(3) Chem. Eng. News, 55 (21), 6 (1977). (4) R. P. Taubinger, Analyst (London), 94, 628-633 (1969). (5) D. W. Beesing, W. P. Tyler, D. M. Kurtz, and S. A. Harrison, Anal. Chem.,
21, 1073 (1949). (6) M. Wronski. and E. Bald, Chem. Anal. (Warsaw), 15, 357-359 (1970). (7) A. J. Gorerea, Gas Chromatogr., 3, 138 (1965). (8) (9) (10) (11) (12)
C. E. R. Jones, Proc. Gas Chromatcgr. Symp., 3rd, Edinburgh,501 (1960). H. Nestler and W. Berger, Chem. Tech. (Berlin), 17, 169 (1965). W . L. Bird, and C. H. Hale. Anal. Chem., 24, 586-587 (1952). S. I . Meklev. Aferbneft Kohz. 6, 33-34 (1968). I. G. Sevast and A . P. Tomilov, Zavod. Lab., 32 1210 (1966).
D. Buckley and T. R . Crompton, Analyst(London), 99, 76 (1968). L. Fujiwara, Sitzungsber. Abh. Naturforsch. Ges. Rostock, 6, 33 (1914). G. A. Fugg, Anal. Chem., 36, 1532 (1966). F. Feigl, "Spot Tests in Organic Analysis". Van Nostrand Company, Inc., Princeton, N.J. 1956, p 280. (17) E. Kroeller, Dtsche Lebensm-Rundsch., 66, 11 (1970). (18) E. D. Smith, and D. M. Mathews, J . Chem. Educ., 44, 757 (1967).
RECEIVED for review June 28,1977. Accepted October 3,1977.
Determination of Optimum Compromise Flame Conditions in Simultaneous Multielement Flame Spectrometry D. F. Brost, 6. Malloy, and K. W. Busch" Department of Chemistry, Baylor University, Waco, Texas 76703
A composite response parameter, PJ,is developed for optimization of compromise excitation conditions in simultaneous multielement flame spectrometry. PJ is a direct measure of overall instrumental response for a particular multielement sample and is therefore sensitive to the detection powers and concentrations of each analyte species. Optimum compromise conditions are selected by simple maximization of the P J response surface. The behavior of P , is illustrated with experimental measurements made with a vidicon flame spectrometer on an ideal sample containing the spectrochemically divergent elements manganese and molybdenum. Practical application to several types of multielement samples is discussed on the basis of these measurements.
Simultaneous multielement analytical methods have played a n important role in survey analyses where information on a large number of elements is desired. Traditionally, this role has been filled by such techniques as spark-source mass spectrometry, neutron activation analysis, wavelength dispersive x-ray fluorescence, and emission spectrometry. Recently, there has been an interest in extending the capability of traditionally single element methods, such as flame techniques, to include simultaneous multielement determinations ( 1 , 2). One of t h e problems inherent in multielement flame spectrometry is the selection of the optimum compromise excitation conditions for the elements under consideration. Although several statistical methods could be applied to this problem, the simplest technique would involve some form of response surface analysis utilizing a single response parameter which directly measures the overall effectiveness of the instrument for the simultaneous multielement determination of all analytes in the sample. If such a composite parameter were available, simple maximization of the response surface would lead directly to the optimum compromise conditions without going through complex mathematical analysis of individual linear regression equations. This paper describes a n effective joint response parameter, developed from probability considerations, as well as a simple method for its use in the optimization of excitation conditions for simultaneous multielement determinations by flame emission.
