1103
Anal. Chem. 1084, 56, 1163-1168
Linked Gas Chromatography/Fourier Transform Infrared/Fourier Transform Mass Spectrometry with Integrated Electron Impact and Chemical Ionization David A. Laude, Jr., Gregory M. Brissey, Carl F. Ijames, Robert S. Brown, and Charles L. Wilkins*
Department of Chemistry, University of California-Riverside, Riverside, California 92521
Molecular weight Information is obtained directly from a linked GC/IR/MS experiment in whlch electron Impact and chemkal loniratlon mass spectral data are alternately collected during a single gas chromatographic run. This integrated GC/IR/MS experlment is demonstrated to provlde results comparable to those for the analogous discrete experiments requlrlng two separate GC runs. I n addition, software Implemented to process the GC/IR/MS data with minimal human interventlon Is demonstrated to lower analysls tlmes tor complex mlxtures to a few hours.
It has been demonstrated previously that the complementary information provided by direct-linked infrared and mass spectrometry allows the unambiguous identification of compounds that would not be identified by the sole use of either IR or MS (1-5). Although discrete gas chromatography/infrared (GC/IR) and gas chromatography/mass spectrometry (GC/MS) experiments provide the analogous chemical information (6),a direct linked GC/IR/MS system offers the advantages of a more efficient experimental procedure coupled with simplified data analysis. The practical feasibility of such a linked system was recently demonstrated for the qualitative analysis of two relatively complex mixtures, peppermint oil and a commercial lacquer thinner (I). Central to the further development of GC/IR/MS as a viable analytical method is complete automation of the procedure; previous experiments have required several days to complete both the data collection and processing. In the present work two significant improvements reduce analysis times to a few hours. The previously independent electron impact and chemical ionization GC/MS experiments are combined into a single integrated experiment. Postrun processing time is reduced dramatically through the implementation of software which precludes the need for human intervention in the analysis of the data. Chemical information provided by the mass spectral analysis includes not only library searches of electron impact (EI) spectra but also component molecular weights from chemical ionization (CI) data. The utility of molecular weight data has already been demonstrated in the GC/IR/MS analysis of complex mixtures. For example, molecular weight information from methane CI data was used in the identification of 18 of 30 lacquer thinner components separated (1). However, in that work the CI data was not obtained from the linked GC/IR/MS run but rather from a discrete GC/MS experiment. The ability to acquire electron impact and chemical ionization data from a single GC/MS experiment has been demonstrated for both quadrupole and sedor instruments through hardware modifications of the source or CI reagent gas inlet (7, 8). An advantage of the Fourier transform mass spectrometer (FTMS) is the ability to perform the same experiment through a simple change in the software parameters. The integrated EI-CI GC/FTMS experiment can offer a 0003-2700/S4/0356-1163$01.50/0
Table I. Component Names and Registry Numbers for the Synthetic Mixture elution peak time, no. reg no. compound name min 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17
107313 67641 79201 110543 141786 109693 110827 1078709 142825 79016 105373 108883 100414 108383 108861 98862 623121
methyl formate acetone methyl acetate hexane ethyl acetate 1-chlorobutane cyclohexane 2-pentanone heptane trichloroethylene ethyl propionate toluene ethylbenzene m-xylene bromobenzene acetophenone p-chloroanisole
4.9 5.6 6.2 8.0 8.5 10.0 10.5 11.6 12.1 12.3 12.7 15.7 19.4 19.7 21.6 24.7 25.4
considerable savings in time, data storage requirements, and efficiency but does have the disadvantage of requiring a trade-off in MS sensitivity or GC resolution. The importance of these parameters will be discussed as a comparison is made between discrete and integrated EI-CI experiments as applied to linked GC/IR/MS. Perhaps the most imposing problem with GC/IR/MS analysis is the development of the software necessary for data processing. It is not feasible to evaluate the many megabytes of data produced in a typical experiment if considerable human intervention is required. The computer-controlled data processing approach presented in this paper provides a far more efficient alternative for the analysis. As Figure 1demonstrates, following the processing of the data into a manageable form, the algorithm for compound identification is divided into two parts. The IR and El-MS search results are first compared by using a match of search output registry numbers as the criterion for identification. If this comparison is unsuccessful, the complementary IR and CI-MS data are used in a second way; the molecular weight value inferred from the CI spectrum is compared with the likely molecular ions of the best spectral matches from the IR search results. As a test of the integrated EI-CI experiment and the new software, the 17-component synthetic mixture listed in Table I was used in a series of linked GC/IR/MS experiments. Mixture components were chosen to represent a variety of chemical functionalities including aliphatic and aromatic halogen, carbonyl, and hydrocarbon compounds.
