Fluorescence Spectrometry with Optoelectronic Image Detectors

Report

Fluorescence Spectrometry with Optoelectronic Image Detectors Yair Talmi and D. C. Baker

J. R. Jadamec and W. A. Saner

Electro-optical Instrument Division EG&G Princeton Applied Research Corp. P.O. Box 2565 Princeton, N.J. 08540

U.S. Coast Guard Research and Development Center Avery Point, Groton, Conn. 06340

Molecular fluorescence spectrosco py (MFS) has received widespread ac ceptance as an analytical technique, primarily because of its high sensitivi ty and selectivity. The growing impor tance of MFS is reflected by the abun dance of recent literature (1-8). The use of parallel optoelectronic image detectors (OID) for spectroscopy has also increased dramatically over the past several years, and numerous re views and application notes have de scribed their unique features {9-15). However, the specific application of the OID to M F S has not been com pletely covered, and this REPORT is an attempt to fill this void by summariz ing the advantages of parallel detec tion in MFS.

(15) or for samples susceptible to pho tochemical decomposition. Because the almost universal usage of the P M T detector makes its behav ior and concepts of operation familiar to most spectroscopists, this REPORT

Although a large variety of spectrofluorometers is now commercially available, the detection system used almost exclusively is based on the use of the photomultiplier tube (PMT) in a single-channel configuration. Yet, the parallel multichannel OID should be clearly superior because of its abili ty to record the entire spectrum si multaneously. Parallel detection can result in either a significant increase in signal-to-noise ratio (SNR) or a cor responding reduction in analysis time (multiplex advantage, 16), and it is uniquely adaptable to transient spectrofluorometry, such as real-time liq uid chromatography peak detection

Wavelength

will compare it where applicable, with OID's. This REPORT is an overview of experimental setups and data inter pretation; thus, only the most basic and unique data acquisition and pro cessing capabilities of OID's are dis-

Wavelength

Figure 1 . E m i s s i o n s p e c t r u m of o v a l e n e (a) Normal spectrum, (b) first derivative spectrum. Spectral coverage, 4 4 0 - 5 8 0 nm (350 channels); spectral bandpass, 2 nm. Golay-Savitzky algorithms; quadratic fit, Δ λ (DS) = 2 nm

936 A · ANALYTICAL CHEMISTRY, VOL. 50, NO. 1 1 , SEPTEMBER 1978

0003-2700/78/0350-936A$01.00/0 © 1978 American Chemical Society

cussed when it is necessary for main taining the coherence of the text and for conceptual support. However, to satisfy the more orthodox reader, it is planned that a sequel will be pub lished at a later date dealing with the more fundamental concepts in detail. Instrumentation

In these studies a silicon intensified target (SIT) vidicon was used as the parallel detector. Control of the SIT and data acquisition and manipula tion were achieved with either an EG&G Princeton Applied Research Corp. Model 1205A optical multichan nel analyzer (OMA) in conjunction with an HP-9825A desk calculator or with EG&G PARC computerized OMA-2 (Model 1215) console and Model 1216 detector controller. Spectrofluorometers used in the study in cluded a Farrand spectrofluorometer Model Mark I, an S.A. Instruments Video-spectrofluorometer Model JY-4, and a Perkin-Elmer spectropho tometer Model MPF-4. The three spectrofluorometers vary in their specific optical design, but the basic arrangement of each consists of a broadband light source, usually a xenon lamp, an excitation monochromator, a sample compartment, and an emission polychromator. One varia tion of this arrangement is the use of a crossed excitation polychromator for total luminescence spectroscopy where two 0.3-m Ebert-mount polychromators (EG&G PARC Model 1208) were used in a special orthogo nal configuration (see Total Lumines cence Spectrometry section). Signal-to -Noise Ratio Considerations

A basic understanding of the origin, behavior, and magnitude of noise sources in a spectrometric system helps considerably in optimizing its SNR performance. The multiplex (SNR) advantage of a parallel imaging detector is largely determined by its inherent sensitivity and resolution and by its noise behavior relative to that of the system as a whole.

In the following, we will briefly compare the fundamental SNR per formance of a P M T and a SIT, used as luminescence detectors. The simpli fied analysis described below is based on the following assumptions: the sys tem is photon-shot noise limited (see Source Compensation section), the en trance slit of the emission monochromator is uniformly illuminated, and in the single-channel (PMT) scanning system (SCSS) the slit height and width are identical to that of the exit slit, the scan time of the SCSS, T, is equal to the SIT signal accumulation time, and dark shot noise is-negligible. The slit width in the emission monochromator/polychromator determines the spectral bandpass, Δλ. This analysis becomes, however, somewhat ambiguous because of the very basic difference between the two detection systems. In a (power detec tion) scanning system the wavelength and time axes are identical. That is, signal intensities are acquired at dif ferent times for each spectral interval. In the (energy detection) OMA sys tem, wavelength is a function of hori zontal position on the detector and is independent of time. Therefore, filter ing the output of a scanning system to improve SNR will result in distortion of the band shape and error in the wavelength registration, unless the scan rate, Rs, (nm s _ 1 ) is limited to Rs < 8\b/tr (13), where δ λ/, is the halfwidth (nm) of the narrowest spectral feature in the spectrum, and tr the re sponse time of the scanning system. Thus, the final assumption of the analysis is that Τ > tr-n, where η = (λ2 — λχ/Δλ) is the effective number of resolution elements within the spec tral range of λ2 — λχ. Incidentally, the OMA-SIT can simultaneously cover a spectral range of 300 nm with a spec tral resolution of Δλ = 1 . 5 nm. The ratio, F, of the SNR of the SIT to the SNR of the P M T over a spec tral range from λι to λ2 is directly pro portional to the square root of the scan (acquisition) time and is inverse ly proportional to the square root of the spectral bandpass, Δλ, as shown

by Equation 1. F = , ' S ^ Î S I T = *(Γ/Δλ)ΐ/2 »JNK P M T

(1)

where K is determined by the nature of the quantum efficiency of the pho tocathode and the relative gain of the two detectors. Equation 1 presumes that the num ber of channels of the SIT system is larger than n, or in terms of system bandpass Δλ, and the wavelength cov erage of one channel, AXc, AX > AXc, where AXc = (X2 — \i)/(number of SIT channels). In MFS this is general ly true; in fact it is quite often the case that Δλ » AXc. For example, with a spectral window from 440 to 580 nm as selected for ovalene (Figure 1), with a bandpass of 2 nm, η is 70 and since only 350 SIT channels were used, AX/ AXc at 5. In such cases, the summing of Ν channels, where Ν (an integer) is equal to (AX/AXc), will improve the SNR of the SIT by VN (experimen tally verified) or by %/Δλ , and Equa tion 1 may be restated: r

summing

Λ

Α

\^f

and F SU mming/F = (Δλ)1/*

(3)

