Anal. Chem. 1980, 52, 154-159
154
Critical Evaluation of Lifetime Measurements via Reiterative Convolution Using Simulated and Real Multiexponential Fluorescence Decay Curves L. J. Cline Love* and L. A. Shaver' Department of Chemistry, Seton Hall University, South Orange, New Jersey 07079
A reiterative convolution method for the calculation of luminescence lifetimes from time correlated single photon technique decay data is critically evaluated using both computer simulated and experimental multicomponent curves. The precision for single component simulated curves was 0.014 ns and was dependent on the lifetime differential for twocomponent simulated curves. The accuracy and precision of the latter improved as the lietkne difference increased. Single and double component experimental curves from some antimalarial drugs had a precision of 0.2 ns. Two-component systems had to differ by 1 ns and 3 ns, respectively, for slmulated and experimental curves In order to be adequately resolved. The relative contribution of the two components to the total fluorescence Intensity had a pronounced effect on the accuracy of both experimental and simulated data. Two-component resolution was found to be the practical limit of reiterative convolution, and the minor component must contribute at least 1/,5 of the signal for accurate resolution. Experimental ternary mixtures were not resolvable.
Because of the finite temporal width of the excitation light pulse and the possibility of multiple fluorophores decaying in a common time span, precise and accurate fluorescence lifetime calculations often necessitate calculation by computer deconvolution (1-6). The observed luminescence decay function is actually the convolution of the excited state decay characteristics, the lamp intensity profile, and various instrumental response functions. The latter distortion functions need not be explicitly known if they are the same for both excitation and emission (7) or appropriate corrections are applied (8). The data analysis generally consists of deconvoluting the experimental luminescence decay curve to correct for the lamp flash profile and to separate any multiexponential decay data into the respective components. Several deconvolution algorithms are currently available and seven principal techniques have been critically compared (9). In the results of the comparison, the iterative convolution method was found superior to the others in its ability to deconvolve simulated double exponential decays, a very fast simulated single exponential decay and it was less susceptible to noise. The particular reiterative convolution (RC) method of Zimmerman and co-workers ( 1 0 , I I ) also has the advantages of being mathematically the simplest of the deconvolution methods and yet powerful enough to meet our research objective of analysis of multicomponent samples. The present work is the first critical evaluation of the reiterative convolution method of Zimmerman for resolution of single and multicomponent fluorescence decay times from both simulated and actual experimental curves measured by the time correlated single photon (TCSP) technique. The 'Present address, FMC Corporation, Industrial Chemical Group, Analytical Chemistry Section, Box 8, Princeton, N.J. 08540. 0003-2700/80/0352-0154$01 .OO/O
capabilities of the RC method for the ideal cases of convoluting simulated single, double, and triple exponential decays with simulated lamp flashes to which random Poisson noise has been added are considered. The accuracy and precision of the calculated lifetimes are evaluated for each case, as well as the effects of total counts collected and relative magnitudes of amplitude constants of the recovery of lifetimes. The results provide a best case base line for the reiterative convolution method applied to single and multicomponent exponential decays, independent of errors contributed by the TCSP measurement system. The TCSP technique is potentially the most useful for experimental quantitative fluorescence decay measurements because its theoretical signal-to-noise (S/N) ratio can be selected to permit maximum accuracy and precision in the measurement process and multicomponent decay data can be conveniently resolved by computerized curve fitting routines (12-14). A further advantage is the absence of RC time constant limitations on the counting statistics which allows the entire working range of concentrations to be determined with the same S/N ratio. Various instrumental aspects of the TCSP technique have been reviewed ( 7 , 1 5 )and the method has been recommended for use over other measurement systems for multicomponent decays to obtain fluorescence lifetimes (16). This method was felt to be capable of providing computer-compatible experimental multiexponential decay data with sufficient accuracy, precision, and sensitivity to allow evaluation of the reiterative convolution data analysis method. I t was used for all of the experiments in this study. The fluorescence decays of several antimalarial (17) and anthelmintic drugs, and several laundry brighteners were measured by the TCSP technique, and the excited state lifetimes were calculated by the reiterative convolution method. Compounds include in this study are quinine sulfate, quinacrine hydrochloride (also known as atabrine dihydrochloride) and its related homologues, thiabendazole and its 5-hydroxy metabolite, and six laundry brighteners. Synthetic mixtures of compounds selected from this group were also studied to evaluate multicomponent resolution. The accuracy and precision of single and double component samples were determined. Comparison of the simulated and experimental systems results allows apportionment of the sources of error and an assessment of the practical reliability of the overall experimental system. The criteria for deciding when graphical lifetime calculation is inadequate and deconvolution should be applied was found to be the same for experimental data as was found for simulated data (18).