EXPERIMENTAL SECTION Figure 2 is a block diagram representing the system configuration. The major Components include a 5880-A Hewlett-Packard gas chromatograph linked in parallel with a Nicolet 60SX Fourier transform infrared spectrometer and a Nicolet FTMS-loo0 Fourier transform mass spectrometer. Both spectrometers are controlled 0 1984 American Chemical Soclety
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ANALYTICAL CHEMISTRY, VOL. 56, NO. 7, JUNE 1984
j-[
I
+, i 4
IDENTIFICATION
I
Figure 1. Flow chart of the software developed for processing GC/ IR/MS
data.
DRIVE
DRIVE
Figure 2. Block diagram of the direct linked GC/IR/MS system.
by Nicolet 1280 computers running Nicolet-developed GC/IR and GC/MS software. IR and MS data are stored on 5-Mbyte Hawk dual disk drives. Data processing is accomplished with Nicolet 1280 and Vax 11/750 computers connected by RS-232 lines. A capillary split injector with a ca. 1O:l split ratio is used for sample injection onto a 60 m X 0.323 mm i.d. J+W DB-5 bonded phase capillary column. The postcolumn effluent is split at a low dead volume Swagelok tee between the IR and MS with a ca. 2005 ratio. Approximately 30 cm and 100 cm of 0.25 mm i.d. empty fused silica tubing connect the splitter to the IR light pipe and MS vacuum system, respectively. Flow restriction to the MS is obtained by inserting between the tee and the fused silica a piece in. stainless steel tubing with 0.007 in. i.d. crimped to allow of appropriate MS vacuum pressures. The MS transfer line is torr using the restrictor. maintained at a pressure of 1.5 X The tee and restrictor are maintained at an average temperature of 190 "C in an oven mounted on the GC. The IR and MS transfer lines are heated to 205 "C and 215 "C, respectively, by enclosing them in in. stainless steel tubing wrapped with heating tape. The FTMS employed a 3.0-T magnet and was equipped with a 7.62 X 2.54 X 2.54 cm3 trapped ion cell. The vacuum can temperature was kept at approximately 75 "C to maintain a relatively clean spectral background. Background pressure for torr while methane reagent the discrete E1 runs was 1.5 X gas pressures for the discrete CI and integrated EI-CI runs were 3.5 x io-' torr. The gold-coated Pyrex IR light pipe with dimensions of 15 cm X 1 mm was heated to 205 "C. A narrow range MCT detector (4000-750 cm-') with a D* equal to 42.5 X lo9 was used. A repetitive scan rate of 10 scans/s was achieved with the Nicolet 60SX because of its substantially higher duty cycle than the previously used Nicolet 7199 spectrometer. Sample and GC Conditions. Approximately equal volumes of the 17 components listed in Table I made up the synthetic mixture. Sample volumes of 0.4 PL were injected with a split ratio
of 1O:l onto the column. Assuming the split ratios determined were correct, this corresponds to an average of 2.3 pg and 12 ng of each component introduced to the IR and MS, respectively, The injector temperature was 200 "C. The GC column was programmed to 45 "C for 5 min after injection followed by temperature ramps of 4.0 "C/min to 85 "C and then 15.0 "C/min to 200 "C. Helium carrier gas flow was 2.6 mL/min at 45 "C. Total run time was held to 25 min so that the IR and MS data for a single experiment could be stored on single 2.5-Mbyte disk cartridges with maximum GC resolution. Spectral Parameters. Mass Spectrometer. For the discrete experiment in E1 mode, a 800-PA, 90 eV (nominal) electron beam was used. The beam duration was 3.0 ms with the trap plates set at 1.0 V. Conditions were chosen to obtain at least unit mass resolution at the highest mass measured. A data file containing 325 signal averaged scans was stored on disk every 3.1 s. Each transient contained 4096 points with a low mass cutoff of 35 amu. A real time GC/MS reconstruction consisting of a 1K FFT integrated over the mass range 35 to 200 amu was displayed directly on the system color raster display. For the discrete experiment in CI mode a 500-pA,9O-eV electron beams was used. The beam duration was again 3.0 ms but a delay of 150 ms was added after the electron beam to allow time for the chemical ionization process to occur. Spectral resolution, while somewhat degraded at the higher CI pressures, was still in excess of that required for unit mass resolution. A data file containing 17 signal-averaged scans was stored every 3.0 s. To perform the integrated EI-CI experiment only a minor change in the GC/MS software was required. A delay of 150 ms was alternately added to the pulse sequence when CI spectra were to be collected. The E1 and CI spectra were stored alternately torr were on