Introduction
Precise characterisation of petroleum-derived fuels is crucial for quality control, to understand the reactions that take place during refining processes, and also for environmental monitoring. However, individually identifying the thousands of components present in these complex samples can be impractical.[1,2]
Group-type analysis using comprehensive two-dimensional gas chromatography (GC×GC) offers a practical approach to this problem. The vastly expanded separation space of GC×GC (compared to conventional chromatography) reduces the incidence of co-elution, while the ‘roof-tiling’ effect facilitates the simple division of hydrocarbons into structurally-similar classes. This approach is now widely used for the analysis of petrochemicals, typically in conjunction with flame ionisation detection (FID) for ‘gold-standard’ quantitation.
However, difficulties can arise when compound classes overlap, and for this reason time-of-flight mass spectrometry (TOF MS) has become important to identify class boundaries accurately, and so generate ‘stencils’ that can be reliably applied to unknown samples (acquired on either TOF MS or FID).
This article describes how group-type analysis can be applied to the case of petrochemicals, using flow-modulated GC×GC and the data-mining tools available in the ChromSpace® GC×GC software package. We additionally show how analyte speciation can be aided by the generation of soft EI data using Tandem Ionisation® technology.
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