For wide class characterizations of volatile organic compounds (VOCs), conventional gas chromatography mass spectrometry (GC-MS)-based techniques are utilized. These GC-MS-based chemical identification approaches typically rely on library searches against ion fragmentation patterns of known compounds. Although MS library searches can often provide correct chemical identities, erroneous chemical assignments of structurally similar unknown compounds are also possible. Other detection systems, such as absorption spectrometers, have been used for VOC analysis and can provide complementary absorption data. Here, we demonstrate the analytical advantages of coupling vacuum ultraviolet (VUV) absorption spectroscopy and MS in tandem for the improved characterization of structurally similar VOCs. We also discuss technical considerations and limitations of coupling a VUV spectrometer to a quadrupole mass spectrometer. Moreover, we show that combining the isomer selectivity of VUV spectroscopy, as a nondestructive analyte detection approach, with the mass selectivity of MS in a VUV-MS detection system improves characterization of GC-eluting compounds. Utilizing GC/VUV-MS data, we demonstrate that orthogonal VUV and MS library searches improve identification of VOCs present in complex mixtures such as a mixed standard sample, a commercial perfume product, and an essential oil sample.

Chemical identification often relies on matching measured chemical properties and/or spectral "fingerprints" of unknowns against their precompiled libraries. Chromatography, absorption spectroscopy, and mass spectrometry are all among analytical approaches that provide chemical measurement databases amenable to library searching. Occasionally, using conventional single-library or single-domain searches can lead to misidentification of unknowns. To improve chemical identification, we present a tandem gas chromatography/vacuum ultraviolet-mass spectrometry (GC/VUV-MS) chemical identification approach that utilizes databases from GC, VUV spectroscopy, and mass spectrometry analyses for a "multidomain" library search. Using standard chemical mixtures as well as aroma compounds as test cases, we demonstrate that multidatabase library searches utilizing GC, VUV, and MS data results in fully correct identification of chemical mixtures examined here that could only be identified with a 69.2% or an 88.5% success rate with MS or VUV library searches alone, respectively. Additionally, we introduce a library- and data domain-independent metric for evaluating the confidence of library search results. Using multidomain library searches improves both the chemical assignment accuracy and confidence.

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