the dmk. Methane reagent gas pressures of 3.5 X maintained throughout the course of the GC run. An 800-~A, 90-eV electron beam with a beam duration of 3.0 ms was used for both E1 and CI spectra. Data files for the E1 spectra contained 325 coadded scans while CI spectral files contained 18 coadded scans. Both E1 and CI spectra were stored with time resolutions of 3.1 s. Because the GC conditions remained the same for both discrete and integrated experiments, only half as many E1 and CI spectra were collected for the integrated experiment compared to the discrete experiment. The FTIR spectrometer collected 4096-point interferograms which produced 4 cm-' spectra over the range 750-4000 cm-'. Each data file contained 32 coadded scans which were stored every 3.6 s. Real time monitoring of the GC/IR run was possible by integrating over selected windows a 2K transform of the data used during the course of the experiment. Data Processing. Figure 1 is a flow chart of the general procedure for data analysis. Following data collection the three types of data are processed into a usable format. The IR data are first apodized with a cosine function and then Fourier transformed (8192 poinb),phase corrected, ratioed to background spectra, and converted to 4-cm-l absorption spectra. Spectral files were prepared for library searching as previously reported (2). With Nicolet-developed software, the SD (SD is the abbreviation for least squares of derivative spectra and is explained in detail in ref 9) metric (9) was used to search the 3300-spectra EPA vapor-phase IR library. The top 10 library matches for each peak were stored in a file on disk. With no commercial Nicolet 1280 software available for the processing of the GC/MS data, an intensive effort was made to produce a complete software package for that purpose. With this new software the data were first compressed to a form amenable to searching a MS library. To do this the data were transformed and peaks with mass intensities above a preselected threshold were extracted and stored in a new data file. This compression reduced the size of the raw data to less than 1% of the original size while retaining essentially all useful information. A GC/MS reconstruction was then obtained by integration over each compressed mass spectrum. GC peaks above a set threshold were then chosen and after automatic background subtraction of the valleys before the peaks, the mass spectral data for each of the 17 peaks were then stored with a format to allow search of the MS library. The 32 000 EPA/NIH mass spectral library was used for the searches. The search programs written were a modified version of the Biemann algorithm (10). This method reduces search time
ANALYTICAL CHEMISTRY. VOL. 5 6 , NO. 7.
JUNE
1984
* 1165
Fbwe 3. A threedimensional reconstruction of the GC/IR data lor the 17-component mixture. Compounds are numbered in order by elution
times
by the use of several search prefilters which allow only the most probable library spectra to be subjected to a poinbhy-point search. The prefdters originally suggested had to be relaxed and modified considerably to meet the requirements of the GC/FTMS spectra. The changes in the Biemann search were derived empirically from analysis of a range of GC/MS experiments with various compounds at different concentration levels. An algorithm was obtained which would yield the hest GC/FTMS search results in the shortest time. Details of the modifications will be presented in a more detailed description of the GC/IR/MS software in a future publication. The modified algorithm was generally successful when applied to the 17-component GC/FTMS data, and a file containing the top 20 MS search results for each compound was created. The CI-MS data were first processed by using the GC/MS software in a manner analogous to the E1 data. An algorithm was then employed to select the most likely molecular ion for each spectrum. Beginning with the highest mass, the intensity of each mass peak was examined until a peak with intensity above 2 % was found. All peaks above this mass and any peaks within a 2 m u range below it were included in a file of possible molecular ions. The 2% threshold was set so that small background peaks would not be chosen instead of the actual molecular ion. The 2 m u mass range was required to include a range of possible molecular ions from halogenated compounds and other pseudomolecular ions Following the matchup of IR and MS data files for the peaks by use of elution time data, the search results and molecular ion information were subjected to a two-step compound