EXPERIMENTAL Instrumentation. The TCSP instrumentation used here is well documented and described elsewhere (17). In these experiments no quantum counter solution was used to correct for lifetime errors due to the wavelength dependent response of the RCA 8850 photomultiplier tube. Reagents. Quinine sulfate was obtained from Aldrich Chemical Co., Milwaukee, Wis.; quinacrine hydrochloride, which is N4-(6chloro-2-methoxy-9-acridinyl)-N',~-diethyl-l,4-pentanediamine C 1979 American Chemical Society
ANALYTICAL CHEMISTRY, VOL. 52, NO. 1, JANUARY 1980
nents in the sample. Thus, for multicomponent samples, the fluorescence intensity is the convolution of the flashlamp intensity, I , and the sum of negative exponentials. Principles of the time correlated single photon technique show that the data accumulation process is the result of countinp; rare events (13, 2 4 ) . Thus, Poisson statistics are followed and the standard deviation of the noise about any given datum equals the square root of that value (22). Random, normally distributed noise following Poisson statistics was added to simulated curves by the algorithm in Equation 4, to more closely approximate actual experimental data.
I
17: Figure 1. Structural form of an antimalarial homologous series related
to quinacrine,species I; parent backbone structure of laundry formulation brighteners, species 11, where DDEA is R = -N(C2H40H),, TA is R = -NH-C,H, and DMEA is R = -N(C,H40H)CH3 dihydrochloride, and the related homologues having the skeletal structure shown as species I in Figure 1, where R = H, n = 1 through n = 7, as well as thiabendazole, which is 2-(4-thiazoly1)-1H-benzimidazole,and its 5-hydroxy metabolite were gifts from G. Downing, Merck & Co., Rahway, N.J. All of the pharmaceutical agents were used without further purification. Aqueous stock solutions M) of quinacrine hydrochloride and its homologues were diluted to lo4 M in either 0.1 N HC1 or 0.1 N H2S04. The mixtures were prepared by combining aliquots of the components and diluting. All homologues were excited at 337 nm and their fluorescence measured in the 425475 nm wavelength range. Stock solutions of thiabendazole and 5-hydroxythiabendazole was prepared by dissolving 10 mg in 2 mL of glacial acetic acid and diluting to 500 mL with distilled water. Working solutions were diluted 10- to 20-fold in 0.1 N HCl. The drug has an excitation wavelength at 310 nm and an emission wavelength a t 370 nm, while the metabolite has values of 325 and 525 nm, respectively. The six laundry formulation brighteners studied are Phorwite DCB (Verona Dyestuffs, Union, N.J.), Uvitex SK NTS (Ciba), Calcofluor white 5BT (American Cyanamid),DDEA (American Cyanamid), TA (GAF), and DMEA (Ciba). The structures of the first three are held in confidence. The latter three have the same backbone structure shown as species I1 in Figure 1, differing only in attached functional groups. They were dissolved in either distilled water or 0,001 N NaOH. The compounds adsorb radiation in the 270-nm to 350-nm range and fluorescence in the 425-nm to 500-nm wavelength range. Computer Simulations. Fluorescence decay is generally considered to follow an exponential decay function and the model used in the present work is E, = Eo exp(-kt)
(1)
where E, is the fluorescence intensity at time t , Eo is the initial intensity and k is the decay constant, the reciprocal of which equals the fluorescence lifetime. Short-lived fluorescence that is convoluted with the exciting radiation is given by the convolution integral E, =
Jt
Ija exp[-k(t - j ) ] d j
155
(2)
where I, is the flashlamp intensity, a is an amplitude term, and j is the time axis index counter. Reiterative convolution calculates a and k by successive approximations. The details of the method are described elsewhere in the scientific literature (6,10,2 9 - 2 1 ) . The convolution integral can be generalized in Equation 3.
