) data obtained from the cuticular hydrocarbons of the black imported fire ants are treated by methods of pattern recognition. Based on a recently described sample preparation procedure, GC data are normalized to eliminate slight variations in chromatographic conditions, and converted to the proper format for discriminant analysis by computer. The results of several methods of data treatment and display are discussed, based on the chemometrics system package, ARTHUR.     

Optimization of selectivity using sequentially coupled capillary columns

This investigation lays groundwork for the development of an optimization system for sequentially coupled capillary column systems. Three methods for calculating effective capacity factors were obtained from the literature and were tested to determine suitability for optimization use, using four test analytes and two dissimilar columns. This work concentrates on the development of a method for the estimation of optimum column temperatures in sequentially coupled systems.     

Use of computerized pattern recognition in the study of the cuticular hydrocarbons of imported fire ants. I. Introduction and characterization of the cuticular hydrocarbon patterns of Solenopsis invicta and S. richteri

A method is described in which gas chromatographic (GC) data obtained from cuticular hydrocarbons are treated by methods of pattern recognition. Based on a recently described sample preparation procedure, GC data are normalized to eliminate slight variations in chromatographic conditions and converted into the proper format for discriminant analysis by computer. The results of several methods of data treatment and display are discussed, based upon the chemometric system package, ARTHUR. The approach has the advantage of largely removing operator bias.     

Application of chemometrics to the classification of orange essence oil varieties by GLC

Orange essence oils of the Navel and Valencia variety were analyzed by GC and GC/MS using two parallel capillary columns of different selectivity. Data were normalized, converted into a computer compatible format, and transferred via an asynchronous communications interface to a mainframe computer for statistical treatment, using the chemometrics software package ARTHUR. After suitable preprocessing of the raw data, reliable classification was possible. It appears that four substances which are present in both varieties can be used for that purpose.     

Viscous fingering induced flow instability in multidimensional liquid chromatography

Viscous fingering is a flow instability phenomenon that results in the destabilisation of the interface between two fluids of differing viscosities. The destabilised interface results in a complex mixing of the two fluids in a pattern that resembles fingers. The conditions that enhance this type of flow instability can be found in coupled chromatographic separation systems, even when the solvents used in each of the separation stages have seemingly similar chemical and physical properties (other than viscosity). For example, the viscosities of acetonitrile and methanol are sufficiently different that instability at the interface between these two solvents can be established and viscous fingering results. In coupled chromatographic systems, the volume of solvent transported from one separation dimension to the second often exceeds the injection volume by two or more orders of magnitude. As a consequence, viscous fingering may occur, when otherwise following the injection of normal analytical size injection plugs viscous fingering would not occur. The findings in this study illustrate the onset of viscous fingering in emulated coupled chromatographic systems and show the importance of correct solvent selection for optimum separation performance.     

Rapid estimation of trace amounts of ethylenimine by high-pressure liquid chromatography.

A rapid procedure utilizing high-pressure liquid chromatography is described for determining trace quantities of ehtylenimine down to 0.01 ppm. The basis for the method is the quantitative reaction of ethyleneimine with the 1,2-naphthoquinone-4-sulphonate ion (Folin's reagent) to give 4-(1-aziridinyl)-1,2-naphthoquinone. Compared with the spectrophotometric procedure, this method provides a high degree of specificity and sensitivity. The method has been employed to determine ethylenimine in the pyrolysis products of polyethylenimine.     

Fuel spill identification using solid-phase extraction and solid-phase microextraction. 1. Aviation turbine fuels.

The water-soluble fraction of aviation jet fuels is examined using solid-phase extraction and solid-phase microextraction. Gas chromatographic profiles of solid-phase extracts and solid-phase microextracts of the water-soluble fraction of kerosene- and nonkerosene-based jet fuels reveal that each jet fuel possesses a unique profile. Pattern recognition analysis reveals fingerprint patterns within the data characteristic of fuel type. By using a novel genetic algorithm (GA) that emulates human pattern recognition through machine learning, it is possible to identify features characteristic of the chromatographic profile of each fuel class. The pattern recognition GA identifies a set of features that optimize the separation of the fuel classes in a plot of the two largest principal components of the data. Because principal components maximize variance, the bulk of the information encoded by the selected features is primarily about the differences between the fuel classes.