A thorough evaluation of Κ is beyond the scope of this paper. However, suf fice it to say that the overall sensitivi ty of SIT's is not significantly differ ent from that of the PMT's; they can detect approximately two photoelectrons/channel/scan with a SNR of ap proximately 1. However, SIT's have an inferior spectral response in the UV compared to PMT's with quartz windows. Nevertheless, when equipped with a UV-to-visible photon converter (scintillator), spectrally matched with the photocathode of the SIT, the quantum efficiency of the SIT is practically uniform, =i2.5%, over a UV spectral range from at least 150 to 350 nm. Κ is therefore assumed to be large enough to allow an F = 1 performance, J S N R } S I T = ! S N R ) P M T a t a certain value of Δλ (and above a cer tain λ value) and F > 1, at yet smaller Δλ values.

ANALYTICAL CHEMISTRY, VOL. 50, NO. 1 1 , SEPTEMBER 1978 · 937 A

vidicon noise can be integrated on the target long enough to ensure their ac curate readout (a process analogous to long exposures of photographic emul sions, prior to development). In fact, in conjunction with source compensa tion techniques (discussed below), ontarget signal integration provides the means for recovery of very weak sig nals (subphoton per second), even when the system as a whole is sourceflicker noise dominated. Figure 5 shows neon (hollow cath ode) spectra obtained in real-time (20 ms per scan) and after 20 and 2000 s, equivalent to 1, 103, and 105 scan peri ods, respectively. Neon spectral lines with intensities of 0.001 counts/scan/ channel; approximately 0.1 photoelectrons/second/channel can be clearly observed in Figure 5c. Thus, the SNR performance of a SIT may be increased during the mea surement by either accumulation of multiple scans in the digital memory of the console or by signal integration

1000-

100

8

I ι

100 Number of Consecutive Accumulations (Scans)

1000

Figure 2. Noise v s . signal a c c u m u l a t i o n t i m e (a study of m u l t i p l e x advantage) Light source: highly regulated tungsten source with variable intensity

The departure of the SIT noise from the square root dependence on the number of accumulations, antici pated from its photon shot noise dom inance behavior, has been previously observed (13, 17), although inade quately investigated and erroneously interpreted. Figure 2 shows the noise vs. number of accumulations relation ship at various illumination light lev els. The curve's "knee" and its relative location are related to the lowpass fil ter effect of the vidicon, caused by the inherent scanning beam discharge-lag or incomplete readout of target signal (in a single scan) by the beam of the SIT. As signal levels are raised, there is a slow shift in the position of the knee toward the origin that correlates to a corresponding reduction in dis charge lag. Consequently, the SNR in real time is better than would be an ticipated from a photon-shot noise dominated system (see extrapolation values), but the relative improvement of SNR with number of accumulations is slower than anticipated. Optimiza tion of signal acquisition time vs. SNR, particularly for transient spec trometers, e.g., liquid-chromatographic detection, should be at least partial ly based on these results. The relative SNR performance of an (SCSS)-PMT and an (OMA)-SIT is shown for anthracene in Figure 3. Figure 4 shows three chrysene emis

sion spectra obtained at concentration levels of 0.022, 0.22, and 22 Mg/L. The calculated SNR values were in good agreement with the theoretical consid erations discussed above, although at lower light levels, stray light, not elim inated by background subtraction, caused an inversion in the relative sig nal intensity levels of the four peaks. On-target signal integration is a de tection method unique to image de vices with storage capabilities, e.g., SIT's. SIT's are photon-shot noise limited down to signal levels of two photoelectrons (one digital count) per channel per frame scan, ts (140 ms > ts > 10 ms), but become electron read out-beam noise and/or preamplifier noise limited below that level. How ever, at low temperatures, e.g., —50 °C, the thermal dark charge genera tion (leakage) on the silicon target is greatly reduced. Therefore, with the vidicon readout/recharge electron beam turned off, signal integration times of 30-45 min are possible. At the end of this time the electron beam is turned on and the signal read from the target. Spontaneous photoemission from the photocathode is also reduced by cooling; its effect is even smaller in the SIT than in the P M T because in the SIT it is divided among the 500 discrete channels instead of one single electron multiplier. Consequently, weak signals buried in preamplifier or

938 A · ANALYTICAL CHEMISTRY, VOL. 50, NO. 11, SEPTEMBER 1978

Figure 3. E m i s s i o n s p e c t r a , 0.4 of a n t h r a c e n e

μg/L·,

(a) SCSS-PMT: scan time, 138 s; I, sample; II, blank, (b) OMA-SIT: acquisition time, 90 ms. (c) Acquisition time, 545 ms

3470 3230 Counts 3 i i o Counts Λ Counts

c

3620 ^ 3 8 2 ° 3025 Counts C ? u n t s Counts

36030 Counts 34510 Counts 25940 Counts

Figure 4. Chrysene emission spectra (OMA-SIT) λ exc. 254 nm, spectral bandpass of excitation monochromator, 10 nm. (a) 0.022 ^g/L, 1000 scans (30 s); spectral bandpass of emission polychromator, 5 nm. (b) 0.22 Mg/L, 100 scans (3 s); spectral bandpass, 5 nm. (c) 22 jig/L, 50 scans (1.5 s); spectral bandpass, 0.5 nm

on the target of a cooled SIT. Both of these must be done during the experi ment, but with storage of the digital data acquired by the OMA-SIT, there are several techniques for data pro cessing which facilitate spectral iden tification. Some of these data will be described in the following sections. Data Processing Techniques

