10 February / March 2016
Adding more Power to your GC-MS Analysis through Deconvolution
by Diane Turner MSc MRSC, Anthias Consulting Ltd
Most laboratories that use gas chromatography (GC), have at least one GC hyphenated with a mass spectrometer (GC-MS) these days. GC-MS has added advantages over GC detectors in that it provides a third dimension of data in the form of a mass spectrum (Figure 1a). The sum of the abundance of all ions at each scan number (data point) produces the total ion current, which is represented as the total ion chromatogram (TIC) and is a 2D plot similar to the data produced from a non-MS GC detector. Extracting a single ion from the 3D plot (Figure 1b), gives an extracted ion chromatogram (EIC) and is useful for finding a target compound or looking for classes of analytes that contain the same ion.
Many analysts use the mass spectra for identification of unknown analytes, whilst others use it for confirmation and increased confidence that they have found and identified the correct analyte. When performing GC-MS analyses we have two methods of achieving resolution (peak separation). The first is chromatographic resolution, where analytes in the sample mixture are physically separated by their selective interaction with the stationary phase of the analytical column and elute at different retention times. The second is spectral resolution, where analytes eluting at similar retention times (that don’t have total chromatographic resolution) are separated by their different (unique) mass to charge ratios by the mass analysing detector. Those analytes with exactly the same peak retention time and shape plus that have all the same masses cannot be separated by GC-MS using that method.
Selecting any point within the Total Ion Chromatogram, will show the ion abundance versus mass to charge ratio, called the mass spectrum (Figure 1c) and these were the detected ions that were summed to give that data point. If there is total chromatographic resolution, the resulting mass spectrum will be obtained containing the mass spectrum for just that peak plus any background ions from carrier gas impurities and column bleed. If that peak is chromatographically impure, then this will result in a mixed mass spectrum, which may contain a low or high proportion of ions from the co-eluting peak, depending on the relative abundance of that peak. The percentage of the total ion signal at the
Figure 1: (a) GC-MS gives 3 dimensional data, (b) an extracted ion chromatogram shows all peaks containing that ion, (c) a single data point gives a single mass spectrum.
peak apex belonging to the peak of interest is known as the peak purity [1].
If, by GC-MS, we analyse individual standards of our target analytes, we obtain a retention time and mass spectrum for each. When these targets are analysed in a simple mixture and there are chromatographic co- elutions, unique masses could be identified in their mass spectra that aren’t present in coeluting peaks and the presence and ratios of these ions could be used to identify and quantify them.
When we are extracting mass spectra to identify unknown components, it can be difficult to see if there are any co-elutions with other components. A co-elution would produce a mixed mass spectrum and when library searched that mixed mass spectrum would most likely result in a poor quality match, no potential matches or the incorrect identification. There are ways to check for co-elutions, this can be achieved manually by either clicking across the peak to see if the mass spectrum changes (Figure 2) or by extracting key ions to produce EICs, which when overlaid should show the same retention times and shapes indicating that they all belong to the peak of interest. There are ways to improve the quality of the mass
spectrum for library searching, the most common by background subtraction on both sides. However, in most software performing both background subtraction and extracting ions manually can be a lengthy and time consuming process especially when looking at many peaks in chromatogram, and/or when there are many samples.
Figure 2: TIC looks like 1 peak, EICs show 3 peaks with different apexes, clicking across the peak shows a change in the mass spectrum. Slight changes in the mass spectrum can be a result of spectral skewing (otherwise known as spectral tilting) for scanning instruments (Figure 3).
Even with the identification of target analytes in dirty or complex samples using their unique masses in either scan or SIM acquisitions, matrix interferences can co-
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