identification process. The registry numhers for the top 10 IR and top 20 MS search results for each component were compared. The best registry number match (as determined by the smallest product from the multiplication of IR and MS search positions) was assumed to provide the correct identity of the unknown. If no match between IR and MS search results was obtained, then the top IR search results were compared with CI data to provide compound identification by a match of molecular ion information. To do this an algorithm was developed to predict the most likely molecular ion from methane CI for many compounds in the 200000 EPA connection table data base. (The principles and potential applications of connection tables are found in ref 11.) The molecular ion algorithm first determines the molecular weight for a compound. The compound type is then ascertained and the molecular ion is chosen. For example, for acetone, a molecular weight of 58 would be calculated and the compound would be classified as a ketone. Because methane CI generally produces an (M + 1) ion for carbonyls, the predicted molecular ion would be 59. Hexane, with a molecular weight of 86, would be classified as a saturated hydrocarbon with a pseudomolecular ion at (M + 1) or 85. The program was developed specifically for methane CI and was applied to a wide number of chemical classed including alcohols, acids, and halogenated and aromatic functionalities. The rules for predicting molecular ions were based empirically on methane CI experiments on a number of compounds. When used as a means of compound identification, the molecular ion algorithm was applied to the top IR search results. The predicted molecular ion for each IR search result was com-
INFRARED
T R = 36r.c
I'
DISCRETE CI T.R.=3 I s m
I
Reconstruct'ons 01 the 17-component miXture from 00th nlegrated and discrete GCIIRIMS experiments The t me resoiution for each reconstruction s incl.oed
Flgure 4.
pared to t h r prohahle molecular inn- irom thr corrcqnmding VI-MS file. A mavh of rnole~:darion values olierrd the alrrrnatiw means fur compound identilicarim.
RESULTS A N D n l S C U S S l O N The GC reronstructions lor buth the inte$zrnted and discrete CC IR. MS experiment5 with the I ? - n m p i m m t mixture are presented in Figures 3 and 1. Finire 3 i i n three-dimenwnal plot cd the FT 1R data u,hich demonstrates thr wralth of chemical information availuhle iwrn a multidimensional experiment. Peak numhers tor i w h cumponetit are inrluded on the plot. Integration of the individual ahsorhance spectra produces the GC IR reconstruction in Figure 4% morr cIrarIs illustrating the chrornatographir resolution uf the mixture. Figure 4b-e shows the mass inrensity reconitructimi t d the El and CI CC MS data for both the integrated and discrete experiments. As expected. these reronstrtirtioni prrsmt in-
ANALYTICAL CHEMISTRY, VOL. 56, NO. 7, JUNE 1984
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Table 11. Comparison of Molecular and Pseudomolecular Ions for E1 and CI Data from the Integrated and\ Discrete GC/IR/MS Experiments integrated expt peak no. 1 2
3 4 5 6
7 8 9 10 11 12 13 14 15 16 17
compound type aliphatic ester aliphatic ketone aliphatic ester alkane aliphatic ester halogenated alkane cyclic alkane aliphatic ketone alkane unsat. halogen aliphatic ester sub. aromatic sub. aromatic sub. aromatic halogenated aromatic aromatic ketone aromatic ether
mol wt 60 55 74
86 88 92 84 86 100
130 102 92 106 106 156 120 142
E1 data MI
%
M+ M+ M+ Mt M+ M - 35 M+ M+ M+ Mt M+ M+ M+ Mt M+ M+ M+
100 22 15 15 3 100 77 15 18 100 8 53 34 46 80 32 100
formation very similar to that for the GC/IR data. Although the actual chromatographic resolution is sufficient to adequately resolve all components, the time response of both IR and MS detectors is not instantaneous; the several seconds between data files stored produces an apparent GC resolution which has been degraded. This is an important consideration for the integrated GC/IR/MS experiment because while both the GC/IR and discrete GC/MS data had a time resolution of about 3 s, the time resolution of the integrated experiment was necessarily only half as good. It should be emphasized that these time resolution parameters were simply a function of the data storage capability of our particular system and not due to some inherent limitation of the technique (see below). As Figure 4d,e demonstrates, the peak shapes for the integrated reconstructions are broader and less well-defined than for those from the discrete experiment depicted in Figure 4b,c. It is fortuitous that for the 17-component