Least-Squares Polynomial Smoothing. All experimental mea surements from which either qualita tive or quantitative information is to

be derived are hampered by random errors (noise) which are superimposed upon and indistinguishable from the information (signal) itself. Although a large variety of "real-time" electronic techniques can be employed by the OMA to reduce these noise effects, e.g., pixel (channel) grouping, this dis cussion will be limited to least-squares polynomial smoothing (18, 19), a nu merical method for smoothing raw data after its accumulation. The Savitzky-Golay least-squares polynomial algorithm was used for smoothing and differentiation in this study. Because

Wavelength

Figure 5. Neon spectra (hollow cathode) acquired with SIT detector cooled to —50

°C (a) Real-time detection, 20 ms/scan, ND = 0. (b) Readout after signal integration for 20 s; equivalent to 10 3 scan periods. Neutral density filter, ND = 3 (0.1 % transmission) attenuated the signal, (c) Integra tion for 2000 s; equivalent to 10 5 scan periods. Neutral density filter, ND = 5 (0.001 % transmission), attenuated the signal. Equivalent " d a r k " spectra subtracted from each neon spectrum


several published tabulations of smoothing convolution parameters, including correction to the original paper, were partially erroneous and also for the sake of computer memory conservation, the correct parameters were calculated by the computer prior to each smoothing procedure. The routine used in Hewlett-Packard's H P L for the HP-9825 is available from the authors. Because the merit of this technique has been reviewed in a previous report (20), it will be only briefly discussed here, particularly in regard to its applicability to imaging detectors. The least-squares polyno mial smoothing technique applies an approximate and sequential fitting of a polynomial smoothing function, whose order, quadratic-cubic, quartic, etc., width or smoothing step or modu lation depth, MD, and number of iter ations of the digital smoothing pro cess, are predetermined and preselect ed to maximize SNR and minimize spectral distortion. The results ob tained in this study were in agreement with those previously reported (20). At low levels the reduction in noise was inversely proportional to the square root of the modulation depth (MD). At higher levels the noise be havior has been complicated by the competitive, low-pass filtering effect of the target lag. Spectral distortion due to smoothing was dependent on the relative smoothing function ratio of half-width values of the MD and spectral features. As a rule of thumb, ratios smaller than one caused mini mal distortion. Because an imaging detector provides a simultaneous dis play of an entire spectrum, it is easy to determine the half-width of the nar rowest spectral feature and therefore also the appropriate (maximum) value of the relative smoothing function. Signal distortion, however, can be tolerated in many quantitative mea surements, particularly where spectral

interferences are minimal, and only relative-intensity measurements are performed. The distortion effects due to oversmoothing, i.e., peak distortion, are then common to all spectra (within the range of the analytical working curve) and are therefore self-cancel ing. As discussed previously (16, 20), the major effect of data smoothing is to render it more accessible and easier to interpret by human observation. Thus, new information is not generat ed; it is only revealed and empha sized. As such, it is particularly useful for qualitative (e.g., identification) studies. Smoothing procedures are particu larly useful for imaging detection of luminescence spectra because the high-frequency (spatial) channel-tochannel sensitivity variations can be greatly reduced without correspond ingly degrading the spectral fidelity of the "low-frequency" spectral bands. As it is, a good portion of the apparent noise in the spectra shown in Figures 3 and 4 is not "white", but rather a "sensitivity pattern" systematic noise. Figure 6 shows the effect of smoothing on the analog display of anthracene. Derivative Spectroscopy. Differ entiation of raw spectral data has the equivalent effect of high-pass filtering, with the bandwidth of the filter de creasing with the order of differentia tion. When applied to various spectrometric systems (21-33), differentia tion generally leads to two basic ad vantages: secondary, weak spectral features, e.g., slopes and peak shoul ders are emphasized and thus become

Figure 6. Emission spectrum of anthra cene (a) Without s m o o t h i n g , (b) W i t h quadratic fit. 1 7 point S a v i t z k y - G o l a y s m o o t h i n g . 0 . 2 μg/L·, a c quired in 3 s ( 1 0 0 a c c u m u l a t i o n s )

more easily identified and interpreted; and systematic errors, such as low-fre quency noise, drift in light source, continuum background and stray light, are removed. However, the sec ond advantage is achieved at the ex pense of enhancing random noise, e.g., white and other multiplicative noise sources (23). A variety of differentiation methods have been devised for single-channel spectrometric applications, but basi cally they all fall into two general categories; electronic modulation and wavelength modulation (22, 23). Al though wavelength modulation has been applied to multichannel imaging spectroscopy with a measurable de gree of success (33, 34), differentiation can be more easily accomplished by direct digital computation (18, 32, 33). It differs from wavelength modulation in that the derivative spectrum is not generated at a fixed wavelength, al though both techniques require the optimization of Δλ (differentiation step, DS). Imaging devices are more adaptable to direct digital computa tion differentiation than scanning spectrometers, since spectral data are already stored in digital format and wavelength registration is highly accu rate and not limited by the reproduc ibility of the scan rate. The effect of differentiation on SNR and peak distortion depends on the width of DS (Δλ), but in a manner fundamentally different from that in which smoothing is affected by the modulation depth (MD). This differ ence originates from the very opposite nature of the two data processing techniques, high-pass and low-pass fil tering, correspondingly. Differentia tion always increases the measure ment noise (multiplicative), approxi mately by a factor of 2 for each succes sive order (Figure 1) (24). Also, peak distortion (due to differentiation) re duces the signal magnitude. For small DS values, the finite derivative term, Δ//ΔΧ, more closely approximates the analytical derivative, dl/dX, but the noise decreases linearly with, R, the ratio of DS to the half-width of the spectral feature differentiated, at least within a 0.05-0.5 range (34, 35). Thus, the largest R value that does not re sult in excessive distortion should al ways be used; for most analytical stud ies where relative intensities are mea sured, some degree of distortion will generally be of little significance. De rivative spectroscopy will be most use ful for any application where system atic noise dominates, including cases where spectral band interferences are constant, known, or broader than the analyte band (24). The basic difference between differ entiation and smoothing at different "modulation widths" is illustrated by

