ANALYTICAL CHEMISTRY, VOL. 51, NO. 12, OCTOBER 1979
technique is one of convenience since the fluorescence lifetime instrumentation can be used. This allows the cancellation of errors due to geometry or quenching in the calculation of the natural lifetime, T ~ by , T / @ Q = T ~ .The method does demonstrate that accurate quantum yields can be measured by using pulsed source excitation in the single photon counting mode. The method as presented here could benefit from certain instrumental improvements, such as monitoring the lamp intensity or a simultaneous measurement of absorbance and fluorescence. This would provide further precision and convenience by eliminating the manual change from absorbance to the fluorescence configuration. This could be accomplished in a manner similar to that of Holland et al. ( 5 ) . This technique holds promise for the performance of routine quantum yield measurements and easy automation because of the intrinsic digital form of the data.
ACKNOWLEDGMENT The authors gratefully acknowledgethe assistance of Arthur Ritter I11 who provided the frequency response data. The use of the Perkin-Elmer fluorometer, courtesy of Omar Khalil of Rutgers University, New Brunswick, N.J., is also acknowledged. LITERATURE CITED (1) C. A. Parker, "Photoluminescence of Solutions", Elsevier. Amsterdam, 1968.
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G. G. Guilbault, "Practical Fluorescence", Marcel Dekker, New York, 1973. J. N. Demas and G. A. Crosby, J. Phys. Chem.. 75, 991 (1971). J. B. Birks in "standards in Spectrophotometry and Luminescence Measurements", National Bureau of Standards, Washington, D.C., 1977. J. F. Holland, R. E. Teets, and A. Timmick, Anal. Chem., 45, 145 (1973). W. H. Meihuish, J . Phys. Chem., 85, 229 (1961). A. Britten, J. Archer-Hall, and G. Lockwood, Analyst (London), 103, 928 (1978). W. R. Ware, Rev. Sci. Instrum., 48, 320 (1977). J. Yguerabide, Methods Enzymol., 26, 498 (1972). M. L. Franklin, G. W i , and H. V. Malmstadt, Anal. Chem..41, 2 (1969). R. E. Curry, H. L. Pardue, G. E. Mieiing, and R. E. Santini, Clin. Chem., 19, 1259 (1973). R. J. Kelly and W. B. Dandliker, Anal. Chem., 48, 846 (1976). P. B. Coates, J. Phys. E, 5, 148 (1971). R. Schuyler and I. Isenberg, Rev. Sci. Instrum., 42, 813 (1971). R. R. Sokal and F. J. Rohlf, "Biometry", W. H. Freeman, San Francisco, Calif., 1969, Chapter 5. L. J. C. Love and L. A. Shaver, Anal. Chem., 48, 364A (1976). L. J. C. Love, L. M. Upton. and A. W. RMer 111, Anal. Chem., 50, 2059 ( 1978). J. B. Birks and I.H. Munro, Prog. React. Kinet., 4, 239 (1967). I.B. Bedman, "Patandbook of Fluorescence Spe&a of Aromatic Molecules", Academic Press, New York, 1971. G. A. Morton, Appl. Opt., 7, 1 (1968). R. R. Alfano and N. Ockman, J . Opt. SOC.Am., 58, 90 (1968)
RECEIVED for review March 30,1979. Accepted July 20,1979. The financial assistance of the Analytical Division of the American Chemical Society through an award of a 1976-1977 full year fellowship to L.M.U. is gratefully acknowledged. Research support provided by the State of New Jersey under provisions of the Independent Colleges and Universities Utilization Act is also gratefully acknowledged.
Matching of Mixture Mass Spectra by Subtraction of Reference Spectra Barbara L. Atwater (Fell), Rengachari Venkataraghavan,' and Fred W. McLafferty" Department of Chemistry, Cornell University, Ithaca, New York 14853
A "spectrum-stripping"technique allows Improved identlflcation of minor mixture components in matching unknown mass spectra against a large reference file using the "Probabllity Based Matchlng" (PBM) system. The poor quantitative agreement expected between spectra of the same compound run under different condttions can be compensated by the hlgh information content of the mass values. Such spectrum subtraction Is complementary to the "reverse-search" feature of PBM, being especially valuable for identlfylng component spectra containing a number of peaks common to other components of the sample.
