Vacuum Ultraviolet Spectroscopy and Mass Spectrometry: A Tandem

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Vacuum Ultraviolet Spectroscopy and Mass Spectrometry: A Tandem Detection Approach for Improved Identification of GC-Eluting Compounds Ian G. M. Anthony, Matthew R. Brantley, Christina A Gaw, Adam R Floyd, and Touradj Solouki Anal. Chem., Just Accepted Manuscript • DOI: 10.1021/acs.analchem.8b00531 • Publication Date (Web): 05 Mar 2018 Downloaded from http://pubs.acs.org on March 10, 2018

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Analytical Chemistry

Vacuum Ultraviolet Spectroscopy and Mass Spectrometry: A Tandem Detection Approach for Improved Identification of GC-Eluting Compounds Ian G. M. Anthony, Matthew R. Brantley, Christina A. Gaw, Adam R. Floyd, and Touradj Solouki* Department of Chemistry and Biochemistry, Baylor University, Waco, TX, USA

Abstract (Word Count: 184) For wide class characterizations of volatile organic compounds (VOCs), conventional gas chromatography mass spectrometry (GC-MS)-based techniques are utilized. These GC-MSbased 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 combing the isomer selectivity of VUV spectroscopy, as a non-destructive 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 complex mixtures such as a mixed standard sample, a commercial perfume product, and an essential oil sample.

Corresponding Author *E-mail: [email protected]. Fax: 254-710-4272.

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Analytical Chemistry 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Introduction Unequivocal identification of volatile chemicals is crucial to numerous fields of science including breath analysis,1-3 cellular culture identification,4 forensics,5-8 industrial applications,911

and many other research endeavours.12 As “real-world” samples rarely contain only one or a

few compounds, characterization of these complex sample mixtures typically involves a separation technique, such as gas chromatography (GC), two-dimensional gas chromatography (GCxGC),3,13 or temperature programmed thermal desorption.14 Gas chromatography devices are often coupled to a detector such as a flame ionization detector (FID) or a thermal conductivity detector (TCD).15 Many of these GC detectors generate concentration-dependent responses in a single dimension for most or all compounds of interest.16 Thus, despite a host of advantages such as affordability, minimal maintenance, and durability, these detectors are limited in the information content provided by the detection event17 and their viability for analyte identification depends on the reproducibility of the separation technique (e.g., highly consistent and precise retention times).18 Detectors providing additional analyte-dependent information, such as ion fragmentation patterns in mass spectrometry19 (MS) or spectroscopic characteristics in spectroscopy20, allow for more confident chemical assignments by matching experimentally acquired data to reference data (i.e., within a library). Mass spectrometers are GC-compatible detectors that can provide molecular weight and structural details unmatched by other conventional detectors.21,22 In mass spectrometry analyses, the mass-to-charge (m/z) values of ionized compounds are measured for simultaneous detection of multiple mass-resolved chemicals.23 Although many gas-phase ionization methods, such as chemical ionization (CI),24 atmospheric pressure photo ionization (APPI),25 radio frequency ionization (RFI),26 and inductively coupled plasma (ICP)27 have been utilized in MS analyses, electron ionization (EI) is the most commonly used ionization technique for the MS detection of GC-amenable compounds.28 Most organic molecules yield a significant number of fragment ions with the typical EI source condition of 70 electron volts (eV). Under stable source conditions, adequate signal-to-noise ratio, and a properly tuned mass analyzer, ion fragmentation and detection can be highly reproducible.29,30 The fragmentation “fingerprints” can then be searched against EI-MS libraries for analyte identification. 28,31-33