Table I. Effect of Smoothing and Differentiation on SNR of Imaging Detectors Spectral features, FWHM

F = {SNR) MD = DS. smoothing/ ÎSNR no. of channels differentiation

Hg emission spectral line ( 3 - 4 channels)

5 9

0.98 0.82

Rhodamine B, emission band (40 channels)

5 9

8.2 3.5

their relative effect on the SNR of the imaging detectors (Table I). Improve ment of SNR with smoothing was pro portional to the square root of MD, but the deterioration of SNR with dif ferentiation was linearly inverse to DS. Only when R =a 1 was there no re duction in SNR upon differentiation (36), as shown for the Hg emission spectral line. Figure 7 demonstrates how the high-pass filtering effect of differentiation facilitates the identifi cation and recognition of minor spec tral features in the fluorescence emis sion spectrum of a methanol solution of an engine oil sample. Finally, an interesting application of direct digital computation differen tiation was demonstrated for liquid chromatography peak detection (37). The system consisted of a polychromator with a self-scanned photodiode array detector. It has been shown that a solute with an absorbance maximum in the UV can be effectively eliminat ed or deconvoluted from the chromatogram by plotting dA/d\ at the corresponding first derivative zero crossing point. The method allows res olution of grossly overlapping peaks without prior knowledge of the indi vidual spectra Spectral Correction and Sensi tivity Normalization. Intensity. Flu orescence spectra obtained with an SIT detector have incorrect spectral distributions because of variations in intensity that originate from thermal ly generated dark charge in the silicon target, channel-to-channel sensitivity variations, nonuniformity of the spec tral quantum efficiency of the photocathode, and nonuniformity of the spectral efficiency of the emission polychromator (principally due to the grating blaze). Of course, the last two effects are common to P M T detection systems as well. These sources of inac curacy may be eliminated, or compen sated for, to yield normalized (correct ed) fluorescence spectra. Dark charge variations are automat ically eliminated by subtracting a dark charge "background spectrum", stored in the OMA's memory, from each ac quired fluorescence spectrum. This is a standard practice with all OMA sys tems. In MFS applications, where de tectors are frequently operated at their full gain, fluorescence spectra are

ANALYTICAL CHEMISTRY, VOL. 50, NO. 1 1 , SEPTEMBER 1978 · 943 A

often partially obscured by impurities in the solvent, Raman scatter, Rayleigh scatter from suspensions, and even by fluorescence from a concomitant agent. In such cases a "blank spectrum" instead of a "dark spect r u m " is subtracted from sample spectra to produce corrected sample spectra with flat baselines wherein weak spectral features are more easily identified. The effect of channel-to-channel sensitivity variations originates from spatial response variations of the photocathode and the target (typically a few percent) and from gradual "shading", produced by the electron optics, which causes a reduction in sensitivity near the edges of the detector (approximately 15-20% decrease from center to edge). This effect can be ignored if relative spectral measurements are to be made. However, it can be corrected to first order by ratioing all analyte spectra by a uniformly illuminated (flat) spectrum. Spectroradiometric corrections of the emission polychromator/detector system are accomplished by replacing the sample with a white reflectance standard, irradiated by a calibrated lamp, e.g., tungsten (visible) or deuterium (UV) lamps. The 500-point ratio curve of the response spectrum of the system to the actual spectrum (from data supplied with the lamps) is stored in memory, and all subsequent emission spectra are divided by it to yield normalized spectra. The emission spectra of pyrene, uncorrected (a) and corrected (b) are shown in Figure 8. Wavelength. Inherent in most electrostatically focused electron image intensification stages, including that used in the SIT, is a pincushion distortion (aberration) which causes a 2-3% magnification variation from the center to the edge. For accurate wavelength registration, this aberration must be eliminated. This was done in software by recording a known atomic line spectrum (neon hollow cathode) and fitting the wavelength to the channel number. Without pincushion (e.g., silicon vidicon and photodiode array detectors), the fit would have been linear; the SIT, however, requires a third order polynomial fit indicating a second order dependence of magnification on channel position. When the nonlinearity of the spectrometer becomes appreciable, as in a prism spectrometer, this same procedure can be used, but with a higher order polynomial fit. Simultaneous Multicomponent Analysis. Various computational techniques have been devised for the deconvolution of spectral overlapping components in a mixture. Generally, all these techniques can be viewed as

Wavelength -

Figure 7. Emission spectrum of methanol extract of used engine oil sample (a) Normal, (b) First derivative, (c) Second derivative

curve fitting processes in which an experimental spectral response curve (fluorescence) is matched as closely as possible by a spectral response curve calculated by combining the response curves of the individual components, each with its proper weighing (convolution) factors. The most universal curve fitting is achieved with the least-squares s.atistical treatment performed in the matrix form (38), where the relative con-

Wavelength -

centration of each component (£), expressed as a matrix \C\i, is determined through its spectral characteristics expressed in the matrix \M\ij, and its fractional response at several measured wavelengths (/)> expressed in matrix \D\j. The relationship between these variables is given in Equation 4 Ci = t


(4)

Contrary to other fitting techniques

Wavelength

Figure 8. Emission spectrum of cyclohexane solution of pyrene (a) Uncorrected, (b) Spectrally corrected

\WJ\D\j

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NEW DESIGN

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·"!*'(

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Table II. Effect of Twentyfold Excess of A and DPS on Accuracy of ( P ) Determination (Computer-Least-Squares Statistical Multicomponent Analysis) Known concentration, ppm Mixture