The increased use of the gas chromatograph/mass spectrometer (GC/MS) for the analysis of complex mixtures, such as those from pollutants, body fluids, and insect pheromones ( I ) , has greatly enhanced the need for computer identification of component spectra (2-10). For such mixtures, complete GC resolution is difficult, resulting in individual mass spectra formed from two or more components. The "reverse-search'' procedure has been found to be of value for such cases ( 5 , 6 , 8);a "Probability Based Matching" (PBM) system (8) of this Present address, Lederle Laboratories, American Cyanamid, Pearl River. N.Y. 0003-2700/79/0351-1945$01.00/0
type designed for a large reference file of spectra from diverse sources (11) was shown to be substantially more effective than forward-searching in identifications from mixture spectra. However, peaks in the mixture spectrum which contain substantial contributions from two components cannot be used with confidence for the identification of either, making identification less reliable for components with overlapping spectra. "Spectrum-stripping" is commonly used for the analysis of mixtures, and has been proposed by Hites and Biemann (3) for matching mixture mass spectra. In the usual application of the stripping technique, however, it is possible to have the y axis (intensities) as well as x axis (wavelength, mass, etc.) values of the reference and unknown spectra in close quantitative agreement. This is often not the case for spectra recorded on different mass spectrometers (11), for which abundances often vary by more than 50%. This paper describes an addition to the PBM algorithm (8) which uses reference spectrum subtraction to improve performance in the identification of minor components of mixture spectra. Computer-automated GC/MS systems can make it possible to obtain a number of mass spectra during the elution of an unresolved multicomponent GC peak. Algorithms have been reported (12-14) to extract the spectrum of each component by cross-comparison of the measured spectra. From the impressive results reported, it would appear that such an algorithm should be used routinely for complex mixtures to 0 1979 American Chemical Society
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ANALYTICAL CHEMISTRY, VOL. 51, NO. 12, OCTOBER 1979
reduce spectral overlap. However, the success of this system in separating spectra characteristic of individual components depends on the degree t o which the chromatographic separation has changed the relative abundance of components in adjacent spectra. Thus it is complementary to the method described here, which could still be useful for spectra produced by the cross-comparison program which represent more than one component.
EXPERIMENTAL Details of the PBM program and DEC PDP-11/45 computer used have been described previously (5,8). The data base (11) searched contains 41 429 different reference spectra of 32 403 different compounds. The Subtraction Algorithm. A subtraction routine has been added t o the end of the PBM program which is automatically entered upon completion of a PBM search. In this routine, the complete reference spectrum retrieved as the best match (highest “K” value) (8) is subtracted from the complete spectrum of the unknown; alternatively, any of the other retrieved spectra can be subtracted on user command. The reference spectrum is that of a pure compound; to subtract it from the mixture spectrum, it is necessary to estimate the proportion of the reference compound in the unknown. This estimate utilizes the pJ values (8) of the masses j found in the condensed reference mass spectrum, where pJ is the ratio of the abundance (on the basis that the largest peak has a value of 100%) of the jth peak in the unknown to its abundance in the reference spectrum. For all the pl values to be the same, it is necessary that spectra of the reference and unknown be identical