In this relationship, n equals the number of fluorescent compo-
E,' is the final value of the simulated fluorescmce to which statistical fluctuations have been added or subtracted. The value s in Equation 4 is the standard deviation of the datum and equak the square root of E,. The algorithm uses the computer's built-in random number generator function, RND, and averages 10 random numbers between 0 and 1. The vi% and v % terms are derived from statistical dispersion properties of the uniform distribution from which ten random numbers are averaged. Using the simulated flashlamp profile and the chosen k values and a values, the program generates the simulated fluorescence decay curve. The random, normally distributed statistical fluctuations are automatically added to both flashlamp and fluorescence profiles. For deconvolution of simulated or real decay curves, initial estimates for a and k are made, then the computer program further refines these estimates with each iteration. The reiterative process is halted when no improvement in fit can be gained using the goodness-of-fit criteria of both Knight and Selinger (23)and Zimmerman and co-workers (24).
RESULTS AND DISCUSSION Capabilities of Reiterative Convolution. A critical evaluation of reiterative convolution of simulated decay curves provides a measure of the best accuracy and precision obtainable and the limits of the data treatment process. T h e algorithm was tested on single and multicomponent computer-simulated curves both in the presence and absence of statistical counting noise. The interaction of the total counts accumulated with the relative magnitudes of amplitude constants, added noise, and excitation source-fluorophore lifetime difference were considered. This information allows the counting statistics governing the S / N ratio t o be fully exploited for maximum benefit. For one-component decays with 1200 and 12000 counts in the peak channel (CPC), lifetimes were recovered by RC from 1.10-ns exciting radiation decay with relative errors of 1.4% and 0.1%, respectively. The simulated decays ranging from 0.50 to 3.33 ns were recovered equally well. Other workers have suggested between IO3 and lo5 CPC be accumulated (10, 23). Results of deconvolution of two-component simulated decay curves in Table I show poor agreement with known values at 1200 CPC, with average relative errors of 9.0% and 7.5%. A CPC of 12 000 gives better agreement with average relative errors for two components of 3.9% and 0.4%, while the results of 120000 are slightly better still. Errors of 3% and 4.5% were found by McKinnon e t al. for 1500 CPC using a n iterative convolution routine (9). The relative errors were less for the longer lived component and much less in the absence of added Poisson noise. Equal pre-exponential amplitude constants also seem to cause better deconvolution of the simulated decays. Curves differing by a factor of two in amplitude constant could not be successfully deconvoluted a t the 1200 CPC level. The increased data accumulation time for lo5CPC does not appear to be justified except for fluorophores of widely differing intensities (amplitude constants) and/or excessive amounts of noise. A CPC of lo4 provides adequate
156
ANALYTICAL CHEMISTRY, VOL. 5 2 , NO. 1, JANUARY 1980
Table I. Comparison of Lifetimes Calculated by Reiterative Convolution for Computer-Simulated Fluorescence Decay Profiles for T w o Components Having Peak Intensities of 1,200, 12,000, and 120,000 Counts fluorescence lifetime, ns component A
component B
found
found
theoreticala
1,200
12,000
120,000
Lllb
0.95 e 1.15
1.15 1.02
1.12
1.1lC
Llld
theoretical' 3.33b 3.33c 3.33d
1.09
1.11
.__
1,200
12,000
120,000
3.78
3.33 3.29 3.33
3.34 3.32'
e
3.38
__-
a Simulation parameters: exciting radiation decay lifetime, 1.10 ns. Pre-exponential amplitude terms, a ( A ) = a(B). Pre-exponential amplitude terms, a ( A ) = a(B)/2. N o noise added t o simulated curves. e Failed to give reasonable result.