A

DPS

1

10

10

Ρ 2.00

A

+ 0.08

-0.15

2.04

-0.03

+0.05

0.52

2

0

0

2.00

3

10

10

0.50

4

0

0

0.50

(39) where simultaneous equations are solved, here there is no need to deter mine the optimum number of re sponse values since the matrix \M\ij is general enough in form to be expand ed to include more standard spectra to determine more unknown compounds (40). It is necessary, however, that the total number of wavelength points equal or exceed the number of compo nents. However, there are a few require ments that must be satisfied to obtain an acceptable analytical accuracy: \M\j and \D\j must be accurately measured because small errors in their values cause larger errors in \C\i. Most serious errors are caused by a shift in wavelength calibration (registration) between standards and samples. A linear combination of the spectra of any two or more components must not produce a spectrum identical to that of any other component in the mixture; this is generally uncommon unless a very large number of compo nents (or a very complex matrix) is de convolved. Physical or chemical interferences between the components and/or the sample matrix are not allowed if they cause a change in the individual spec tral responses as compared to the standards. It is often very difficult to satisfy this last requirement because lumines cence measurements are amenable to various physical interferences such as intermolecular interactions, and static and dynamic quenching processes. Furthermore, at high concentrations, distortion of spectral features can be caused by intermolecular energy transfer processes, i.e., emission inten sities from compounds with higher en ergy excited states will be suppressed and those from compounds with lower energy excited states will be enhanced (41). The requirement for accurate wavelength calibration (registration) can, however, be met much more easi ly with electronic imaging devices be cause of their superior geometric accu racy when compared to that of most mechanical scanners. Other potential sources of inaccuracy include: drift in the xenon lamp light output between standard and mixture readouts, which can, however, be corrected with the source compensation techniques de scribed below, and errors in concen-

CIRCLE 214 O N READER SERVICE CARD


Calculated concentration. p p m DPS

Ρ

2.15 0.57

tration levels of both standard and mixture solutions due to evaporation and bleaching. Deconvolution measurements were carried out with a mixture of anthra cene (A), pyrene (P), and P-P'-diphenylstilbene (DPS) in cyclohexane. The effect of a twenty-fold excess of anthracene and DPS on the accuracy of pyrene determination is shown in Table II. The apparent negative con centration errors can be reduced by tightening the experimental control but can never be completely eliminat ed, because of wavelength calibration shifts and the very statistical nature of the technique. Clearly, however, the technique can be most useful in reduc ing the number and extent of chemical separation steps (40, 42) required for analyzing mixtures of known compo nents. Figure 9 shows the normalized (but not spectrally corrected) compos ite spectrum of a 1 ppm cyclohexane solution of A, P, and DPS and their deconvoluted corresponding pure emission spectra. The extent of spec tral distortion introduced by the pro cess increased as the SNR was re duced and the intracomponent dy namic range was increased, although at least partially, it could have been further reduced by data smoothing. Nevertheless, the "stripped" pyrene spectrum was easily identifiable even in a mixture ratio of 1:20:20 of P:A: DPS, respectively (Figure 9c). Source Compensated Spectrofluorometers. Various methods have been devised to compensate for flicker and drift of high-intensity CW light sources and for pulse-to-pulse varia tions characteristic of pulsed light sources such as xenon flash tubes and lasers. These methods include dualbeam, time-shared single detection, (43, 44), optical feedback (45-47), and dual-beam-dual-detector ratiometric detection (48). Each of these methods, however, suffers some inadequacy. The first method does not efficiently compensate for noise components with frequencies in the vicinity of the chopper modulation frequency and is incapable of compensating for pulseto-pulse variations when the pulse du ration is shorter than the chopper onoff period. The second method can handle low-frequency, drift-like varia tions of the source, but not noise com ponents at frequencies higher than

M i x t u r e : A, Ρ, D P S

Wavelength

Wavelength

Wavelength

Îife^TM»-·

>+*+> >'.

Figure 9. E m i s s i o n s p e c t r a of a n t h r a c e n e , p y r e n e , and d i p h e n y l s t i l b e n e (a) 1 ppm cyclohexane solution of the three c o m pounds. Experimental conditions: λ e x c , 340 nm; 400 accumulations; spectral bandpass, 3 nm. (b) Individual emission spectra of same three c o m pounds, (c) Computer-deconvoluted emission spectra of same three compounds

that of the source response frequency, determined by its thermoelectric time constant (49). The third method is useful for compensation of both highand low-frequency noise components, but it requires high-stability electron ic circuitry to avoid relative temporal performance variations, mainly drift, in the two detectors used. It is our intent, here, to briefly de scribe two alternative source compen sation methods which are rather unique to image detectors: constantenergy detection and dual-beam-dualtrack single detection. Constant-Energy Detection. The monochromatic excitation beam is split prior to reaching the sample and is monitored by a reference photodiode operated as a light energy inte

grator. When the integrator reaches a preset level proportional to the total energy of the incident beam, the accu mulation of signal by the multichan nel detector is terminated. Monitoring the monochromatic ex citation intensity, rather than the total energy output of the xenon lamp, ensures an efficient compensation of source fluctuations regardless of their origin, i.e., source intensity flicker, e.g., arc wandering, or variation in the spectral distribution. All fluctuations in the excitation beam will equally af fect the entire emission spectrum, si multaneously recorded by the SIT, since the excitation intensity acts merely as a multiplicative parameter in the emission expression of conven tional luminescence spectrometry. This mode of operation provides the means for the suppression of all noise components with frequencies higher than that of the SIT frequency band width, / = (2n 0.032 s ) - 1 ; (n is the number of consecutive accumulations or repetitive scans). For instance, an accumulation of signal for 32 s renders the SIT/reference-integrator system the equivalent of a low pass filter of 0.0015 Hz bandwidth. However, a small error (inversely proportional to the number of accumulations) can be introduced if termination of accumu lation occurs in the midst of a scan. This can be avoided if termination is done by electronically (or mechanical ly) shuttering the SIT, thereby "turn ing off" its photocathode and allowing the last scan to be completed, but without signal detection. Another potential source of error is drift in the dark charge of the SIT (the dark charge shot noise is insignif icant). Fortunately, the long thermal time constant of the SIT, approxi mately 30 min, significantly dimin ishes this effect. However, because of drift in the source light output, the total generated target dark charge varies from one measurement to an other since the system operates in the constant energy, not constant time, detection mode. Consequently, the number of "dark" accumulations to be subtracted (blank) must equal that of the signal itself. This can be done au tomatically by the OMA after shutter ing the SIT (electronically or mechan ically) at the end of each measure ment. To test the noise rejection capabili ties of the technique, a simulated "flickering" fluorescence emission source was constructed; an LED light source was electronically modulated at the frequency range of 1 Hz to 10 MHz, while maintaining constant the total irradiance. A statistical variance, F-test, was then conducted (20 mea surements per frequency) on the mea sured intensity signals. At a signifi-

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WILKS

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CIRCLE 77 O N READER SERVICE CARD A N A L Y T I C A L CHEMISTRY, V O L . 50, NO.