on a relative basis (there usually are substantial abundance differences) and that no other component spectra of the unknown contribute t o the j peak values. Because the presence of other components can only increase the p, values, the fourth lowest value (of 15 values), rather than the average, is used as the estimated component percentage. (This value was found to be the best in extensive tests.) For the subtraction, the complete spectrum (not the condensed (8) spectrum) of the selected reference is read from storage and normalized so that its largest peak and that of the unknown are in the same abundance ratio as the fourth lowest pJ value (peaks at m / z 18,28, and 32 are ignored). The resulting reference abundances are subtracted mass by mass from the unknown spectrum with differences less than zero set to zero. In deciding whether to match the resulting residual spectrum with PBM, the user should first consider the values reported by PBM for the proportion of the spectrum accounted for by the indicated component and by contaminants. Examination of the residual peaks can also be helpful; in practice it has been found sufficient to restrict those displayed according to the following criteria: the mass of the peak must be as great as the lowest mass in the reference spectrum, and its abundance must be both 21% and 1 2 X as large as the reference abundance subtracted. (The latter helps to ensure that the residual peak truly arises from another component and not from abundance variations due to different instrumental conditions.) Only 15 residual peaks with the highest U + A values (8)are displayed. The user can decide instead to rerun a residual spectrum prepared by subtraction of another of the compounds retrieved by PBM; the fourth lowest pJ value found for each of these is also saved during the first PBM run to make this possible. Test Set of Unknown Spectra. Both computer-generated mixture spectra and actual mixture spectra were used for testing the program. The former were derived by computer summing of reference spectra (8);these included a 50/50 mixture of 1heptanol and n-heptane, a 90jlO mixture of benzaldehyde and benzyl alcohol, and a 40/40/20 mixture of methyl hexanoate (molecular weight (MW) 130, C7HI4O2),methyl %hydroxyiminopropionate (MW 117, C4H7N03), and 6-methylaminopurine (MW 149, C6H7N5).The first two mixtures represent cases in which there is considerable overlap of the component mass spectra. The components of the third artificial mixture were chosen at random. More than one spectrum of each chosen compound was present in the reference file so that the algorithm could be tested with spectra other than those used to generate the unknown mixture spectra.
-
Three spectra of actual mixtures were used. The first, containing bis(2-chloroethyl) ether and C3-benzene(C9HI2)isomers as major components, came from a GC/MS analysis of Philadelphia drinking water by Brenner, Silver, and Suffet (15). Their application of PBM to this unknown had identified the first component as choices 1, 2, 4, and 5 of the top 5 matches, while the Biemann system ( 4 ) had identified the second component as choices 3,4, and 5 of the top 10 matches; neither system identified both major components. The other two actual spectra were taken from a GC/MS analysis of a synthetic mixture of 69 compounds commonly found as stream pollutants. These two spectra represented unresolved mixtures of DDE [ l,l-dichloro-2,2-bis(pchlorophenyl)ethylene] and pyrene, and of fluoranthene and diethyl phthalate, respectively. Implementation and Availability. The program of approximately 300 statements was written in FORTRAN IV and run on the Cornel1 University IBM-370/168 computer as part of the PBM/STIRS system (16). It is available to outside users through the TYMNET and TELENET computer network systems (Office of Computer Services, Cornell University, Ithaca, New York 14853).