THEORY The need for the determination of compromise excitation conditions in simultaneous multielement flame emission 2280
ANALYTICAL CHEMISTRY, VOL. 49, NO. 14, DECEMBER 1 9 7 7
spectrometry arises from differences in the chemical and physical behavior of elements in the flame. Because of these differences, optimum detection power for some elements may be obtained by observing a volume element close to the burner top in a fuel-lean flame, while others may require observation higher in the same flame, or under more fuel-rich conditions. Since the simultaneous determination of all elements in a given sample is presently restricted to one set of conditions, a compromise must be found which provides adequate detection power for all analyte species. The severity of the necessary compromise depends upon the spectrochemical behavior of the individual elements as well as their respective concentrations in the sample. If all the elements are present in concentrations far in excess of their poorest detection limits over the useful range of experimental conditions, the selection of a particular set of conditions is not critical for their determination. On the other hand, if two or more spectrochemically divergent elements are present in a sample in low concentrations, the selection of an appropriate compromise becomes very important. The optimum excitation conditions for any element in flame emission spectrometry are those which yield the minimum possible detection limit. Under these conditions, the signal-to-noise ratio (S/N) is a t a maximum for a given concentration, and the emitted intensity a t the wavelength of interest is measured with the greatest possible precision. All that is needed, therefore, for optimization in single element determinations is the location of the minimum experimentally obtainable detection limit. For the case of multielement optimization, the problem becomes more complex. In order for a response parameter t o be useful for optimization of multielement systems, it must satisfy two criteria. First, the parameter must be a function of the detection power of the instrument for each element just as in the single element case. Second, it must be sensitive t o the prevailing concentrations of the analyte species. The necessity of concentration dependence is a direct consequence of the basic need to compromise. Consider a model sample containing two elements whose hypothetically divergent spectrochemical behaviors are shown in Figure 1 for various oxidant-to-fuel ratios (Ox/Fuel) at a constant observation height. The individual optimum for element X occurs a t low values (fuel-rich), while that for element Y occurs a t high values (fuel-lean). If element X is present in very high concentration in the sample (e.g., 100 ppm), its presence will easily be detected a t any Ox/Fuel setting. If element Y is present at very low concentration (e.g.,
-L i
I
2o I5
"
"
"
'
r
'
h/
l
x: 0 8
Ox/Fuel
0
04-
/
" I
L
Q
03-
02
I
k
(ARBITRARY UNITS)
Figure 1. Hypothetical variation of detection limit with oxidant-to-fuel ratio at constant observation height for elements X and Y
T
-
-
0 lr L
Li
A
1
1
Samples
2
3
Ox/Fuel
above
4
5
l
i
7
e
s
(ARBITRARY U N I T S )
Figure 3. Response parameter curves for elements X and Y
Table I. Experimental Facilities External optics Cd,,, -
- - - - - - - - - ---_
Burner
S a m p l e s below Detection L i m i t
Monochromator
Figure 2. Line segment diagram for element i
5 ppm), it will only be detected a t Ox/Fuel settings above six. Clearly, for elements X and Y to be determined simultaneously, the detection power of X will have to be sacrificed in order to observe both elements. Before describing a multielement optimization parameter, it is necessary to analyze the single element case from a probability viewpoint. Consider the line segment diagram in Figure 2 for element i. The entire length of the line represents the total number of possible samples of different concentration which can occur within the sample space from 0 to C,. T h e segment from Cd,, to C, represents the total number of possible samples which are greater than or equal to the detection limit. In other words, element i will be "observed" only in those samples where the concentration is above C d i s . The probability of detecting the presence of element i in a random sample increases or decreases with the length of Cd&,. The following response parameter can now be defined:
p. =
ci
- cdl,i n
; P i = 0 when Cdl.i> Ci
Li
P,is confined to values from 0 to
1 and represents the probability of observing element i in a randomly selected sample, if all concentrations are equiprobable. As a single element response parameter, P, is a maximum when Cdl,, has its lowest value. Since this condition corresponds to the best possible reproducibility of measurement. the maximum in the P, surface, computed from detection limit measurements at each set of excitation conditions, represents the optimum conditions for the determination of element i. For a sample containing n elements, the joint probability of observing all the analyte species simultaneously in a random sample can be computed from
where PJ a t a given set of conditions is the product of the individual response functions, P,, computed from detection limit measurements at the same set of conditions. Analysis of Equation 2 reveals that the joint probability of observation, PJ,fulfills all the requirements of a multielement response parameter as discussed above. T h a t is, P J is calculated from the individual detection limits of the elements in the sample and from an appropriate estimate of their respective concentrations. A joint response surface for any
Detector Optical multichannel analyzer Readout Flow meters
5-cm UV-grade fused silica lens with 10-cm focal length, Oriel Corp. Varian Techtron 5-cm slot burner for nitrous oxide-acetylene Spex, Model 1870, 0.5-cm CzernyTurner spectrograph, f i 6 . 9 , with 1200 groovesirnm grating blazed for 300 nm. Reciprocal linear dispersion 1.6nm/mm in the first order Model 1 2 0 5 D silicon intensified target detector head, Princeton Applied Research Corp. Model 1205A, Pyinceton Applied Research Corp. Tektronix oscilloscope, 604 Monitor Brooks Full-View rotameters calibrated for nitrous oxide and acetylene, Brooks Instrument Division
multielement sample can thus be constructed by simply computing PJ for several combinations of Ox/Fuel and obill correspond servation height. The maximum in this surface w to that set of conditions giving the greatest possible compromise detection power for all elements in the sample. The degree to which a given element influences the location of the optimum depends upon the proximity of its expected sample concentration, C,, to its detection limit, Cdl,,, Consider again the model binary system depicted in Figure 1. T h e response parameter curves Pxand Py,computed from these detection limits, are shown in Figure 3 for a sample where Cx = 100 ppm and Cy = 10 ppm. PJ is also shown. Since Cx is much greater than Cdl,X at every Ox/Fuel setting, Pxremains relatively constant and a t high valu.es. On the other hand, Cy is either close to or less than Cdl,y. Because of this Py is quite sensitive to Ox/Fuel and therefore is the determining factor in the shape and maximum of PJ. The practical use of PJ for flame emission will be discussed on the basis of experimental measurements on the spectrochemically divergent elements manganese and molybdenum.