mixture, data files were collected in the integrated experiment so that all peaks, including the closely spaced peaks 9 and 10, were resolved. Other integrated experiments produced reconstructions which would not completely resolve those peaks. The apparent chromatographic resolution in the GC/IR/ MS experiment is closely related to two other parameters, spectral signal to noise ratio (SIN) and disk storage capacity. In general, chromatographic resolution is improved as SIN decreases because signal averaging, which increases SIN, also increases the time per data file. However, even when SIN is adequate to allow very fast data storage, disk storage capacity often becomes the limiting factor in chromatographic resolution, For example, in our experiments it is convenient to store a single GC/MS or GC/IR run on a 2.5-Mbyteplatter. Since typical spectra require a 4K transient, only 400 to 500 data files can possibly be stored on a platter. This constraint requires that for the 25-min separation in this experiment, the best possible time resolution is about 3 s. The problem of degraded GC resolution for these multidimensional techniques obviously can be solved by two approaches. Large mass storage devices now available would ease the restrictions on the amount of data collected; future GC/IR/MS experiments in our laboratory will employ Winchester-type drives with at least 80-Mbyte capacities. Detector sensitivity must also be improved so that fewer signal averaged scans are required for adequate detection limits. As an example, the Nicolet 60 SX with its rapid scan mode allows a 10-fold increase in sampling rate over previous GC/IR/MS
CI data MI % M+ 1 Mt 1 M + 1 M-1 M + l M - 35 M- 1 M + 1 Mt M+ 2 M + l M+ 1 M + l M t 1 M+ 3 Mt 1 M+ 1
100 100 99 73 55 100 100 87 7 100 48 100 83 100 100 100 100
discrete expt E1 data CI data MI Mt Mt Mt
M+ M - 35 Mt M+ Mt Mt M+ Mt Mt Mt Mt M+ M+
%
MI
%
100 23 13 14
M+ 1 M+ 1 M+ 1 M- 1 M+ 1 M-35 M- 1 M+ 1 Mt M+ 2 M+ 1 Mt 1 M t 1 M+ 1 M+ 3 Mt 1 M+ 1
100 100 100 67 48 100 100 89 7 100 100 100 63 102 100 100 100
100 77
15 18 100
7 59 32 43 92 35 100
experiments using a Nicolet 7199 FTIR. Since SIN is increased approximately as the square root of the increase in sampling rate, a 3-fold increase in SIN would be expected for the same time resolution with the new IR. Preliminary results also suggest that improvements in the GC/MS interface will offer subnanogram detection limits for the FTMS-1000 mass spectrometer. With the addition of mass storage devices and this improved IR and MS sensitivity, acquisition times per file below 1s will be easily attainable in future experiments. Because the E1 and CI experiments are being performed essentially simultaneously in the integrated mode, it is likely that both E1 and CI spectra could become “mixed”. To avoid this, conditions had to be chosen carefully to avoid any crossover in the spectra which might degrade the results. An example of the possible combination was observed when the total electron beam and delay time for the E1 experiment exceeded 3 ms. Because of the methane reagent gas present, the E1 spectra acquire the character of CI spectra at greater experiment times with a corresponding decrease in the quality of MS search results. As the mass spectra for the four components in Figure 5 demonstrate, however, conditions were found which made the integrated experiment feasible. The four componentshexane, ethyl acetate, trichloroethylene, and p-chloroanisole-represent the range of compounds tested. Note that both the integrated and discrete E1 spectra (parts A and B) and the integrated and discrete CI spectra (parts C and D) are essentially identical. In addition, with the CI conditions chosen for both integrated and discrete experiments, a much more prominent molecular or peeudomolecular ion was obtained. Table I1 demonstrates more completely the improvement in intensity of the molecular ion for the CI case. As expected for methane CI, aromatic and carbonyl compounds yielded very strong (M - 1) ions. Peak 6, 1-chlorobutane, showed strong loss of C1 to give an (M - 35) peak for both E1 and CI spectra. Only peak 9, hexane, did not act as expected; no (M - 1)ion was observed with CI and in fact the M+ ion was far stronger for the E1 spectrum. It is most important to recognize however that the integrated and discrete experiments yield almost identical data. Tables 111and IV present the results of the data analysis for the 17-componentmixture in discrete and integrated mode, respectively. The IR searches yielded the correct result for 16 of the 17 Components. Only 1-chlorobutane,which was not in the infrared library, did not give a correct match. The