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Vacuum ultraviolet (VUV) absorption spectroscopy is a valuable analytical technique that can provide an additional dimension of analysis for analyte characterization.3,13,34 Although VUV absorption spectroscopy has been used for a number of years,35,36 it is only recently that a commercially-available detector has been introduced for use with GC analysis.34,37 Photoabsorption by analytes in the commercial VUV spectrometers’ detection regions of ~125 to 240 nm produces spectral “fingerprints” that, similar to EI-MS data, can be matched against a reference library for chemical identification.38-40 As MS and VUV absorption spectroscopy provide information in two complementary domains, library-based chemical identifications using both systems can allow for accurate chemical identifications in cases where one or both systems would, alone, fail. Herein, we report the assembling and testing of a GC/VUV-MS tandem detection system for the improved identification of GC-eluting compounds. We discuss experimental considerations for assembling a GC/VUV-MS system and provide examples that demonstrate the superior performance of VUV-MS tandem detection over individual VUV and MS detections alone. Experimental Sample preparation: The analytes selected for GC/VUV-MS experiments were either those presumed to be challenging to distinguish by (a) VUV alone (e.g., alkanes), (b) MS alone (e.g., isomers), or (c) from “real-world” samples (i.e., perfume and essential oil). All purchased compounds had a purity of 99% or greater unless otherwise noted. 1,2-dichlorobenzene (1,2DCB), 1,4-dichlorobenzene (1,4-DCB), heptane, octane, nonane, linalool, ethyl salicylate, (+)-αpinene, and “Programmed Test Mix” (PTM) were purchased from Sigma Aldrich Corp. (St. Louis, MO - USA). 1-octadecene (90% purity), and 1,3-dichlorobenzene (1,3-DCB) (≥98% purity) were purchased from Alfa Aesar (Haverhill, MA - USA). Dichloromethane and methanol were purchased from ThermoFisher Scientific (Waltham, MA - USA). Perfume was purchased from a local perfumery in Waco, TX and stored at 0 °C. A vial of “Grapefruit Essential Oil” was purchased from an online retailer via Amazon (Seattle, WA - USA). Helium (99.9999% purity) and nitrogen (99.999% purity) gases were purchased from Praxair, Inc. (Danbury, CT - USA). All chemicals were used without additional purification.



To generate the mixture of standards, a solution containing 2,000 µg/mL of each DCB isomer (i.e., 1,2-DCB, 1,3-DCB, and 1,4-DCB) was first prepared in methanol. 250 µL portion of this DCB isomer mixture solution was combined with 500 µL of the PTM standard in a new, 2 mL screw-thread vial (VWR: Radnor, PA - USA) equipped with a PTFE/red rubber septa and polypropylene cap (yielding a solution that contained ~667 µg/mL of each DCB isomer with concentrations of the compounds in the PTM standard solution between 290 to 353 µg/mL). Final sample constituent concentrations were selected such that the signal responses from the VUV and MS detectors would be within both detectors’ linear response ranges (for more information regarding the detectors’ response ranges, see S1). A list of the compounds in the standard mixture (PTM + DCBs) as well as compounds identified in the perfume and essential oil samples along with their detection rankings are provided in table 1 (as discussed in more detail in Results and Discussion section). For the retention time confirmations of linalool, ethyl salicylate, and oxybenzone, a 1,000 µg/mL ternary solution of these three analytes was prepared in methanol. This solution was then analyzed in an identical manner as the perfume sample. All samples were allowed to return to ~25 °C prior to their GC injections. Gas chromatography: All experiments were performed in triplicate; method blanks were used in-between each sample run to trace and eliminate any potential sources of carry-over and/or artificially introduced contaminations. For the perfume sample or the ternary solution of linalool, ethyl salicylate, and oxybenzone, 1.0 µL solutions were injected (using a 1 µL, 26 gauge, 2.75” syringe, Hamilton Company: Reno, NV - USA) into the heated (300 °C) injection port of the GC (model: GC-14B, Shimadzu Corp.: Kyoto - Japan) equipped with a stainless steel column (model: MXT-1, stationary phase: 100% dimethyl polysiloxane; length: 60 m; I.D.: 0.28 mm; film thickness (df): 3.0 µm; Restek Corp., Bellefonte, PA - USA). For GC analysis of both the essential oil and PTM + DCBs standard mixture, 10 µL solutions were used (using a 10 µL, 22 gauge, 2,75” syringe, Hamilton Company). Helium was used as the GC carrier gas at an optimized head pressure setting of ~43.5 pounds per square inch gauge (psig). Unless otherwise specified, upon each sample injection (using split ratio of 25:1), the temperature was held isothermal for 5 minutes, then ramped from 50 °C to 285 °C (at a rate of 5 °C min-1), where it remained isothermal for 5 minutes. The perfume sample was also analyzed with a second set of Page 4 of 19 ACS Paragon Plus Environment