EXPERIMENTAL Apparatus a n d Experimental Conditions. The vidicon flame spectrometer used in this study was similar to that described previously (3-5). Details of the operat ion of this system can be found in the cited references. A description of the spectrometer components can be found in Table I. This investigation requires the determination of reproducible detection limits which are functions only of the oxidant-to-fuel ratio and the flame volume element observed by the optical system. In order to accomplish this, the other instrumental variables were held constant at settings which were known to be compatible with good general sensitivity. The monochromator was adjusted so that the wavelength range between 390 and 410 nm was focused on the detector faceplate. ANALYTICAL CHEMISTRY, VOL. 49, NO. 14, DECEMBER 1977
2281
Detection Limits. The best linear relationship passing through the origin of the S/Nvs. concentration plot was determined by using a slope averaging procedure. The detection limit was obtained from this line and was taken as the concentration corresponding to a S/N of 2. Each detection limit was determined in this manner a minimum of 5 times for each set of measurement conditions.
Table 11. Experimental Flame Conditions Molar
Flow rates (L/min) N>O C,H, 9.5 9.5 9.5 9.5
ox i dan t-to-
fuel ratio
5.3 5.7 6.0 6.5
1.8
1.7 1.6 1.5
The lens and burner assembly were positioned to produce a 1:l image of the flame on the entrance slit. The slit was set at 5 fim and the height was maintained at 2 mm. A neutral density filter with an absorbance of 0.3 was placed in front of the entrance slit. This filter, in combination with the slit dimensions, provided a light level such that 500 frame scans could be accumulated over the entire range of measurement conditions without exceeding the capacity of the optical multichannel analyzer memory. A premixed nitrous oxide-acetylene flame was used in this investigation. The flame conditions were altered by varying the fuel flow while maintaining the oxidant flow at 9.5 L/min. Table I1 gives the fuel and oxidant flow rates as well as the molar oxidant-to-fuel ratios, p, for the various flame conditions employed. A stoichiometric nitrous oxide-acetylene flame has a p value of 3.0 (6). The oxidant flow produced a constant solution aspiration rate of 5.4 mL/min. Determination of Detection Limits. Signal-to-Noise Ratios. S/Nvs. concentration curves were constructed for manganese and molybdenum at each combination of observation height and oxidant-to-fuel ratio from the background-corrected spectra of two single-element standard solutions. Each spectrum was obtained as follows. A blank spectrum was collected by nebulizing a distilled water blank containing 1000 ppm Cs into the flame for 500 accumulation cycles and storing the resulting spectrum in memory B. The sample spectrum was similarly obtained and stored in memory A using a simple aqueous standard solution of the element in question which also contained 1000 ppm Cs as an ionization buffer. The background-corrected spectrum was observed using the A minus B mode of the optical multichannel analyzer. The signal-to-noise ratio in a given spectrum was determined from the number of counts accumulated in the channel corresponding to the peak of the spectral line, and the counts in the ten adjacent channels on either side of the spectral line. The average of the counts in the 20 background channels was taken and subtracted from the counts at the line peak to yield the signal. The rms noise was taken as the standard deviation of the counts in the background channels. Concentrations were chosen which yielded a maximum S / N of 25 at each set of measurement conditions for each element investigated. This resulted in greater reproducibility when extrapolating the curve back to the detection limit. In order t o ensure linearity of the standard curve, the intercept on the S / N axis was monitored. Concentrations were taken as acceptable when the intercept was within f l S / N unit of the origin.