1 1 , SEPTEMBER

1978 ·

947 A

4561' 4105· 36493193· 2737228118241368 912 4560

Wavelength, nm

325

620

(472 nm)

1669 1502 1335 1168 ο 1001

II

Φ (Λϋ

|B

Hg (546)

Hg (405)

835 668

501 334-167-·^-*\»yurW»>f**vV Wavelength, nm

325

620

Figure 10. E m i s s i o n s p e c t r a (a) 1,1,4,4,-Tetraphenyl-1,3-butadiene (TPB). (b) Ovalene. Both spectra simultaneously acquired by SIT, operated in dual-beam detection mode

cance level of a = 0.02 and 0.05, there has been no reason to believe that a reproducibility (variance) difference existed between the irradiance levels recorded at the various "flicker" frequencies studied. Thus, the con stant-energy detection system can drastically improve the reproducibili ty of flicker-noise-limited measure ments by practically performing a

Anthracene

flicker-to-shot noise conversion, and operating the SIT in a constant-ener gy mode thus ensures the reproduc ibility of consecutive measurements. Dual-Beam-Dual-Track Single Detection. The area-array target of the SIT can be electronically scanned in a two-dimensional fashion; in the OMA-2 this pattern can be random. The target can be subdivided (by the

Ovalene

Scattered ^ Liant \ c

400 500 Emission Wavelength (nm)

600

Figure 1 1 . Total l u m i n e s c e n c e s p e c t r u m of a n t h r a c e n e and o v a l e n e 948 A · ANALYTICAL CHEMISTRY, VOL. 50, NO. 11, SEPTEMBER 1978

readout scanning beam) into 1-256 tracks, each of which functions as an independent optical multichannel de tector with up to 500 channels. The number of tracks that can be accurate ly used is limited by crosstalk or blooming of adjacent diodes, by pin cushion distortion of the electron image, and by the astigmatism of the spectrometer. The last two will result in a corresponding degradation in wavelength registration, particularly in the off-center tracks. Nevertheless, a proper selection of the target region to be scanned, e.g., central 5 X 8 mm region, allows a satisfactory use of at least 20-40 tracks. The two-track scan mode is particularly adaptable to dual-beam spectrometry. Because of the large number of discrete diodes in cluded in each of the two target tracks selected, the channel-to-channel sen sitivity variations in each track are relatively small, typically less than 5%. Because the two tracks are physically located on the same single-crystal wafer in the same vidicon tube, com mon-mode, low-frequency fluctua tions such as thermal drift are selfcanceling. Data acquisition and ontarget integration in both tracks are performed simultaneously; therefore, high-frequency noise components are also canceled. In pulsed laser spectrometry it is highly desirable to compensate not only for pulse-to-pulse intensity varia tions, but also for variations in the laser output spectral distribution. The "acquire-now-read-later" operation of

the SIT in the dual-beam-dual-track mode will normalize both parameters. Figure 10 shows the emission spec tra of l,l,4,4-tetraphenyl-l,3-butadiene (TPB) and ovalene, simultaneous ly acquired by the two tracks. The light emitted from both sources was conducted by two separate opticalfiber pipes to locations along the verti cal slit of the polychromator, which correspond to the position of the two selected tracks along the focal plane of the spectrometer (and the detector faceplate).

exe. = 260 nm

I I

Total Luminescence Spectrometry

The relative spectral distributions, emission and excitation, of a pure compound are independent of the ex citation and emission wavelengths, correspondingly (within the appropri ate spectral range characteristic of that compound). The spectral charac teristics of a mixture, however, are de termined by both parameters and by the relative concentrations of the indi vidual compounds. Spectral interpre tations of mixtures can be further hampered by co-occurrence of fluores cence and phosphorescence. The use of spectral matrices, i.e., λ em. vs. λ exc, for spectral characteriztion of complex mixtures has been suggested (50) and applied (51, 52) to various fluorescence studies. Recently, a system has been devised that projects the entire spectral matrix of a mixture at the focal plane of a con ventional spectrometer, where it can be simultaneously detected with an area array imaging device (8). This de tection method has some distinct ad vantages over single-channel scanners designed for similar purposes (53). Nevertheless, the two-dimensional spectrometric use of an imager can be limited by aberrations in the spec trometer and by pincushion distortion and blooming in the detector (vide infra). Other potential sources of inac curacy include stray light from reflec tions in both the spectrometer and the detector, detector deviation from lin earity, and insufficient dynamic range and self-absorption and energy trans fer mechanisms in solutions. Some ob vious applications of the technique in clude characterization of complex (fluorescing) mixtures, particularly under conditions where more spectral information becomes available, e.g., Shpolskii-effect, quasi-line emission spectra, and identification of coeluted compounds, incompletely separated by the liquid-chromatographic col umn. The capability to electronically shutter an imager, e.g., SIT, can pro vide additional identification in the form of emission decay times.