RESULTS AND DISCUSSION Computer-Generated Mixture Spectra. For the artificial 40/40/20 mixture, the first PBM run identified only methyl 2-hydroxyiminopropionate (choices 1,2,4, and 5 of “IC’values 103, 103,67, and 64) and 6-methylaminopurine (choice 3, K = 102). The methyl hexanoate was not retrieved because >70% of the total abundance of the 10 largest peaks of the unknown spectrum are not present in the reference (the choice of this 70% limit has been discussed) (8). Automatic subtraction of the reference spectrum of the first compound from the mixture and rerunning of the residual with PBM gave 6-methylaminopurine ( K = 102) and methyl hexanoate ( K = 88) as the first two choices. After subtraction of the reference spectrum of 6-methylaminopurine from the original mixture spectrum, PBM rerunning of this residual gave methyl 2hydroxyiminopropionate as choices 1 , 2 , 4 , and 5 ( K = 96,96, 60, and 58) and methyl hexanoate as choices 3 and 9 (K = 69 and 40). The K (and AK) values for the latter are poorer than the values obtained when methyl 2-hydroxyiminopropionate was subtracted, as a much larger number of the peaks of the latter overlap those of the methyl hexanoate. This causes the total abundance of some methyl hexanoate peaks in the mixture spectrum to fall outside the allowed “window” tolerances (8) so their presence is not credited toward the K value for this match. PBM examination of the 90/ 10 benzaldehyde/benzyl alcohol mixture found benzaldehyde as the top five choices ( K = 101,101,96,91,and M),but did not retrieve benzyl alcohol ( K < 33). Subtraction of a reference spectrum of benzaldehyde from the mixture spectrum and rerunning by PBM gave only benzyl alcohol as the eleventh match ( K = 42); four of the first five matches gave cresols, isomers of benzyl alcohol, and all matches had a t least one flagged peak (8). However, using the lowest p J value (94%) instead of the fourth lowest (99%) to calculate the proportion of the reference spectrum subtracted gave benzyl alcohol as the first five PBM matches ( K = 104,102,95,88, and 79). Raising p, to 137% gave no PBM matches of K > 20. This sensitivity to the p, value used arises from the large proportion (90%)of the subtracted component and the high degree of overlap of the spectra (12 of the 15 benzyl alcohol peaks used in matching are also present in the benzaldehyde spectrum). Because the minor component concentration is only l o % , increasing p, by 5% (from 94% to 99%) causes a dramatic abundance reduction of any residual spectrum peak which is of substantial importance in both reference spectra; for example, for p, = 99%, m / z 106 in the residual spectrum for this mixture is a negative value. In this case the subtracted reference spectrum was actually that used in calculating the unknown mixture spectrum,
ANALYTICAL CHEMISTRY, VOL. 51, NO. 12, OCTOBER 1979
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Table I. PBM Results from Suffet Spectrum and Its Residuals (Figure 1) Original Spectrum confidence values compound bis( 2-chloroethyl) ether 2-( 2-chloroethoxy)ethanol bis( 2-chloroethyl) ether bis( 2-chloroethyl) ether
%
'70
Ka
AK
contamination
component
62** 53*** 51t 41 T
37 46 45
24 26
53 64
29
:'i3
50
30
38
11 10 9 10
34 34 34 43 36
First Residual Spectrum isopropylbenzene isopropylbenzene isoprop ylbenzene isopropylbenzene 1-methyl-2-ethylbenzene
73t 72+
72+ 71+ 61**+
20
'1 7
91
83 '7 2 '14
Residual Spectrum of Residual methyl 2-keto-3-methylvalerate methyl 2-ketoisocaproate 4-methyl-l,2-epoxypentane
vinyl 2,2-dimethylpentanoate 2,2,3,3-tetramethylhexane a
54** 47** 39*** 32** 32***
28 31 46 46 54
50
!j 2
50
62 43 40 43
62 62 66
The number of asterisks indicates the number of flagged peaks; plus indicates that the molecular ion was matched.