R E S U L T S AND DISCUSSION Experimentally determined detection limits for manganese and molybdenum are shown in Table 111. Single element response parameter values, P& and PMo,were calculated using Equation 1 for several arbitrary concentrations which may be encountered in an analytical sample solution. P L f n for manganese concentrations of 0.03 and 1.0 ppm and Phfo for molybdenum concentrations of 0.5 and 10 ppm are given in Table IV. Examination of the individual detection limit surfaces (Table 111),reveals that maximum detection power occurs a t different sets of conditions for the two elements. Manganese response is best in a fuel-lean flame ( p = 1.80-1.70) a t observation heights between 5 and 10 mm. Optimum conditions for molybdenum occur in a fuel-rich flame ( p = 1.60-1.50) a t approximately the same range of observation heights. As has been previously indicated, this behavior is reflected in P M n and PMo (Table IV) for all the chosen sample concentrations. T h e response toward both elements changes slowly and evenly as conditions are varied about the individual optima. Also, as is indicated in Table IV, each point on the response surfaces has its own degree of uncertainty arising from the uncertainties in the corresponding detection limit measurements. For these reasons, it is more realistic to simply locate the region of optimum joint response than to attempt to identify a single set of conditions which represents a statistically unique optimum. Joint response surfaces are shown in Table V for three combinations of PMnand P M ~ The . uncertainties shown represent the most probable error in PJ computed from the precision indices of P M n and PMo. These results clearly demonstrate the response of PJ t o samples of varying composition. When C& is low and Chfois high in relation to their respective detection limits (Table Va), optimum compromise conditions are located in the region of maximum detection power for manganese. Likewise, when only molybdenum is present in critically low concentration (Table Vb), PJ indicates optimum conditions which overwhelmingly favor molybdenum response. In a sample which contains both elements in low amounts (Table Vc), the maximum in PJ moves toward conditions which partially sacrifice the individual detection powers of each in order to indicate the best compromise for the determination of the multielement system.
Table 111. Manganese and Molybdenum Detection Limits Observation height ( m m above burner top) P
5
1.50 1.60 1.70 1.80
0.06 i O . O l a s b 0.027 t 0.005 0.012 t 0.002 0.010i 0.002
10
15
20
0.06 i 0.01 0.024 i 0.005 0.021 i 0.003 0.020 0.003
0.05 i 0.01 0.028 i 0.003 0.027 i 0.005 0.029 i- 0.003
M n detection limit surface
*
0.06 0.01 0.022 t 0.006 0.016 * 0.002 0.016 + 0.003
*
Mo detection limit surface 1.50 1.60 1.70 1.80
0.12 0.11 0.18 0.53
t i i i
0.02 0.03 0.04 0.06
0.09 t 0.02 0.12 t 0.03 0.35 r 0.07
0.13 i 0.04 0.3 i 0.1
3*1
14t 2
2.7
t
0.3
0.20 i 0.01 1.1 i 0.2 13* 3 39 * 6
a All uncertainties are represented as the standard deviation of the mean of replicate measurements at the 95% confidence level. All detection limits are in parts per million.
2282
ANALYTICAL CHEMISTRY, VOL. 49, NO. 14, DECEMBER 1977
Table IV. Single Element Response Parameter Values Observation height ( m m above burner) 5
P
15
10
20
Mn response surface for C M =~0.03 ppm 1.50 1.60 1.70 1.80
0 0.10 0.60 0.67
0 0.27 0.47 0.47
0,17a 0.07 0.07
i
i i
i
i i
0 0.20 0.30 0.33
0.20 0.07 0.10
Mn response surface for C M n 1.50 1.60 1.70 1.80
0.94 f 0.01 0.973 i 0.005 0.988 i 0.002 0,990 i 0.002
1.50 1.60 1.70 1.80
0.76 f 0.04 0.78 c 0.06 0.64 i 0.08 0
1.50 1.60 1.70 1.80
0.988 0.989 0.982 0.947
0.94 i 0.01 0.978 i 0.006 0.984 t 0.002 0.984 i 0.003
=
t i
i
0.17 0.10 0.10
0 0.07 0.10 0.03
t i t
0.10 0.17 0.10
1.0 ppm 0.94 i 0.01 0.976 i 0.005 0.979 f 0.003 0.980 i 0.003
0.95 t 0.01 0.972 i 0.003 0.973 I0.005 0.971 i 0.003
Mo response surface for C M =~ 0.5 ppm 0.82 0.76 0.30 0
i i i
0.04 0.06 0.14
0.74 0.40 0 0
t i
0.08 0.20
0.60
f
0.02
0 0 0
Mo response surface for C M o = 10.0 ppm
a
i t i i
0.002 0.003 0.004 0.006
0.991 i 0.002 0.988 i 0.003 0.965 i 0.007 0.70 -f 0.10
0.987 i 0.004 0.97 i 0.01 0.73 i 0.03 0
0.980 i 0.001 0.89 f 0.02 0
0
All uncertainties are represented as the standard deviation of the mean at the 95% confidence level.