component. Two-component curves having various ratios of amplitude terms were simulated and deconvoluted. The curves had 12 000 CPC and the ratio of a values varied from 1:2 to 1OO:l. The results of this study are given in Table 11. I t is evident that a minor component can be deconvoluted to within 10% accuracy if it contributes a t least of the fluorescence signal. Reiterative convolution was able to deconvolute one case of three-component simulated data having lifetimes of 1,3, and 5 ns and equal amplitude terms with approximately 10% relative error. Three-component experimental data could not be successfully deconvoluted to resolve the three components, although two of the components were successfully extracted. A large number of two-component simulated and experimental decay curves were successfully deconvoluted, and it appears that two components is the practical limit of reiterative convolution of experimental data. Simulated fluorescence decay curves of one-component systems having lifetimes from 0.05 to 4.00 ns were deconvoluted from simulated 1.10-ns decay excitation pulses by reiterative convolution to test the accuracy of the method. From the results it is concluded the RC is capable of deconvoluting fluorophores having lifetimes as low as 0.05 ns with a 10% relative error. Lifetimes in the 0.25- to 0.9-ns range deconvoluted with less that 2% error and for 1.0 ns and larger lifetimes, the relative errors were negligible. The precision of RC of one-component simulated data having lifetimes ranging from 0.10 to 4.00 ns is consistently uniform. The standard deviation of 45 deconvolutions of simulated curves in this lifetime range was *0.014 ns. The resolution of multiexponential curves into the respective components by RC was moderately successful. Decay curves for simulated two-component mixtures of fluorophores were deconvoluted to determine the minimum lifetime difference required for resolution. The results given in Table
Table 11. Results of Deconvolution of Two-Component Computer-Simulated Fluorescence Decay Curves for Various Ratios of Amplitude Terms
ratio a*:ag
fluorescence lifetime, ns component A component B _ _ theoretical found theoretical found
1:2 2:l
1O:l 1:lO 1OO:l
1.11 1.11 1.00 1.00
1.00
1.07 1.08
1.04 1.10 1.00
3.33 3.33 4.00 4.00 4.00
3.31 3.27 4.20 3.9Y 4.73
accuracy for most situations encountered. RC requires that the operator input estimates of the values of the pre-exponential amplitude term, a, and the decay constant, k , which are then improved by the algorithm's successive approximations. For one-component curves, it was found that the initial estimate for the amplitude term could be off by an order of magnitude, high or low, and the algorithm still rapidly converged on the correct value. If the initial estimates of the decay constants were less than the theoretical value, the algorithm converged to the correct value, but estimates much larger than the correct value caused the computer to exceed the computer's magnitude limits of one or more variables. These findings resulted in the adoption of the practice of underestimating the value of k in the deconvolution of experimental data. The effect of relative magnitudes of amplitude constants was noted earlier in Table I. For two components having fluorescence lifetimes within a few nanoseconds of each other, the pre-exponential amplitude term, a,, in Equation 3 approximately equals the relative contribution of the respective fluorophores to the total fluorescence signal. Emission from a minor component may be masked by that from a major
Table 111. Resolution and Precision of Fluorescence Lifetimes of Two Components Calculated from Computer-Simulated Data fluorescence lifetime, ns difference between
theoretical lifetimes, ns 0.10 0.25
resolution poor poor poor fair-good good
theoreticala 1.00 4.00 1.00
-
component B
component A
theoreticala
found
0.61, b
1.10
b, b
4.25 1.67 5.00 3.33
found
1.34, b b, b
1.99, 1.33 4.99 mean = mean = 3 . 3 F std. dev. = 0.07 std. dev. = 0.09 RSD = 8% RSD = 2% 4.00 mean = 4.00d 3.00 good 1.00 mean = 0 . ~ 9 ~ std. dev. = u.03 std. dev. = 0.014 RSD = 3% RSD = 0.34% a Simulation parameters: excitation radiation decay lifetime; 1.10 ns, intensity at peak = 1 2 000 counts; preexponential amplitude terms. a ( A )= a ( B ) . Failed to give reasonable results. Five trials. Six trials. 0.67
1.00 2.22
4.00 1.11
1.25, 0.42 3.87 1.12c
*
ANALYTICAL CHEMISTRY, VOL. 52, NO. 1, JANUARY 1980
157
Table IV. Accuracy of Graphical Slope vs. Deconvolution Methods for the Calculation of Fluorescence Lifetimes from Single-Component Experimental Data fluorescence lifetime, ns literature compound
value
quinine sulfateb quninacrine homologues' R=H,n=l R=H,n=2 R = H, n = 3 R=CH,,n=3 R = H, n = 4 R=H,n=5 R= H,n= 6 R=H,n=7 acridined
founda deconvolution graphical 19.4
19.8
11.7 5.6 3.4 2.9
11.5 6.0 3.8 3.3 3.0 2.6 2.6 2.4 1.7
2.2
1.9 1.8 1.4
0.7
Exciting radiation width-at-half-maximum,3.0 ns; decay lifetime, 1.3 ns. M in 0.1 N HCI. Excitation wavelength, 337 nm; M in 0.1 N H,SO,. a
5% error graphical calculation 2
ref. (25)
2
7 12 14
36 37 31 71
142 (27) Excitation wavelength, 337 nm; 5 X Excitation wavelength, 358 nm; 5.8 x
lov4
M.