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triplicate experiments under isothermal conditions at 285 °C (to enhance the observation of the oxybenzone peak). All other GC parameters (head pressure, injection temperature, etc.) were identical for both temperature gradient and isothermal experiments. Vacuum ultraviolet spectroscopy: The GC effluent was directed into a VGA-100 VUV spectrometer (VUV Analytics, Inc., Austin, TX - USA) through an insulated, stainless steel transfer line (length of 61 cm, I.D. of 0.25 mm, heated with temperature-controlled, resistive heating wire to 210 °C). For all experiments, the VUV wavelength (λ) detection range was 125– 240 nm and helium was used to pressurize the VUV spectrometer’s source optics’ housing. The detection cell and internal VUV transfer line (I.D. of 0.28 mm) were kept at 275 °C. The VUV spectra were collected by first collecting a “dark” spectrum (averaged using 100 spectra each integrated over 11 ms in the absence of VUV light). Then, a “reference” spectrum (averaged using 100 spectra over 11 ms with the VUV lamp on) was acquired. Finally, the series of absorption spectra (averaged using 20 scans of 11 ms with the VUV lamp on) were measured and corrected against the background “reference” spectrum.34 These parameters were chosen as they provided a reasonably noiseless signal at a tolerable acquisition rate (i.e., ~4.5 Hz). No additional make-up gases were used. Mass spectrometry: The VUV exhaust transfer line was re-routed to exit through the VUV via a stainless steel heated transfer line (I.D. of 0.10 mm, length of 76 cm, heated to 210 °C) and into a triple quadrupole mass spectrometer (TQMS) (Model 1200L, Varian, Inc., Palo Alto, CA - USA). This instrumental setup allowed to maintain MS ionization source pressure of 100 to 150 mTorr within a GC run while the VUV flow-cell registered ~-0.105 psig (i.e., -0.105 psi relative to atmosphere). No split was used between the VUV spectrometer’s output and the MS inlet. The electron ionization (EI) source of the TQMS was operated in positive-ion mode and electron energy of 70 eV.41 The TQMS was operated in scan mode (Q1: scan, Q2 and Q3: transfer) with a scan range of 35–350 m/z. An MS acquisition frequency of 1 Hz was used. The ion source and MS internal line temperatures were both set to 250 °C. Main vacuum chamber pressure was maintained at ≤ 5.5 × 10-7 Torr. To ensure optimal performance, detector voltage (~1450 V) and other parameters were automatically adjusted by performing daily instrument



calibration/auto tuning prior to all MS measurements. See Scheme 1 for a block diagram of the GC/VUV-MS assembly. Data processing and library searching: VUV background correction was performed using the VGA-100 Control Software (version 5.04.177).40 First, a baseline-level region (≥ 5 seconds) prior to, but near, the elution of a VUV peak of interest was selected as the background region; then the corresponding peak was selected as the signal region and the “average” function was applied.34 For extraction of mass spectra from co-eluting peaks (i.e., the peaks labeled “I1, J1” in Figure 4), halves of the GC peaks (~ 4 s) that corresponded to higher amounts of the analytes of interest were selected as the signal region and remainders of respective GC peak halves (~4 s) that corresponded to the other co-eluting analytes were selected as background regions. Mass spectra were background corrected using the Varian Mass Workstation software (version 6.9.1)41. In most cases, MS spectral-averaging was performed across the entirety of each GC/MS peak. VUV spectral library searches were performed using a custom script (see S2) written in Python (CPython 3.6.1, Python Software Foundation, DE - USA) and a commercial VUV spectral library.42 The custom script generated Pearson correlation coefficients (R2) for the measured VUV spectra against their matching VUV library spectra from a VUV library42 that contained some user-provided spectra (such as those of oxybenzone and ethyl salicylate). To conduct batch-processing of the VUV library searches, a custom script was used and this approach yielded R2 values identical to those produced by the commercial VUV software. The matched entry with the highest R2 was selected as the identified compound. Mass spectral library searches were performed using MS Search version 2.0f (National Institute of Standards and Technology (NIST), MD - USA)43 against the NIST 2014 EI-MS library44 using the default parameters. All analyte GC retention indices were obtained from the NIST 2014 library.44 Results and Discussion Multi-domain VUV spectroscopy and MS: The VUV and MS analyses provide data in two distinct domains. This data independence or orthogonality offers a unique advantage that can be utilized to improve unknown identification with GC/VUV-MS. For example, Figure 1 shows representative VUV (left) and mass (right) spectra of heptane (top), octane (middle), and nonane