300 nm

500 nm Wavelength

Figure 12. Emission spectra of methanol extract of used engine oil sample simul taneously acquired while sequentially stepping excitation monochromator

The OMA-2 (SIT) system is unique ly adaptable to total luminescence spectrometry: • It has a wide linear dynamic range, in excess of 104, although under high light level illumination it may be reduced to scatter and reflection of light inside the imaging sector of the detector (veiling glare). • Preamplifier noise is very low, ap proximately 2000 electron rms. • The spectral range of the detector extends across the near VUV to near IR region. • The area array target (detector) can be read out in a pseudorandom fashion; that is, preselected "scan pat terns" across the target can be ran domly accessed. Thus, only relevant information is stored. Pseudorandom access readout can also significantly reduce spectral interferences caused by high-intensity neighboring spectral features. While the weak analyte spec tral features are integrated on target to enhance SNR, the strong interfer ing features are read off (erased) from the target by the scanning beam. Using this method the "blooming" (cross-talk between neighboring chan nels) effect is drastically reduced. • A TV monitor display allows a semiquantitative inspection of the contours of the spectral matrix. Finally, it has occurred to us, and to others (54), that diagonal scans across the spectral matrix provide spectral information identical to that obtained by synchronous luminescence systems (41, 55), but without mechanical scan ning and with simultaneous data ac quisition. Also wavelength difference


between the emission and excitation monochromators, Δλ, can be selected in software after data acquisition; therefore, there is no need for multiple scanning procedures. Figure 11 shows the total luminescence spectrum of anthracene and ovalene. The spec trum, obtained with an experimental system made up of two 0.3 mm, EG&G PARC Model 1208 polychromators, has 28 tracks with 125 data points per track (every four channels were grouped). With the OMA-SIT system, total luminescence spectra can also be ac quired in a somewhat slower but more accurate and simpler manner. The technique employs an electromechani cal scanning method; emission spectra in a predetermined spectral range are simultaneously acquired and stored in memory while the excitation mono chromator is stepped. Using a fast scanning excitation monochromator, a total luminescence spectrum with 100 tracks could be acquired and stored in a few seconds. Of course, in many cases longer acquisition times are necessary to ensure a satisfactory SNR performance. Figure 12 shows a sequence of emission spectra achieved in that manner. Laser Applications

Laser-induced molecular fluores cence has been shown to be a very sen sitive and selective means for the de termination of ultralow traces of lumi nescing compounds (56, 57). Laser light is bright (high power), coherent in nature (easily focused on small

s a m p l e s ) , a n d is efficiently t r a n s m i t t e d t h r o u g h optical d i s p e r s i o n sys t e m s . Also, p u l s e d lasers allow t e m p o ral d i s c r i m i n a t i o n b e t w e e n fluores cence a n d scattering. T h e O M A - S I T s y s t e m is p a r t i c u l a r ly s u i t e d for pulsed-laser-induced-fluorescence b e c a u s e t h e e n t i r e emission s p e c t r u m (per pulse) is s i m u l t a n e o u s l y m o n i t o r e d , p u l s e - t o - p u l s e source com p e n s a t i o n is easily achieved, o p e r a t i o n in t h e d u a l - t r a c k m o d e allows a q u a n t i t a t i v e analysis ( s a m p l e vs. s t a n d a r d ) b a s e d on a single pulse, a c c u r a t e aver aging of s p e c t r a o b t a i n e d with m u l t i ple pulses ( m u l t i p l e x a d v a n t a g e ) is simple, s a m p l e bleaching (due to m u l tiple pulse exposure) can be avoided, a n d t h e S I T can be electronically s h u t t e r e d (gate > 4 0 n s ) . Recently, it h a s been a r g u e d a n d d e m o n s t r a t e d t h a t t h e i n t e g r a t e d flu orescence emission o b t a i n e d u p o n c o m p l e t e bleaching of a c o m p o u n d is c o n s t a n t a n d independent on its fluo rescence q u a n t u m efficiency ( F Q E ) , a b s o r p t i o n cross section, a n d t h e in t e n s i t y a n d d u r a t i o n of t h e excitation illumination (58). T h u s , only t h e i n t e g r a t e d fluorescence signal is essential for q u a n t i t a t i v e analysis. W h e n highly fluorescing tagging molecules are used (and t h e tagged complex is low fluo rescing), it is possible to d i s c r i m i n a t e t e m p o r a l l y ( S I T gating) b e t w e e n t h e r a p i d l y bleached (fast decay) high F Q E tag a n d t h e low F Q E complex. T h e S I T - O M A s y s t e m is a parallel g a t a b l e i n t e g r a t o r d e t e c t o r , ideally s u i t e d for such a p p l i c a t i o n s . T h e gatability of t h e S I T provides a very c o n v e n i e n t m e t h o d for m e a s u r e m e n t s of (laser-induced) p h o s p h o rescence decay t i m e s , b u t it is too slow for analogous fluorescence s t u d i e s . Nevertheless, the system has been successfully applied t o s p e c t r o m e t r i c m e a s u r e m e n t s of u l t r a s h o r t lifetime m e a s u r e m e n t s of molecular excited s t a t e s (59); t h e light i n c i d e n t on t h e t a r g e t was t i m e d i s p e r s e d with a n ech elon, vertically across t h e t a r g e t , while t h e s p e c t r a l information was d i s p e r s e d horizontally. A few t e n s of s p e c t r a , a few picoseconds a p a r t , were recorded

Yair Talmi

D. C. Baker

s i m u l t a n e o u s l y for further d a t a p r o cessing a n d m a n i p u l a t i o n s . Finally, a n i n t e r e s t i n g a p p l i c a t i o n of t h e S I T - O M A s y s t e m is for r e m o t e d e t e c t i o n of oil spills, using laser-ex cited R a m a n b a c k s c a t t e r i n g a n d backs c a t t e r e d fluorescence (60). G a t i n g t h e S I T (2-μδ g a t e pulse) in s y n c h r o n i zation with t h e laser firing r e d u c e d t h e b a c k g r o u n d from s e a w a t e r t o a level low e n o u g h t o allow d a y t i m e o p eration.

Acknowledgment W e a c k n o w l e d g e J o h n B a r b y of E G & G P A R C for his a s s i s t a n c e in t h e design a n d c o n s t r u c t i o n of s o m e of t h e experimental setup.