I11 show that resolution is not feasible if the respective fluorophores differ in lifetime by less than 1 ns. Further, the shorter-lived component will be less accurate and precise than its longer-lived companion. The greater the difference in lifetimes, the more accurate and precise is the resolution, as expected. Precision and accuracy data on the simulated curves represent statistical fluctuations of the decay profiles as well as the performance of reiterative convolution, as each deconvolution was performed on a freshly simulated decay profile containing newly generated random noise. Criteria for Deconvolution. The accuracies of the graphical slope and deconvolution methods of data treatment have been tested on computer simulated data (18). It was reported that when the decay lifetime is within 2 ns of the exciting radiation decay lifetime, then serious errors of greater than 5% in the graphical slope calculated value can be expected and the decay curve should be deconvoluted. A comparison of real experimental lifetimes obtained by both the graphical and deconvolution methods bears out the predictions of the computer simulation studies. The results shown in Table IV were obtained with a flashlamp having a radiative decay of 1.3 ns. Using the 2-11s difference rule, deconvolution of the experimental decay curves of fluorophores with lifetimes of 3.3 ns or less is necessary to avoid serious error. For example, the fluorescence lifetime of 3.8 ns found for compound I, R = H, n = 3, by the graphical slope method is in error by 12%, assuming the deconvoluted value is correct. The data in Table IV also contain references to compare three of the compounds' lifetime values with those obtained by other workers in the scientific literature (25-27). The agreement is reasonably good. Small discrepancies in the values obtained for the quinacrine series, species I in Figure 1, can be attributed partially to the absence of a quantum counter in the present experiments to correct for the wavelength dependence of the lifetimes at the photomultiplier tube. The results of experimental and computer simulated studies are presented in the errnr analysis plot in Figure 2. It plots the difference between the luminescent lifetime as calculated by the graphical slope method and pulsed source radiation lifetime vs. percent error for 1.10- and 3.03-11s simulated (18) and 1.10- (28,29) and 1.30-ns experimental excitation radiation. The error values from the experimental data are in good agreement with the predicted errors. From this plot, the error of the graphical slope calculation can be quickly estimated and a decision made objectively whether deconvolution is necessary to obtain the desired accuracy. It can be used to estimate luminescence lifetime errors for any type pulsed
a 0
I
+ Y
E
120 -1
4 0
= a Q
80 a 0
m a Y
& 40 W
V
a W
a
0 0 1 2 L U M l N E S C E N C E- S O U R C E
3 4 DIFFERENCE
5 (ns)
Figure 2. Error anabsis of the graphical slope lifetime calculation method vs. deconvolution calculations for -e- 1.10 and I- 3.03 os simulated and -0- 1.10 and -X- 1.30 ns experimental exciting radiation. See text for specific compounds used in experimental studies and references 18, 28, and 29
source having a lifetime in the 1-to 3-11s range by interpolation of the other members of the family of curves. The overall standard deviation of the deconvoluted experimental lifetimes in this work was 0.2 ns over the entire 0.9- to 20-11s range. The precision of the graphical slope calculation is comparable, with estimated standard deviations of 0.03 ns for the simulations and 0.2 ns for the experimental data. For single-component samples with long lived fluorescence lifetimes, there is little advantage in deconvolution. Deconvolution should be used for the separation of the components in double-exponential decay curves of fluorophore mixtures unless the lifetimes are far enough apart. Application to Single-Component Chemical Systems. The accuracy of the deconvoluted fluorescence lifetimes (Table IV) for quinine sulfate, quinacrine, and acridine was previously noted, as well as the standard deviation of f0.2 ns for fluorophore lifetimes between 1 and 20 ns. The latter is in good
158
ANALYTICAL CHEMISTRY, VOL. 52, NO. 1, JANUARY 1980
Table V. Fluorescence Lifetimes of Some Short-Lived Species fluorescence lifetime,a compound
(ns) t 0.2
thiabendazoleb 5-hydrox yt hiabendazole Phorwite DCBC Calcofluor white 5BT Uvitex S K DDEA
0.3 0.3
2.3 2.7 1.4 0.7
TA
0.8
DMEA
0.6
a Decay lifetime of exciting radiation, 1.3 ns. Excitation wavelength, 312 n m ; 1 x M solution in 0.1 N HCl. The same lifetimes were obtained in 0.001 NaOH and in distilled water for all the laundrv formulation