making the lowest p, value more accurate for the subtraction calculation, as all uncontaminated peaks arising from this component in the unknown spectrum will have the same p, value. This would not be true for a real mixture spectrum matched against reference spectra measured under different conditions, however (vide infra). Ten of the 15 peaks used for PBM retrieval of n-heptane are prominent in the 1-heptanol spectrum. For their 50/50 mixture, the PBM system retrieved 1-heptanol as matches 1, 2, 3, 4, 6, and 11 ( K = 82, 73, 66, 65, 61, and 561, but n-heptane only as matches 7 and 1 2 ( K = 60 and 5 5 ) . The residual spectrum resulting from the subtraction of the 1heptanol reference using either the lowest or fourth lowest p, value gave the same results, retrieving n-heptane as matches 1, 2, 4, and 5 ( K = 86, 85, 84, and 5 2 ) . When p, used to calculate the residuals was increased by 38%, only the first spectrum of the top five retrieved was of n-heptane, and the match was poorer: K = 65 with three flagged peaks (Le., three peaks had to be ignored to obtain the match) (8). Actual Mixture Spectra. Figure 1 contains the normalized spectra of the bis(2-chloroethyl) ether (BCEE)/C3benzene mixture, of the residual after subtracting the reference spectrum of the former using the fourth lowest p,, and of the residual of the residual after further subtraction of the best matching (&-benzene reference. The PBM results for each of these three spectra are shown in Table I. As found by Suffet (15),only BCEE, and not the C3-benzene,was identified by PBM in the original spectrum because the BCEE interference caused >70% of the total abundance of the 10 largest peaks of the unknown spectrum not to be present in any of the (&benzenes reference spectra. After subtraction of the BCEE reference, however, PBM retrieved isomeric C3benzenes as the first 13 matches. Further subtraction of the isopropylbenzene reference spectrum gave the residual of the residual. This spectrum (Figure 1) indicates the presence of one or more additional components; note the ion series m / z 29, 43, 57, 71, and 85. However, when this second residual spectrum was matched by PBM against the data base, a wide variety of compound types were retrieved a t poor confidence levels (Table I). Because the reference spectra subtracted did not agree quantitatively with those due to the mixture components, some residual peaks remain, such as m / e 105, 120, and 142, and the amount subtracted from other peaks will be inaccurate, as found for the 90jlO mixture above. The
Figure 1. Top: Mass spectrum of mixture containing bis(2-chloroethyl) ether (BCEE) and C9H,, isomers (C,-benzenes)from ref. 15. Middle: Residual spectrum after subtracting a reference spectrum of BCEE. Bottom: Residual of residual after further subtraction of reference spectrum of isopropylbenzene
subtractions and renormalizations also will increase the relative noise levels. Thus the algorithm is restricted to only one level of subtraction for PBM searching using reference
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ANALYTICAL CHEMISTRY, VOL. 51, NO. 12, OCTOBER 1979
1
I
Figure 2. Top: Mass spectrum of unresolved GC peak containing l,l-dichlor~2,2-bis(p-chlorophenyl)ethylene (DDE) and pyrene. Bottom: Residual spectrum after subtracting a reference spectrum of DDE
Table 11. PBM Results for the DDE/Pyrene Spectrum from the Pollutant Mixture Original Spectrum confidence values Ka AK
compound l,l-dichloro-2,2bis( p-chlorop henyl )ethylene l,l-dichloro-2,2bis(p-chloropheny1)ethylene 1,l-dichloro-2,2-
%
%
contaminat ion
component
156+
21
39
61
144+
33
39
51
112+
63
26
52
log**+
61
51
73
bis(p-chloropheny1)ethylene
l,l-dichloro-2-(o-chloropheny1)2-(p-~hlorophenyl)ethylene
Residual after Subtraction of DDE Reference Spectrum pyrene pyrene pyrene flu oranth en e fluoranthene a
63***+ 48** *+ 39***+ 35***+ 30***t
43 58
38
99
64
66
58
62 73
54 64
61 91 58 91
The number of asterisks indicates the number of flagged Deaks: Dlus indicates that the molecular ion was matched.