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(bottom). The VUV spectra for these three alkanes are quite similar with almost no distinguishing features. Although the regions below λ~136 nm may appear to possess some distinguishing features (i.e., the pattern of depressions at 125–140 nm), these generally irreproducible and sharp features are the consequence of low VUV light transmission at these wavelengths and the inverted spectral pattern of nitrogen present in the source optics’ housing.34 Thus, these sharp spectral features alone (Figure 1, left panels) are insufficient for specific alkane-chain identification. The lack of distinguishing features in the VUV spectra of these alkane chains made it difficult for a VUV library search to provide conclusive matches. In contrast, the mass spectra shown in Figure 1 (right panels) each have a unique, identifying feature (viz., radical cation (M•+) peaks at 100, 114, and 128 m/z for heptane, octane, and nonane, respectively). Therefore, in this case (Figure 1), the MS data provided higher analyte specificity than the corresponding VUV data. However, Figure 2 demonstrates the powerful advantage of VUV spectroscopy in cases where MS fails to differentiate between similar chemical structures such as certain structurally similar isomers. Figure 2 shows representative VUV (left) and mass (right) spectra of the 1,2-DCB (top), 1,3DCB (middle), and 1,4-DCB (bottom) isomers. The three VUV spectra in Figure 2 show distinguishing features such as: (a) shifted centroids of the main absorption band in the spectral region of λ ~ 170–200 nm (the vertical, dotted line at ~185 nm is intended to aid in observing the centroid shift), (b) differing slopes and peak shapes for the same region, (c) a unique second peak at λ ~220 nm for 1,4-DCB, and (d) differently shaped absorbance profiles between λmax ~135– 155 nm. These features persist even in the presence of matrix effects and can aid in spectral deconvolution.45,46 However, in contrast to Figure 1, the mass spectra in Figure 2 possess almost no distinguishing features (i.e., the presence of different m/z’s or changes in their relative abundances). Therefore, for the analysis of DCB isomers (Figure 2), VUV absorption spectroscopy provided greater analyte specificity than MS. Hence, Figures 1 and 2 highlight the complementary nature of VUV spectroscopy and MS as a tandem detection system for analyte identification. In-series detection and photodegradation: High-energy, single-photon VUV irradiation can ionize and fragment compounds (and is used as an ionization source for MS).47-49 However, a low-energy VUV absorption event is reportedly not destructive.34 For instance, at the shorter Page 7 of 19 ACS Paragon Plus Environment


wavelength of 125 nm (~9.9 eV), there is sufficient energy to ionize and potentially photodissociate some molecules; however, detection of intact molecules are possible because of potential ion neutralization and low cross section for photodegradation processes within the VUV cell. In-series VUV-MS detection approach allowed us to confirm that, under our experimental conditions, mass spectra of post-VUV detected analytes (including α-pinene and dichloromethane which are known to photodegrade when exposed to VUV light50,51) were not appreciably altered (i.e., by changing the VUV lamp to “on” or “off”, the GC peak heights and areas were not affected and the relative abundances of m/z values and corresponding fragmentation patterns across the GC peak remained constant, see Figure 3). Further discussions and additional experimental details/results on this topic are included as S3 and S4. Although a parallel (i.e., post-GC split to both VUV and MS or GC/VUV/MS) detection approach is also possible, an in-series configuration was used for the reported data here. In-series detection may provide a more confident chemical identification approach for measurements that require high sensitivity52 and accurate quantitation.53-55 Considerations for VUV-MS coupling: A narrow-bore transfer line (I.D. of 0.1 mm, length of 76 cm) was installed between the VUV and MS. This transfer line provided a sufficient conductance limit between the VUV flow-cell and MS source and avoided the decreased VUV sensitivity that was observed when a GC column type transfer line (I.D. 0.28 mm) was employed. All GC/VUV-MS data reported in this paper were collected using the 0.1 mm ID transfer line. To evaluate the addition of the VUV spectrometer on the mass spectrometer’s performance, the VUV spectrometer was disconnected and the MS was directly connected to the GC (using all identical experimental parameters listed above). The PTM + DCB standard mixture was analyzed (in triplicates) in both GC/VUV-MS and direct GC/MS configurations. To compare the GC elution and peak profiles under the two different instrumental configurations, the stacked GC/VUV-MS, GC/VUV-MS, and GC/MS chromatograms are displayed in Figure 4 (letters in bold indicate the specific detector that was used to generate a displayed GC plot). The top and middle plots in Figure 4 (top and middle) are from a single GC/VUV-MS run. The bottom plot of Figure 4 is from a separate GC/MS (VUV disconnected) experiment. The Page 8 of 19 ACS Paragon Plus Environment