brighteners; 0.2 mg/L. agreement with the experimental precision work of Tao (30). The fluorescence lifetimes of several short-lived species are shown in Table V. No values were found for them in the scientific literature. The last three laundry formulation fabric brighteners have essentially the same lifetimes within experimental error, as expected based on their molecular structures. Their skeletal backbone structure is shown as species I1 in Figure 2. The first three brighteners listed have longer lifetimes as a group compared to those of the species' I1 homologues. Application to Double-Component Chemical Systems. Several synthetic mixtures of quinine sulfate and the quinacrine-type series compounds were studied using the timecorrelated single-photon technique with reiterative convolution data reduction. The fluorescence lifetimes of the compounds alone and in mixtures are given in Table VI. The first three mixtures are quinine sulfate and quinacrine hydrochloride (R = CH3, IZ = 3) in 0.1 N H2S04in various concentration ratios. The lifetime recovered for quinine is best when it predominates the total fluorescence signal, as demonstrated in mixtures 1 and 2. The quinacrine lifetimes recovered from mixtures I, 2, and 3 are in good to fair agreement with that of the 2.7 ns for the compound alone. At relatively low quinine concentrations, as in mixture 3, the 13.1-ns lifetime found in the mixture is in poor agreement with the 19.4 ns found for quinine alone. The two compounds in a 1 : l O concentration ratio were resolved by deconvolution in good agreement with lifetimes obtained alone, but they could not be resolved accurately at a 150 concentration ratio. There is no apparent interaction of quinine sulfate and quinacrine a t these concentration levels. The computer simulations and experimental data agree that a minor component must be contribute approximately of the total fluorescence signal
in order to be resolved. In addition, these results demonstrate that the instrumental and deconvolution system is capable of the resolution of simple two-component samples. The lifetimes recovered in mixtures 4, 5, 8, and 9, for compound I, (R = H, n = l ) ,are in fair agreement with the 11.7 ns found for the compound alone. However, the shorter-lived component in each case had larger errors in their recovered lifetimes, as predicted from computer simulations. Mixtures 6 and 7 represent two fluorophores having decay times of 5.6 and 2.9 ns, a difference of 2.7 ns. As previously mentioned, deconvolution of computer-simulated decay curves for mixtures of two fluorophores predicted that the two fluorescence lifetimes must differ by at least 2 ns in order to be accurately resolved. Computer-simulated curves represent ideal situations where no noise other than statistical counting noise is present. The experimental results which include instrumental noise and any chemical manipulation errors from mixtures 6 and 7 suggest that a > 3 ns difference instead of 2 ns should separate the two lifetimes for their accurate resolution. In mixtures 6 and 7, for component A (R = H, n = 2 ) , the lifetime of the compound alone was 5.6 ns and values of 5.2 and 6.5 ns were calculated from the mixtures data. Component B (R = CH3, IZ = 3) had a lifetime equal to 2.9 ns alone but was found to be 1.2 and 1.6 ns when determined in mixtures 6 and 7 , respectively. Attempts to deconvolute experimental data for two fluorophores having lifetime values differing by less than 2 ns were unsuccessful. CONCLUSIONS The reiterative convolution method is capable of deconvoluting single component decay curves containing only Poisson distributed noise with a standard deviation of about 0.02 ns. The standard deviation of actual experimental systems was ten times larger and is attributed to instrumental and chemical manipulation errors. While theoretically two component decays could be adequately resolved by calculation if separated by 1 ns, TCSP experimental decay data suggests a minimum of 3 ns for comparable accuracy. However, the resolution also depends on the relative contributions to the total fluorescence signal (amplitude constants) of the components. Concentration ratios larger than about 1:15 showed large errors in lifetimes compared to the values of the compounds alone. The TCSP technique with RC data analysis was found to be useful for qualitative identification of singleand double-component chemical systems within certain concentration ranges. Reduction of instrumental fluctuations added to the decay curves potentially could result in a tenfold improvement in precision for single-component fluorophore lifetime calculations and an improvement in the resolution of two fluorophores from a 3-ns difference to a 2-ns difference in their lifetime.
