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22 February / March 2018


Figure 2: Total Ion Chromatogram Contour Plot for Sample 7. Note the separation of the bleed components from the deconvoluted spectra and in particular the separation in the y-axis (2 dimension of GC) of co-eluting components in the first dimension. For example, at 1st dimension retention time 1125 seconds there exists at least 4 co-eluting components (see Figure 3).


to successfully identify components known to be present in the blinded mixtures (see discussion).


We divided the data review process across 5 individuals (10 samples x 2 data sets EI and CI). The results of this grading system (A’s and B’s) were submitted to the EPA as the proposed blind mixtures identification results.


After submission of the blind lists of identified components to the EPA, we received the list disclosing the standards contained in each mixture. We could then evaluate our grading system against the actual results. The matching process was carried out by matching the ‘MS-ready’ InChKey from both lists. For the most part, the matching was straight forward, a match was a match. However, there were cases where InChIKey did not match due to inconsistencies among databases so seamless, automatic matching was not possible and some manual intervention was required. Comparison of the compound list from the EPA to our largest spectral database (NIST 17) gave us our best possible results (discounting those from the Cayman library) that we could expect since our initial reporting was based solely on spectral database matching. This data is summarised in Table 2.


The maximum possible percentage of correct hits based on the NIST database varies for each sample but approximately 80% of the spiked compounds were present in NIST.


There was a significant number of non-NIST compounds and those can be interpreted as laid out by others [11].


Results and Discussion:


GCxGC Advantages The combined GCxGC and HRAM TOF- MS approach provides multiple benefits for identification of known unknowns. A ‘known unknown’ is defined as: in the NIST MS database but unknown to be in a mixture. GCxGC is well-known to separate co-elutions which occur in simple 1D chromatography, therefore the ability to resolve more chemicals in any particular sample is increased significantly. Typically, this is quantified by the effective peak capacity (the ability to resolve chemical constituents) which is well described elsewhere [12]. Also, typically GCxGC data is displayed in what is known as a contour plot where, each dimension of chromatography is plotted (x and y axis) against total intensity as a colour (z axis). This visually appealing type of plot explicitly shows the extra dimension of resolution that GCxGC provides (Figure 2). The black dots indicate the deconvoluted peaks found by HRD algorithm. GCxGC is further known to separate analytes of interest from chemical noise and in some cases, it can also increase


1 2 3 4 5 6 7 8 9


10


sensitivity over non-GCxGC experiments [13]. In Figure 2 one can observe all of these phenomena except the increase in sensitivity which is not relevant for this sample set as it was not explicitly challenged for sensitivity. One can observe the very generic nature of the experiment performed where little relevant elution occurs after 2000 seconds on the x-axis. The long hold time (30 min) was performed intentionally since this was a completely blind sample we needed to be sure to elute every component from the injection (no carry over injection to injection). Obviously the chromatography can be improved even further by using all the chromatographically available space (for more information on method optimization see Simply GCxGC [14]) and in doing so


Sample # # of Spiked Compounds


95


365 185 95


365 95


365 95 95


185


# of Spikes in NIST17 (# absent in NIST)


75


261 136 86


264 82


307 83 78


146 (20)


(104) (49) (9)


(101) (12) (58) (12) (17) (39)


∑=1519 (421)


% of Spikes w/NIST 17 Spectrum


78.9 71.5 73.5 90.5 72.3 87.4 84.1 87.4 82.1 78.9


x̄ =80.7


Table 2: Number of compounds placed in samples and the corresponding number that actually existed in the NIST 2017 mainlib and replib spectral databases.


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