ANALYTICAL CHEMISTRY, VOL. 56, NO. 7, JUNE 1984
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Table 111. Analysis of Synthetic Mixture Using the Discrete GC /IR /MS Experiment peak no. 1 2
3 4 5 6 7 8 9 10 11 12 13 14 15 16 17
IR MS search search resulta resulta 1 1 2 1 1 1 1 1
compd identification mol wt fromCI IR/MS IR/CI none 60 X 58 X 74 X 86 X 88 X X
1 1 1 1 1 1 1 1 1 1 1
16 1 1 1
4 1 4 1 1
84 86 100 138 102 92 106 106 156 120 142
X X X X
lliL
10.00
SO.00
IO 00
110.00
140 00
10 00
SO 00
IO 00
110 00
I 4 0 00
X X X X X
le
X X
I
10
L L L l J L
10.00
Search result position from comparison of the known compound with the IR or MS library spectrum (Le., position 1is best match). a
I
SQ.00
80.00
110.00
I+O.OO
1000
SO00
80.00
110.00
14000
Table IV. Analysis of Synthetic Mixture Using Integrated GC/IR/MS Experiments oeak no, 1 2 3
4
IR MS search search resulta resulta 1 1 1 1 1
1 1 1 1
compd identification mol wt fromCI IR/MS IR/CI none
60 58 74 86 88
X X
A tJ l d L m IO 00
10 00
80 00
I10 00
140 PO
10 00
IO
00
80 00
110 00
110 00
X X X
5 6 X 7 1 14 84 X 8 1 1 86 X 9 1 1 100 X 1 13 8 X 10 1 102 X 11 1 4 92 X 12 1 1 106 X 13 1 14 1 4 106 X 15 1 1 156 X 16 1 120 X 17 1 1 142 X a Search result position from comparison of the known compound with the IR or MS library spectrum (Le., position 1 is best match).
molecular weight information from CI data for both experiments was correct in 16 of 17 cases, with heptane the exception. (1-Chlorobutane which produced only the (M - 35) peak would still have been identified by using the molecular ion algorithm if 1-chlorobutane had been in the IR library and had been a top search result.) Mass spectral search results, while essentially the same for both experiments, are actually better for the integrated case. Ten compounds were correctly identified 8s the top hit for the integrated experiment compared to only eight top matches for the discrete case. Of the 17 compounds, 4 were consistently not among the top 20 search results. For the cases of methyl formate and acetophenone the probable explanation is that a lower mass cutoff of 35 amu was used, effectively eliminating the majority of MS peaks for those compounds. The high cutoff was chosen so that the intense C2Hs+peak a t mlz 29 from the methane would not be included as data in the mass spectra collected. The mass spectral searches for l-chlorobutane while unsuccessful for the data shown actually pro-
Figure 5. GC/FT-MS spectra of hexane, ethyl acetate, trichloroethylene, and p-chloroanisole. For each compound spectrum A is the integrated EI, spectrum B is the discrete EI, spectrum C is integrated CI, and spectrum D is the discrete CI.
Table V. Comparison of Integrated and Discrete Results from Analysis of 17-Component Mixture GC/IR/MS method no CI discrete EI-CI expts integrated EI-CI expt
IR/MS IR/CI identifi- identification cation
total
12 12
4
12 16
13
3
16
duced correct matches for cases where the E1 ionization was less energetic. Ethyl propionate yielded excellent mass spectra which matched very well with the hard copy library spectrum but did not give a top 20 MS search result because of an error in the library spectrum stored on the computer. As Table V suggests, the integrated experiment was as successful as the discrete experiment in the mixture analysis, with the importance of the CI data also demonstrated. For those cases where the problems with the MS search listed
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Table VI. Experiment and Processing Time for Integrated GC/IR/MS Experiment procedure integrated GC/IR/MS run MS and IR Fourier transforms MS search IR search search comparison molecular ion algorithm total time
computers used
time, min
two Nicolet 1280’s two Nicolet 1280’s
60
Vax 11/750 Nicolet 1280 Nicolet 1280 VU 11/750Nicolet 1280
25 30
5
20 140
above did not allow compound identification by IR/MS registry number matches, the CI data allowed correct compound identification from IR/CI molecular ion matches for three of four compounds. Although the improvement in compound identification provided by increased information content from the integrated experiment is obvious, the limitations imposed should be recognized. Sensitivity for both E1 and CI data is necessarily halved and the E1 spectral resolution is also degraded by the higher pressures required for the CI experiment. The loss of MS sensitivity is not significant, however, because the GC/ IR/MS experiment will always be limited by the much poorer IR sensitivity. Compared with the GC/MS