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analyte peaks are labeled from A1 to O1 and assigned identities of the corresponding 15 compounds are listed in Table 1 (A1 to O1, top section categorized as “PTM with added DCBs”). An observed unknown contaminant (present in the pure PTM sample as well) at GC retention time of tR ~ 37 min is denoted with asterisks in Figure 4; the VUV spectra of this unknown were not very similar to any spectra in the VUV library and thus the unknown contaminate was not subject to the same VUV-MS analysis as other compounds in the chromatograms. GC peaks with gray labels (peaks C1, D1, E1, K1, and N1 in Figure 4) correspond to compounds with aromatic rings. Between the direct GC/MS and tandem GC/VUV-MS trials, elution times of these five aromatic compounds were shifted to slightly longer tR by ~7 s. Presumably, under our experimental conditions, slight preferential retention of aromatic compounds occurred pre-VUV flow cell transfer-line. In tandem GC/VUV-MS configurations (top and middle plots in Figure 4), there were no GC shifts observed between the VUV and subsequent MS detections. To assess potential GC peak broadenings for all three modes of Figure 4, the GC peakwidths at half-height (∆PW50%) for the observed 15 compounds from the PTM + DCB standard mixture were measured. Experimentally calculated average ∆PW50% values for the VUV spectroscopy data (in GC/VUV-MS mode) and MS data (in GC/VUV-MS and GC/MS modes) were 7.97 ± 0.12 s, 8.52 s ± 0.14 s, and 8.43 ± 0.11 s, respectively (n = 45 for all three averages, as triplicate sets of 15 observed GC peaks). The ∆PW50% measurements for MS detections were performed on selected ion chromatograms (SICs) of observed base peaks for each individual compound; the VUV peak width measurements were performed by observing the full wavelength range (in the case of convoluted GC-VUV peaks such as “H1” and “I1, J1” peaks in top and middle plots in Figure 4, the “VUV Model and Analyze” software package version 5.04.177d was utilized to deconvolute and measure the merged peaks’ ∆PW50%). The smaller ∆PW50% values for direct GC/MS mode indicate that the observed GC peak broadenings in tandem GC/VUV-MS mode (most likely from the gas diffusions occurring within the VUV flowcell and/or post-VUV transfer lines) are negligible and GC peak comparisons can be made for different detection modes. It is expected that future reduction of the transfer line lengths (from a total of ~2 m (~0.6 m GC to VUV, ~0.6 m internal VUV, ~0.76 m VUV to MS) for the current setup) and increasing transfer line temperature (to beyond the 210 °C currently set) will help to further improve chromatographic performance. Page 9 of 19 ACS Paragon Plus Environment


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Library search results: Table 1 shows the rankings for the library search results for the VUV and MS from the triplicate GC/VUV-MS runs. The first column, denoted with a “#” indicates the peak label for the given compound (listed in the second column) with a subscripted number to denote the sample or sample conditions. The first fifteen rows (A1–O1) in table 1 (under the title “PTM with DCBs”) correspond to assigned peaks for the standard mixture in Figure 4. The next three sets of rows in Table 1 correspond to observed analytes in the perfume sample under temperature ramp (“Perfume (Ramp)”, A2–G2) and under isothermal conditions (“Perfume (Isothermal)”, F3–H3), and the “Essential Oil” sample (A4–O4). Chromatographic plots similar to those of Figure 4 but with the perfume sample under ramp conditions (S5), perfume sample under isothermal conditions (S6), and the essential oil sample (S7) are provided in the Supporting Information with a table (S8) containing reference retention index values (NIST 2014 RI Library)44. Match rankings for the correct chemical assignments (i.e., the compounds listed under “Chemical Name”) using VUV and MS are shown in table 1 for each of the triplicate trials (T1, T2, and T3 for VUV in columns 3–5 and for MS in columns 6–8). For example, in Trial 1 of the PTM with dichlorobenzene isomers, peak H1 (corresponding to 2-Ethylhexanoic Acid) was identified correctly (i.e., match rank 1) by the mass spectral search but was misidentified as the third-best match (i.e., match rank 3) by the VUV search. As indicated in Table 1, VUV library searches of the data from the PTM + DCB sample mixture resulted in correct identification of all three DCB isomers. However, decane, undecane, nonanal,