Table V . Multielement Response Parameter Values Observation height ( m m above b u r n e r ) P
10
5
15
20
A. Response surface for C M =~ 0.03 ppm and C M =~ 1 0 ppm 0 0 1.60 0.10 c 0.17a 0.26 i 0.20 0.45 f 0.06 1.70 0.59 i 0.07 1.80 0.63 t 0.07 0.33 i 0.08
0 0.16 0.06 t 0.09 & 0.07 0 0 0 0
1.50
0.19 0.22
i
B. Response surface for C M =~ 1.0 ppm and Cbl0 = 0.5 ppm 1.50 0.71 c 0.04 1.60 0.76 i 0.06 1.70 0.63 t 0.08 1.80 0
0.77 i 0.04 0.70 i- 0.08 0.57 i- 0.02 0.74 i 0.06 0.39 i 0.20 0 0 . 3 0 k 0.14 0 0 0 0 0
C. Response surface for C M n = 0.03 ppm and CM,, = 0.5 ppm
1.50
0 1.60 0.08 i- 0.13 1.70 0.38 T 0.06 1.80 0
0 0 0 . 2 0 ? 0.15 0.08 i- 0.08 0.14 i 0.07 0 0 0
0 0 0 0
Interferences. In order to correctly apply Equations 1 and 2 to locate the optimum compromise conditions for t h e simultaneous determination of a particular set of elements, care must be taken in the determination of the detection limits. I t is well known that many general and specific interferences may be present in a sample which could alter instrumental response toward one or more of the analyte species. For this reason, the optimum obtained by maximizing Pa is valid only if t h e detection limits are measured in the presence of the sample interferences. This, however, does not present a significant problem, since the primary requirement of a multielement analysis is the capability of preparing multielement standards which mimic the behavior of all analytes in the sample. These standards can then be used to determine the detection power of the instrument for each element. Thus
the location of the correct optimum compromise conditions by the joint probability of observation and the accurate determination of analyte concentrations in the final analysis are dependent upon the same basic capability. Selection of C,. As has previously been discussed, the determination of the optimum compromise conditions via PJ requires that an estimate of each analyte concentration, C,, be available. The closer these estimates are to the actual case, the more accurate will be the selected optimum. There are several practical approaches to the selection of C, and each has its own degree of complexity and reliability. First, if typical concentration ranges are available for samples of a given type and origin, the central value in the range for each element can be used as its C,. Since no measurements are required, this method is by far the simplest, and can be sufficiently accurate when the expected concentration ranges are narrow. Serious error may result in the determination of P J if actual analyte concentrations are a t the extremes of a wide range for one or more elements Second, a rough survey determination of the elements in a given sample could be carried out by any analytical technique, and the results used as C,. Although this approach is more time-consuming, the results are usually more reliable than the above technique, even if the analysis is accurate to only 10-2070. Finally, if enough sample is available, the sample dilution method as discussed below can be employed to eliminate C, from Equation 1. Sample Dilution Technique for Relative Detection Limit Determination. As stated above, C, represents an analyte concentration in the actual sample solution. If this solution (where C, is assumed to be on t h e linear portion of the calibration curve) is serially diluted, and S/N measurements are made a t each dilution, a curve of S / N vs. the fraction of C, can be constructed. As indicated in Figure 4, point A represents the fraction of the original concentration which yields a S / N of 2. At this point, the element in question is present in the sample at its detection limit. Mathematically,
Cdl,,= A C ,
(3)
where A is the factor by which C, must be diluted to give Cd,,[. ANALYTICAL CHEMISTRY, VOL. 49, NO. 14., DECEMBER 1977
2283
0
A 0.2
0.4
08
0.8
1.0
Fraction of C i
Figure 4. Signal-to-noise ratio vs. fraction of C,
Combination of Equations 1 and 3 leads to the following relation,
Pi=l-A
(4)
The individual response parameters for each analyte can therefore be accurately computed without knowing their respective absolute concentrations. In addition to eliminating all possible errors arising from inaccurate selection of C,, the sample dilution technique offers the distinct advantage of interference compensation. T h a t is, the relative detection limit of an analyte will be determined in the presence of any general or specific interferences which might be unique to a particular sample. Although this can be accomplished using correctly prepared multielement standards as discussed above, the present approach circumvents the necessity of specifically identifying each interference for the purpose of optimization. T h e major limitation to the general usefulness of this