experiment, much larger quantities must be injected on the column for a GC/ IR/MS experiment; if the requirements for IR detection are met a sufficient amount of material will be available for the EI-CI experiment. The problem of degraded mass spectral resolution can be solved through the use of a pulsed valve which will eliminate high pressures for both the E1 and CI scans (12). The value of the GC/IR/MS technique with its multidimensional data must be emphasized. While GC/IR would also have correctly identified 16 of 17 components there would be no assurances as to absolute compound identification. The three complementary types of data from the integrated GC/IR/MS experiment offer a cross-check of the results which would be impossible by any simple spectroscopic technique. An inadequate library, poor chromatographic resolution, or poor spectral SIN are eliminated as sources of error in compound identification; in the one case where a compound, 1-chlorobutane, was not in the library, the GC/IR/MS technique did not choose an incorrect result as would have been the case with the single GC/IR or GC/MS experiment. As the flow chart in Figure 1suggests, the data processing and analysis time for the GC/IR/MS experiment is considerable and could only be feasible if under complete computer control. As detailed in the experimental section, the software for automation of the analysis has been written and was used in the 17-component mixture work. Complete analysis times
including data collection for the integrated experiment were less than 3 h as illustrated in Table VI. With this software the routine use of the experiment became far more plausible. A further decrease in processing time would be achievable by implementing a hardware FFT for both FTIR and FTMS spectrometers. Fourier transformation of the spectral data, the most time consuming of the postrun data processing, could then be done in real time with the further advantage that real time MS peak picking would drastically reduce storage requirements for the GC/FTMS. In the future the software will be expanded beyond the point where only simple comparisons of library searches and molecular weight information are made. Even in those cases where no certain compound identification is possible, as with the 1-chlorobutane, a wealth of chemical information is still available. For example, the IR and MS search results, in addition to the individual spectra, offer a great deal of information which with human interpretation, provides ultimate compound identification. The computer could be used to provide, if not the actual interpretation, at least the results of spectral peak picking, and correlations of search data which would make the final interpretation of the data far simpler. It is clear that the methods investigated here show great promise for unknown mixture analysis, although applications to unknowns have yet to be demonstrated.
LITERATURE CITED (1) Wilkins, C. L.; Giss, G. N.; Whlte, R. L.; Brissey, G. M.; Onyiriuka, E. C. Anal. Chem. 1982, 5 4 , 2260-2264. (2) Wilkins, C. L.; Giss, G. N.; Brissey, G. M.; Steiner, S. Anal. Chem. 1981, 53, 113-117. (3) Crawford, R. W.; Hirschfeld, J.; Sanborn, R. H.; Wang, C. M. Anal. Chem. 1982, 5 4 , 817-820. (4) Laude, D.; Brissey, 0.; Giss, G.; Wilklns, C. L. 1983 Pacific Conference on Chemlstry and Spectroscopy, Oct 28, 1983; Paper No. 357. (5) Wilkins, C. L.; Giss. G. N.; Brissey, G. M.; Ijames, C.; Steiner, S. 1983 Pacific Conference on Chemlstry and Spectroscopy, Oct 27, 1983; Paper No. 267. (6) Shafer, K. H.; Fayes, T. L.; Brasch, J. W.; Jakobsen, R. J. Anal. Chem. 1984, 56, 237-240. (7) Arsenault, G. P.; Dolhun, J. J.; Biemann, K. Anal. Chem. 1971, 43, 1720-1 722. (8) Taylor, K. T.; Chapman, C. J.; Compson, K. R. “Alternate Scan CUE1 Mass Spectrometry”; Kratos Scientlflc Instruments: Manchester, Kratos Data Sheet A193-0279. (9) Lowry, S. R.; Huppler, D. S. Anal. Chem. 1981, 53, 889-893. (IO) Hertz, H. S.; Hites, R. A,; Biemann, K. Anal. Chem. 1971, 43, 681-691. (11) Wlpke, W. T., Heller, S. R., Feldmann, R. J., Hyde, Eds. “Computer Representation and Manipulation of Chemical Information”; Wiley-Interscience: New York, 1974, (12) Sack, T. M.; Gross, M. L. Anal. Chem. 1953, 55, 2419-2421.
RECEIVED for review December 27,1983. Accepted March 5, 1984. This work was supported by the National Science Foundation under Grant CHE-82-08073. Purchase of the FTMS-1000 mass spectrometer was supported under a Department instrumentation grant, CHE-82-17610,which is also gratefully acknowledged. Partial support was also provided by an NIH Biomedical Research support grant.