methyl-decanoate,

methyl-undecanoate,

and

methyl-dodecanoate

were

often

misidentified. These misidentifications are due to the very similar and difficult-to-distinguish nature of long hydrocarbon chains’ VUV signatures (e.g., the top ~30–50 matches associated with decane and undecane were above 0.99 R2 for all trials, indicating that all were highlymatched). In contrast, the MS approach correctly identified decane, undecane, nonanal, methyldecanoate, methyl-undecanoate, and methyl-dodecanoate in all runs. However, the mass spectral library searches failed to distinguish the three DCB isomers from one another, leading to several misassignments. These results are not surprising, given the observed similarities among the VUV spectra of alkanes (see Figure 1) and the similarities among the MS spectra of DCB isomers (see Figure 2).


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Of the other incorrectly-identified species by MS for the PTM + DBC sample mixture, misidentification of 2,3-butanediol was likely because of its very low intensity (see Figure 4, peak A1), leading to difficult-to-ascertain ion ratios when background subtraction was applied. 2,6-xylenol and 2,6-dimethylaniline were misidentified as they both had several difficult-todistinguish isomeric forms with similar fragmentation patterns. Likewise, VUV failed to identify 2-ethylhexanoic acid (and occasionally octanol) as the specific number of linear saturated carbons was difficult to determine using the VUV domain (especially with six or more linear saturated carbons). Interestingly, without using the VUV and MS data in tandem, it would not be possible to identify the “I1, J1” peak of Figure 4 that contained co-elution of 2,6-xylenol and undecane; this is because MS cannot reliably identify isomers of xylenol and VUV cannot reliably identify longer alkane chains. However, the identification of the components of such a co-elution is made much easier when VUV and MS are used together. One advantage of the GC/VUV-MS coupling is that, with knowledge of each detection approach’s relative strengths and weaknesses, compounds can be identified in cases where one identification technique is correct and the other is incorrect. In fact, in all trials either MS, VUV, or both were correct in the identification. This demonstrates the orthogonality of the MS and VUV detection approaches, as MS excels where VUV spectroscopy does not (i.e., hydrocarbonlike chains) and VUV excels where MS does not (i.e., isomeric species). For the single entry of ethyl salicylate (E2) where both detection techniques produced an error (T1 for VUV and T2 for MS), MS misidentified ethyl salicylate as dimethyl-3nitrobenzenamine (a compound that shares many similar nominal-mass fragments as ethyl salicylate)44 and VUV misidentified ethyl salicylate as methyl salicylate (where both absorption spectral profiles appear similar to one another). However, both detection approaches ranked ethyl salicylate as their respective second-highest matches. Thus, even when both detectors misidentify a compound, the correct reference spectra (MS and VUV) may still be ranked sufficiently high for successful identification by the combined approach. In fact, if a compound is present in only one library, inspection of the relevant matches and data (both MS and VUV) may still yield valuable information leading to a more confident match.