Table VI. Resolution of Fluorescence Lifetimes of Synthetic Mixtures of Quinine Sulfate and Quinacrine Homologues concentra- ~. fluorescence lifetime, nsa component B tion component A ratio, alone mixture alone mixture medium mixture component A component B A :B 1 2 3
quinine sulfate
I, R = CH,, n = 3 I, R = CH,, n = 3 I, R = CH,, n = 3 I, R = CH,, n = 3 I, R = CH,, n = 3 I, R = CH,, n = 3 I, R = CH,, n = 3 I,R=H,n=2 I,R=H,n=2
I,R=H,n=l I,R=H,n=l 6 I,R=H,n=2 7 I,R=H,n=2 8 I, R = H, n = 1 9 I,R=H,n=l Decay lifetime of the exciting radiation. 1.3 ns. 4 5
a
quinine sulfate quinine sulfate
1:10 1: 2
1:50 1:5 1:l 1:5 1:l 4:l
1:l
19.4 19.4 19.4 11.7 11.7 5.6 5.6 11.7 11.7
19.1 lY.9 13.1 11.0
12.8 5.2 6.5 13.2 12.5
2.7
2.5
2.7
2.8 2.1 1.6
2.7 2.9 2.9 2.9 2.9 3 .6 3.6
2.2 1.2 1.6
2.8 3.6
0.1 N 0.1 N 0.1 N 0.1 N 0.1 N 0.1 N
H,SO, H,SO,
H,SO, HCI HC1
HCI 0.1N HCI 0.1 N HCI 0.1 N HCI
Anal. Chem. 1980, 52, 159-164
ACKNOWLEDGMENT The authors are grateful to George Downing, Merck & Co., Rahway, N.J., for the gift of all of the antimalarial compounds employed in this study. They also thank James Fronek, Nathan Albert, and Michael McCarthy for technical assistance.
LITERATURE CITED A. Gafni. R. L. Modlin. and L. Brand, Siophys. J., 15, 263 (1975). E. Valeur and J. Moirez, J . Chim. Phys., Phys.-Chim. Biol., 70, 500 (1973). W. R. Ware, L. J. Doemeny, and T. L. Nemzek, J . Phys. Chem., 77, 2038 (1973). B. R. Hunt, Math. Biosci., 10, 215 (1971). I.Isenberg and R. D. Dyson, Biophys. J., 9, 1337 (1969). A. Grinvald and I.2. Steinberg, Anal. Biochem., 59, 583 (1974). I.Isenberg in "Biochemical Fluorescence-Concepts", Vol. 1, R. F. Chen and H. Edelhoch, Eds., Marcel Dekker, New York, 1975, Chapter 2. D. M. Rayner, A. E. McKinnon. A. G. Szabo, and P. A. Hackett. Can. J. Chem., 54, 3246 (1976). A. E. McKinnon. A. G. Szabo, and D. R. Miller, J . Phys. Chem., 81. 1564 (1977). H. E. Zimmerman, D. P. Werthemann, and K. S. Kamm, J . Am. Chem. Soc., 96, 439 (1974). H. E. Zimmerman and T. P. Cutler, J . Chem. Soc., Chem. Commun., 598 (1975). C. Lewis, W. R. Ware, L. J. Doemeny, and T. L. Nemzek, Rev. Sci. Instrum., 44, 107 (1973).