spectra from diverse sources, and identification of more than two overlapping spectra is not attempted. In particular cases, however, the reverse search capability of PBM makes possible the identification of other components with more unique spectra, such as the 40/40/20 mixture discussed above. The spectrum of the DDE/pyrene mixture taken from the GC/MS analyses of the 69-component synthetic mixture is shown in Figure 2 , along with the residual obtained by subtracting the best matching spectrum (DDE). The PBM results (Table 11) show DDE as matches 1, 2 , and 4, and the third and fifth ranked compounds are closely related structures. The second major component, pyrene, was not identified because the DDE spectrum makes significant contributions to most of the mlz values found in the pyrene spectrum. However, PBM matching of the residual spectrum from DDE removal correctly identifies pyrene, finding it as the first three matches (Table 11). The closely similar isomeric spectra of fluoranthene are the fourth and fifth PBM selections. The peaks remaining after the pyrene is subtracted are due mainly to background (which was not removed from
the original spectrum before the PBM identifications) and to peaks from the DDE that were not totally removed during subtraction. The other spectra from the same GC/MS analysis yielded similar results. The minor component, diethyl phthalate, was not identified by PBM despite the presence of a very large m / z 149 peak. Upon removal of the spectrum of the major component, fluoranthene, the first two spectra retrieved for the residual by PBM were of diethyl phthalate, and all of the top 5 matches were phthalates. Applicability. General use of the spectrum subtraction system for a year by a variety of laboratories indicates the above to be typical results. These show the spectrum subtraction to be complementary to reverse search as an aid to the identification of mixture components. The latter does not require identification of another component to be effective, and can match two or more components in one PBM run. On the other hand, spectrum subtraction makes it possible to derive information for identification of a component from peaks which contain contributions of another component, and
ANALYTICAL CHEMISTRY, VOL. 51, NO. 12, OCTOBER 1979
to identify a component whose concentration in the original spectrum was below detection limits. Both of these are complementary to the mathematical extraction of pure component spectra from multiple spectra across an unresolved GC peak (12-14), which in effect improves the chromatographic resolution using data from the multiplicity of unknown spectra of unknown decompositions, rather than from reference spectra. Thus it is recommended that both of these methods be employed in matching mass spectra of unknown samples for which high purity is not proved.
ACKNOWLEDGMENT We thank W. M. Shackelford, Environmental Protection Agency, Athens, Ga., for supplying the mass spectra of the pollutant mixture. LITERATURE CITED (1) Burlingame, A. L.; Shackleton, C. H. L.; Howe, I.; Chizhov, 0. S. Anal. Chem. 1978, 50, 346R. (2) Crawford, L. R.; Morrison, J. D. Anal. Chem. 1968, 4 0 , 1464. (3) Hites, R. A.; Biemann, K . Adv. Mass Specfrom. 1968, 4 , 37. (4) Hertz, H. S.;Hites, R. A.; Biemann. K. Anal. Chem. 1971, 4 3 , 681.
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(5) McLafferty, F. W.; Hertel, R. H.;Villwock, R. D. Org. Mass Spectrom. 1974, 9, 690. (6) Abramson, F. P. Anal. Chem. 1975, 47, 45. (7) Mathews, R. J. Inf. J . Mass Specfrom. Ion Phys. 1975, 77, 217-31. (8) Pesyna, G.M.; Venkataraghavan, R.; Dayringer, H. E.; McLafferty, F. W. Anal. Chem. 1976, 48, 1362. (9) Pesyna, G.M.; McLafferty, F. W. "Determination of Organic Structures by Physical Methods"; Academic Press: New York, 1976, Vol. 6. (IO) Zupan, J.; Penca, M.; Hadzi, D.; Marsel, J Anal. Chem. 1977, 49, 2141. (1 1) Stenhagen,E.; Abrahamsson, S.;McLafferty. F. W. "Registry of Mass Spectral Data", Wlley-Interscience: New York. 1974. (12) Biller, J. E.; Biemann, K. Anal. Left. 1974, 7, 515. (13) Dromey, R. G.;Stefik. M. J.; Rindfleich, T. C.; Duffield, A. M. Anal. Chern.
1976, 4 8 , 1368. (14) Blaisdell, B. E.; Sweeley, C. C., submitted for publication. (15) Brenner, L.; Silver, B.; Suffet, I. J . Environ. Sci. Health, 1978 A 73(2), 149- 166. (16) Venkataraghavan, R.; Dayringer, H. E.; Atwater. B. L.; Pesyna, G. M.; McLafferty, F. W. Adv. Mass Spectrom. 1978, 7, 989-92.
RECEIVED for review January 23, 1979. Accepted June 18, 1979. The authors are grateful to the Environmental Protection Agency for generous support of this research, and to the National Science Foundation for partial funding of the PDP-11/45 computer used.