Literature Cited (1) C. A. Parker, "Photoluminescence of Solutions", American Elsevier, New York, N.Y., 1968. (2) G. G. Guilbault, "Practical Fluores cence—Theory, Methods and Tech niques", Marcel Dekker, New York, N.Y., 1973. (3) J. D. Winefordner, S. G. Schulman, and T. C. O'Haver, "Luminescence Spec troscopy in Analytical Chemistry", Wiley, New York, N.Y., 1972. (4) E. I. Wehry, Ed., "Modern Fluores cence Spectroscopy", Vols 1 and 2, Ple num Press, New York, N.Y., 1976. (5) G. M. Barenboim, A. N. Domanskii, and Κ. Κ. Turoveror, "Luminescence of Biopolymers and Cells", Plenum Press, New York, N.Y., 1969. (6) I. B. Berlman, "Handbook of Fluores cence Spectra of Aromatic Molecules", Academic Press, New York, N.Y., 1971. (7) P. Froehlich, Appl. Spectros. Rev., 12, 83 (1976). (8) D. W. Johnson, J. B. Callis, and G. D. Christian, Anal. Chem., 49, 747A (1977). (9) K. W. Busch, N. G. Howell, and G. H. Morrison, ibid., 46, 575 (1974). (10) M. J. Milano, H. L. Pardue, T. E. Cook, R. E. Santini, D. W. Margerum, and J. M. T. Raycheba, ibid., ρ 374. (11) Y. Talmi, ibid., 47, 658A, 697A (1975). (12) R. P. Cooney, G. D. Boutilier, and J. D. Winefordner, ibid., 49, 1048 (1977). (13) R. P. Cooney, T. Vo-Dinh, G. Walden, and J. D. Winefordner, ibid., ρ 939. (14) Η. Steinhart and J. Sandmann, ibid., ρ 950. (15) D. C. Jadamec, Jr., W. A. Saner, and Y. Talmi, ibid., ρ 1316. (16) Y. Talmi, Am. Lab., p 79 (Mar. 1978). (17) A. E. McDowell and H. L. Pardue,

J. R. Jadamec

W. A. Saner


Anal. Chem., 49, 1171 (1977). (18) A. Savitzky and M. J. E. Golay, ibid., 36, 1627 (1964). (19) J. Steiner, Y. Termonia, and J. Deltour, ibid., 44, 1906 (1972). (20) C. G. Enke and T. A. Nieman, ibid., 48, 705A (1976). (21) A. Griese and C. French, Appl. Spec tros., 9,78(1955). (22) R. N. Hager, Jr., Anal. Chem , 45, 1131AU973). (23) G. L. Green and T. C. O'Haver, ibid., 46,2191 (1974). (24) T. C. O'Haver and G. L. Green, ibid., 48,312(1976). (25) W. Snelleman, W. Rains, K. Yee, H. Cook, and O. Menis, ibid., 42, 394 (1970). (26) R. C. Elser and J. D. Winefordner, ibid., 44,698(1972). (27) J. W. Strojek, D. Yates, and T. Kuwan&,ibid., 47, 1050(1975). (28) G. Bonfiglioli and P. Brovetto, Appl. Opt., 3, 1417 (1964). (29) F. Arames and A. Rucci, Rev. Sci. Instrum., 37, 1696 (1966). (30) J. C. McWilliam, Anal. Chem., 41,674 (1969). (31) H. L. Pardue, A/ E. McDowell, D. M. Fast, and M. J. Miiano, Clin. Chem., 21, 1195(1975) (32) F. Grum, D. Paine, and L. Zoeller, Appl. Opt., 11,93(1972). (33) T. E. Cook, H. L. Pardue, and R. E. Santini, Anal. Chem., 48, 451 (1976). (34) T. E. Cook, R. E. Santini, and H. L. Pardue, ibid., 49, 871 (1977). (35) R. J. Hanisch, G. P. Hughes, and J. R. Merrill, Rev. Sci. Instrum., 46, 1262 (1975). (36) Η. Η. Arsenault and P. Marmet, ibid., Rev. Sci. instrum., 48, 512 (1977). (37) M. J. Milano and E. Gurshka, J. Chromatogr., 133, 352 (1977). (38) J. C. Sternberg, H. S. Stillo, and R. H. Schwendeman, Anal. Chem., 32, 84 (1960). (39) J. Sustek, ibid., 46, 1676 (1974). (40) M. J. Milano and Κ. Υ. Kim, ibid., 49, 555 (1977). (41) P. John and I. Soutar, ibid., 48, 520 (1976). (42) A. E. McDowell, R. S. Harner, and H. L. Pardue, Clin. Chem., 22, 1862 (1976). (43) R. E. Anacremon and Y. Ohnishi, Appl. Opt., 14,2921 (1975). (44) T. J. Porro and D. A. Terhaar, Anal. Chem., 48, 1103A (1976). (45) H. L. Pardue and S. N. Denning, ibid., 41,986(1969). (46) H. L. Pardue and P. A. Rodriquez, ibid., 39,901 (1967). (47) P. A. Loach and R. J. Lloyd, ibid., 38, 1709 (1966). (48) J. D. Defreese and H. V. Malmstadt, ibid., 48, 1530(1976). (49) B. Chance, D. Mayer, N. Graham, and V. Legalais, Rev. Sci. Instrum., 41, 111 (1970). (50) G. Weber, Nature (London), 190, 27 (1961). (51) W. P. Williams, N. R. Murty, and E. Rabinowitch, Photochem. Photobiol., 9, 455(1969). (52) A. P. Bentz, Anal. Chem., 48, 455A (1976). (53) L. P. Geiering and A. W. Hornig, Am. Lab., p 113 (Nov. 1977). (54) H. L. Pardue et al., private communi cation, April 1978. (55) T. Vo-Dinh, Anal. Chem., 50, 396 (1978). (57) J. H. Richardson and S. M. George, ibid., 50,616(1978). (58) T. Hirschfeld, Appl. Opt., 15, 2965, 3135(1976). (59) T. L. Metzel, P. M. Rentzepis, and J. Leigh, Nature, 182,238(1976). (60) T. Sato, Y. Suzuki, H. Kashiwagi, M. Nanjo, and Y. Kakui, IEEE J. Oceanic Eng., OE-3 (1), 1 (Jan. 1978).

Fluorescence Spectrometry with Optoelectronic Image Detectors

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