(18) (19) (20)
(21) (22) (23) (24) (25) (26) (27) (28) (29) (30)
159
J. B. Birks and I. H. Munro, Prog. React. Kinet.. 4, 29 (1967). L. J. Cline Love and L. A. Shaver, Anal. Chem., 48, 364A (1976). W. R. Ware in "Creation and Detection of the Excited State", Vol. 1, Part A. A. A. Lamola, Ed., Marcel Dekker, New York, 1971, Chapter 5. M. A. West and G. S.Beddard, Am. Lab., 8(11), 77 (1976). L. J. Cline Love, L. M. Upton. and A. W. Ritter, Anal. Chem., 50, 2059 (1978). L. A. Shaver and L. J. Cline Love, Appl. Spectrosc., 29, 485 (1975). L. A. Shaver and L. J. Cline Love, Prog. Anal. Chem. 8, 249 (1976). A. E. W. Knight and E. K. Selinger, Spectrochim. Acta, Part A, 27, 1223 (1971). A. L. Hinde, B. K. Selinger, and P. R . Nott, Aust. J . Chem., 30, 2383 (1977). R. R. Sokal and F. J. Rohlf, "Biometry", Freeman, San Francisco, 1969, Chapter 5. A. E. W. Knight and E. K. Selinger, Aust. J . Chem.. 26, 1 (1973). H. E. Zimmerman, K. S.Kamm, and D. P. Werthemann. J . Am. Chem. Soc., 97, 3718 (1975). R. F. Chen, Anal. Biochem., 57, 593 (1974). R. F. Chen, Arch. Biochem. Siophys., 172, 39 (1976). I. B. Berlman, "Handbook of Fluorescence Spectra of Aromatic Molecules", 2nd ed., Academic Press, New York, 1971. G. L. Loper and E. K. C. Lee, Chem. Phys. Lett., 13, 140 (1972). G. C. Loper, University of California, Itvine, Calif., private communication, November 1974. T. Tao, Biopolymers, 8, 609 (1969).
RECEIVED for review June 25, 1979. Accepted October 18, 1979. One of the authors (L.A.S.) is grateful for partial support by FMC Corp., Princeton, N.J.
Characterization of Environmental Samples for Polynuclear Aromatic Hydrocarbons by an X-ray Excited Optical Luminescence Technique C. S. Woo,' A. P. D'Silva, and V. A. Fassel" A m e s Laboratory,
USDOE and Department of
Chemistry, I o w a State University, Ames, I o w a 500 7 1
The X-ray excited optical luminescence (XEOL) of a concentrate in n-heptane of the neutral fraction isolated from by-products of coal combustiin and conversion, and from shale and fuel oils has been utilized to obtain profiles of their polynuclear aromatic hydrocarbon content. The advantages of observing the XEOL of these compounds in Shpol'skii solvents to differentiate Isomeric compounds are documented.
A substantial increase is predicted in the utilization of coal for power production and in coal gasification-liquefaction technologies. The products of coal combustion or conversion to gaseous or liquid fuels are known to contain substantial quantities of polynuclear aromatic hydrocarbons (PAHs), nitrogen heterocyclics, sulfur heterocyclics (thiophenes), and oxygen heterocyclics (furans). Several constituents in the above classes of compounds are known to be carcinogens, co-carcinogens and oncogens ( I ) . Thus, the increased utilization of coal will substantially increase the environmental load of the above compounds through particulate and other fugitive emissions. Because the carcinogenicity of such emissions has been found to be enhanced through synergistic effects ( I ) , the cumulative effects on environmental degra'Present address: Chemistry Department, University of N o r t h e r n Iowa, Cedar Falls, Iowa. 0003-2700/80/0352-0159$01 .OO/O
dation and occupational health of these emissions are expected to be of substantial complexity and magnitude. T o evaluate the potential impact of this environmental loading, a large number and variety of environmental samples consisting of particulates and products of coal conversion technologies should be characterized. As a result, there is increasing interest in new analytical concepts that may prove useful for the efficient detection, quantitation, and monitoring of the potentially hazardous compounds at trace levels. There have been recent significant advances in the application of new analytical techniques and methodologies to the quantitation of PAHs in environmental samples (2-12). In the discussion that follows, only typical "state of the art" technologies and methodologies are cited, and the references are not exhaustive. In recent years the principal techniques utilized are: thin-layer chromatography (TLC), capillary column gas chromatography followed by flame ionization detection (GC) or mass spectral characterization (GC-MS), gas-liquid chromatography using nematic liquid crystal columns (GLC), and high performance liquid chromatography with fluorescence detection (HPLC). A critical test for any of these analytical techniques is t.he capability to identify and/or quantitate isomeric species, because the PAHs contained in environmental samples usually consist of several isomeric groups, having widely varying carcinogenicity. Typically, an analytical technique should be able to resolve the four-ring isomers, chrysene, benz[a]anthracene (B[a]A), 0 1979 American Chemical Society