Gas Chromatographic Determination of Phosphorus-Containing Pesticide Metabolites via Benzylation Christian G. Daughton,' Alasdair M. Cook,' and Martin Alexander* Laboratory of Soil Microbiology, Department of Agrononiy, Cornell University, Ithaca, New York, 14853
Mono- and di-protic alkyl and aryl phosphates, phosphonates, and thio analogues were determined in spiked samples of bacterial growth medium and human urine using a new procedure wlth a detection llmit of less than 2 pmol each. The acids were fully protonated by passing the aqueous samples through BioRad AG 50W-X8 (H') resin and dried thoroughly before refluxing with 3-benzyl-1-p-tolyltriazene in acetone. The benzyl esters that formed partitioned quantitatively into cyclohexane and were determined by gas-liquid chromatography with a flame-photometric detector (phosphorus mode) and a glass column ( 5 % OV-210 on 80/100 mesh Gas Chrom 0 ) . Linear recovery curves were obtained. Inorganic orthophosphate did not interfere with urine analysis, although it could be easily removed by Ca(OH), precipitation.
Ionic alkyl and aryl phosphates, phosphonates, and thio analogues are metabolites of organophosphorus pesticides and several other categories of economically important chemicals (1). These compounds can be determined on a class basis as inorganic orthophosphate (Pi)after wet ashing ( 2 ) . However, no single method is available for the routine identification or quantitation of these compounds, especially diprotic alkylphosphonates, in biological or abiotic samples. Most of the chromatographic methods have been designed for dialkyl phosphates and thiophosphates. These techniques involve esterification with diazoalkanes and determination of the alkyl Present address, Sanitary Engineering Research Laboratory, University of California, 112 RFS, 47th and Hoffman Blvd., Richmond, Calif. 94804. Present address, Mikrobiologisches Institut, ETH Zentrum,
CH-8092 Zurich, Switzerland.
0003-2700/79/0351-1949$01.00/0
esters by gas-liquid chromatography (GLC) (3,and references therein). All of these methods have suffered from a key weakness: the unfavorable partitioning of the highly polar dialkyl phosphates into the extraction solvent ( 3 ) . Indeed, recovery of dialkyl phosphates from urine has been a t best semiquantitative ( 4 , 5 ) ,and the samples required extensive cleanup (6). Furthermore, the techniques available for determining the extremely polar non-esterified alkylphosphonates are few. Jakob et al. (7) developed a separation method for several ionic alkylphosphonates in water, but the procedure was lengthy and the detection limits were poor. Phenylphosphonates in urine have been amylated and separated by GLC, but many interferences were encountered (8). We report here a method for identifying and quantitating alkyl and aryl phosphates, phosphonates, and thio analogues in biological samples by GLC of the benzyl esters formed with 3-benzyl-1-p-tolyltriazene (BTT). This derivatizing reagent has been proposed for the determination of ionic dimethyl phosphate (9).
EXPERIMENTAL Gas-Liquid Chromatography. A Perkin-Elmer 3920B gas-chromatograph equipped with a flame-photometric detector (phosphorus mode) was used. The 0.25411. 0.d. glass column (6 ft X 2-mm id., treated with 5% w/v dimethyldichlorosilane in toluene) was packed with 5% OV-210 on 80/100 mesh Gas Chrom Q and vapor-phase deposited with Carbowax 20M (10). The glass inlet liner was also treated with dimethyldichlorosilane. The operating conditions were: column oven temperature programmed from 170 "C at 16 "C per min to 225 "C for 4 min; injector, 250 "C; detector, 250 "C; He, 30 mL/min; air, 109 mL/min; H,, 70 mL/min. Isothermal determinations were at 225 "C. Reagents and Compounds. Technical grade BTT (Aldrich Chemical Co., Metuchen, N.J.) (Caution: BTT is a suspect carcinogen!) was recrystallized from petroleum ether using 2,C 1979 American Chemical Society