approach is obviously the relatively large sample requirement. For the sample and spectrometer used in this investigation, a single determination of the 20 point detection limit surfaces consumed approximately 80 mL when the S / N of both Mn and Mo were measured in two sample dilutions. This amount, however, represents the total aspirated volume of the dilutions employed, and does not indicate the amount of actual sample solution which would be consumed. The worst possible case would correspond to a Kituation where the undiluted sample solution is used for one set of S / N measurements. The dilution required for the next set of measurements determines the total amount of sample solution required. If half the original concentration is used, the total sample volume required would equal about 60 mL. Since S / N measurements for all elements are made simultaneously, the sample requirement remains constant regardless of the number of analytes considered. Because of the sample volume limitation, optimum conditions for the determination of small samples which cannot be diluted without reducing analyte concentrations to undetectable levels, must be found using CL’sestimated by one of t h e alternatives discussed above. A large number of analytical samples do, however, easily satisfy the volume requirement of the sample dilution technique. Practical Considerations. Several variables mediate the practical application of PJ to multielement optimization. Due consideration must be given t o such factors as the presence or absence of interferences, the amount of available sample, the time allotted to optimization, and the degree of instru-
2284
ANALYTICAL CHEMISTRY, VOL. 49, NO. 14, DECEMBER 1977
mental mechanization before a viable approach to a given problem can be decided upon. Rigorous optimization, according to the methods discussed above, can be carried out if the requirements of sample size and optimization time are met. For a spectrometer like the one used here, which was not computer interfaced or mechanized in any way, a single determination of the 20 point detection limit surfaces would require about 1 day. The same is true for relative detection limit measurements by the sample dilution technique. Once these data are obtained, it is then a simple matter to compute PJ for the particular sample. If a computer-interfaced spectrometer were available, optimization of conditions for nearly any multielement sample could probably be accomplished in an afternoon. Fortunately, the use of PJ provides an alternative to pure guesswork when one or more of the above mediating factors make rigorous optimization impractical. When sample size is small, time is short, or the presence or absence of interferences is impossible to determine, PJ can be approximated if detection limit surfaces were previously measured using simple aqueous solutions of the individual elements. If these surfaces were stored in a computer, as was done for manganese and molybdenum in this paper, PJ could be computed and maximized in a matter of minutes. For a sample containing no significant interferences, the optimum obtained by this method would be as accurate as the estimates of C;. If unknown interferences were present, the maximum in PJ would still indicate a first approximation of the actual optimum conditions for the sample. Even though the accuracy of this ideal approach may be lacking for some samples, it is important to remember that only one determination of the detection limit surface for each element is necessary. These results can then be used again and again, no matter what combination of elements is under consideration, and may indeed provide the only possible route to the approximate optimum conditions for the determination of many critical samples.
ACKNOWLEDGMENT T h e authors thank M. A. Busch for many helpful discussions.
LITERATURE CITED 11) K. W. Busch and G. H. Morrison. Anal. Cbem.. 45. 712A (1973) (2) J. D. Winefordner, J. J. Fitzgerald, and N. Omenetto,’Appl. Spectiosc., 29, 369 (1975). (3) K. W. Busch, N. G. Howell, and G. H. Morrison, Anal. Chem., 46, 575 (19741. (4) K.-W.’Busch, N. G. Howell, and G.H. Morrison, Anal. Cbem., 46, 1231 (1974). (5) K. W. Busch, N. G . Howell, and G. H. Morrison, Anal. Cbem., 46, 2074 1197A\ ,.”. .,.
(6) J. 0. Rasmuson, V. A. Fassel, and R. N. Kniseley, Spectrochim. Acta. Par? 6, 28, 365 (1973).
RECEIVED for review January 26, 1977. Accepted October 3, 1977. This paper was presented at the November 1976 Pacific Conference on Chemistry and Spectroscopy in Phoenix, Ariz. Acknowledgment is made to the Donors of T h e Petroleum Research Fund, administered by the American Chemical Society, for partial support of this research. Acknowledgment is also made to the Robert A. Welch Foundation for partial support of this research.