For example, ethyl salicylate (peak E2 in S5) and oxybenzone (peak H3 in S6) did not have spectral data entries in the original VUV library. Before the addition of ethyl salicylate to the VUV library, all VUV library searches for peak E2 resulted in methyl salicylate as the top match. In contrast, the MS library search results for E2 consistently ranked ethyl salicylate highly (rank 1, 2, and 1 for T1, T2, and T3, respectively). Additionally, the mass spectral library search for E2 ranked methyl salicylate very poorly (206th, 74th, and >400th place for T1, T2, and T3, respectively), suggesting that VUV identification for E2 as methyl salicylate was highly unlikely. However, MS data suggested that E2 could correspond to a compound closely-related to methyl salicylate in the VUV domain (i.e., ethyl salicylate). Before the addition of oxybenzone to the VUV library, no VUV library “matches” closely matched GC peak H3 (i.e., manual inspection of the “highest matched” VUV spectra to H3 peak revealed significantly dissimilar spectral features between the VUV spectrum of peak H3 and all matched VUV spectra). However, the MS ranked oxybenzone highly (rank 1 for all trials of H3). To evaluate the hypothesis that the observed GC peaks (labeled E2 in S6 and H3 in S6) were ethyl salicylate and oxybenzone, we purchased standards of these chemicals and added their spectra to the VUV library. Using an updated VUV spectral library containing the spectra of these two analytes, two of the three VUV spectral searches of E2 correctly identified ethyl salicylate (one of the three trials still incorrectly identified methyl salicylate as the compound, but ranked ethyl salicylate as the second highest match). All three VUV spectral searches of H3 peak identified oxybenzone as the correct match for this previously unknown peak. Additionally, a mixture of standards of ethyl salicylate, oxybenzone, and linalool was run under similar experimental conditions as that of the perfume sample. Retention times were comparable (± 2%) to those of the investigated compounds, providing another dimension (i.e., GC retention index) to confirm identification of ethyl salicylate, oxybenzone, and linalool. These examples highlight the unparalleled advantage of utilizing two independent detection approaches for highly confident identification of unknown volatile organics. Although several analytes with low signal-to-noise ratio and/or convoluted GC peaks were successfully identified by using the GC/VUV-MS approach, the small size of our current VUV library (1,174 chemical entries) limited our ability to use both VUV and MS for identification of some of the observed unknowns. Nevertheless, even without using any VUV library matching, it was often Page 12 of 19 ACS Paragon Plus Environment

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possible to use VUV data to confirm or reject MS identification of an analyte (e.g., as an aliphatic or aromatic compound, etc.). We plan to increase our VUV library size for future studies. Conclusion We successfully coupled a VUV spectrometer in-series with an MS to collect multi-domain data for improved identification of GC-eluting compounds. We verified that, under our experimental conditions, the VUV absorption did not result in any significant analyte photodissociation or modification in a manner that would prevent successful MS identification. We discussed considerations for VUV-MS coupling, such as the need for a conductance limit between the VUV flow-cell and the inlet of the EI-MS source. Independent, standalone VUV and MS library searches resulted in numerous incorrect compound assignments. However, for all trials (reported here) that resulted in incorrect identifications by a single detection method (i.e., VUV or MS), the tandem VUV-MS detection method resulted in successful and correct identifications. The orthogonal nature of spectrometric (MS) and spectroscopic (VUV) data highlights the importance of this tandem VUV-MS approach for avoiding false unknown assignments (either as false-negative or false-positive outcomes). We anticipate that the use of GC/VUV-MS will improve characterization of complex mixtures (e.g., petroleum, biological, and environmental samples) and enhance correct identification of compounds in accuracy-critical analyses (e.g., forensics, explosive detection, security settings, etc.). Supporting Information (S): Calibration lines of 1,2-dichlorobenzene, linalool, and ethyl salicylate (S1); Python script to generate R2 values for VUV spectra (S2); MS data on potential sample photodegradation by VUV (S3); Comparison of “lamp on” and “lamp off” data for sample photodegradation (S4); GC/VUV-MS chromatograms of the perfume sample with temperature ramp conditions (S5), the perfume sample with isothermal conditions (S6), and the essential oil sample (S7); Reference retention indices and names of identified chemicals (S8). Acknowledgements The authors thank Carter Lantz (Baylor University) for data extraction, James Diekmann (VUV Analytics) for technical support, Dr. Johnathan Smuts for insights into VUV data analysis Page 13 of 19 ACS Paragon Plus Environment


(VUV Analytics), and Dr. Dale Harrison (VUV Analytics) for valuable discussions on VUV detection. The authors gratefully acknowledge funding provided by the National Science Foundation (IDBR - NSF 1455668), financial support from Baylor University, and the loan of the VGA-100 VUV spectrometer from VUV Analytics. Opinions, findings, conclusions, and recommendations expressed in this material are those of the authors, and do not necessarily reflect the views of the NSF, Baylor University, or VUV Analytics.


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Figure Captions: Scheme 1 shows the design of the GC/VUV-MS assembly. (I) GC injection port, (II) GC oven and column, (III) VUV lamp, (IV) VUV flow-cell, (V) VUV detector, (VI) ionization source/filament, (VII) MS quadrupoles, and (VIII) MS detector are labeled. Figure 1. VUV (left panels) and mass (right panels) spectra of heptane (top), octane (middle), and nonane (bottom), along with their respective structures. The mass spectra show analytespecific identifiable features (i.e., the peaks at m/z 100, 114, 128 for molecular radical cations, M•+, of heptane, octane, and nonane, respectively). Figure 2. VUV (left panels) and mass (right panels) spectra of 1,2-DCB (top), 1,3-DCB (middle), and 1,4-DCB (bottom) isomers, along with their respective structures. The VUV spectra show isomer specific, identifiable features (e.g., a shifting peak maximum, λmax, at ~185 nm denoted by the dashed vertical line, a unique region between λ range of ~136–150 nm, and a small local maximum at λ ~220 nm, etc.). Figure 3. Mass spectra (taken via a GC/VUV-MS experiments) of α-pinene (top) and dichloromethane (bottom) with the VUV spectrometer’s lamp in off (left) and on (right) positions. No significant differences are seen in relative abundances of molecular and/or fragment ions. Figure 4. Representative VUV (top) and MS (middle) chromatograms from a single GC/VUVMS run and a GC/MS run (bottom) for the sample mixture of PTM + DCB isomers. Labeled peaks correspond to 2,3-butanediol (A1), decane (B1), 1,3-DCB (C1), 1,4-DCB (D1), 1,2-DCB (E1), octanol (F1), nonanal (G1), 2-ethylhexanoic acid (H1), 2,6-xylenol (I1), undecane (J1), 2,6dimethylanlinine (K1), Methyl decanoate (L1), methyl undecanoate (M1), dicyclohexylamine (N1), and methyl dodecanoate (O1). An unknown contaminant is labeled with an asterisk. GC peaks corresponding to aromatic compounds (viz., C1, D1, E1, K1, and N1) are labeled in a lighter gray.



Table 1: Library search results for VUV and MS VUV MS Rankings Rankings T1 T2 T3 T1 T2 T3 #

Chemical Name

A1 B1 C1 D1 E1 F1 G1 H1 I1 J1 K1 L1 M1 N1 O1

2,3-Butanediol Decane 1,3-DCB 1,4-DCB 1,2-DCB Octanol Nonanal 2-Ethylhexanoic acid 2,6-Xylenol Undecane 2,6-Dimethylaniline Methyl decanoate Methyl undecanoate Dicyclohexylamine Methyl dodecanoate

A2 B2 C2 D2 E2 F2 G2

Limonene Linalool Benzyl acetate Linalyl acetate Ethyl salicylate α-Isomethyl ionone Diethyl phthalate

F3 G3 H3

α-Isomethyl ionone Diethyl phthalate Oxybenzone

A4 B4 C4 D4 E4 F4 G4 H4 I4 J4 K4 L4 M4 N4 O4

α-Pinene β-Myrcene Limonene Linalool Decanal α-Terpineol Carvone E-Citral Geranyl acetate Dodecanal α-Copaene β-Farnesene β-Carophylene α-Humulene Carophyllene oxide

PTM with DCBs 1 1 26 1 20 2 2 1 1 1 1 1 1 1 1 1 1 2 3 3 1 1 3 2 3 4 1 1 1 1 2 2 1 1 1 5 1 1 1 1 1 1 6 4 7 1 2 1 1 1 1 1 1 5 3 2 7 1 1 1 6 6 1 1 1 1 1 1 1 1 1 3 1 1 1 Perfume (Ramp) 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 5 2 1 1 1 2 1 1 1 1 1 1 1 2 1 1 1 1 1 Perfume (Isothermal) 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Essential Oil 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 2 1 1 1 6 7 5 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 2 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 1 1 1 1 3 1 6 1 3 6 1 5


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47x26mm (300 x 300 DPI)

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Figure 1. 62x51mm (600 x 600 DPI)



Figure 2. 62x51mm (600 x 600 DPI)


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Figure 4. 80x38mm (300 x 300 DPI)


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Scheme 1. 63x28mm (300 x 300 DPI)


Vacuum Ultraviolet Spectroscopy and Mass Spectrometry: A Tandem

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