Quantitative analysis of solids in motion by transient infrared emission

Oct 1, 1990 - Vibrational Spectroscopy: Instrumentation for Infrared and Raman Spectroscopy∗. John Coates. Applied Spectroscopy Reviews 1998 33 (4),...
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can be obtained only with less-volatile paraffins, since highvolatile paraffins will vaporize from ultrafine particles within milliseconds due to the Kelvin effect (16). A solution to this problem may be the application of a heated (ca. 323 K) thermodenuder in front of the photoelectric aerosol sensor, which will remove not only high-volatile paraffins but also other interfering products (8). CONCLUSIONS The presented investigations have shown that an additivity of the photoelectric signals is given only for small PAH coverages on particles. In real exhaust situations similar PAH concentrations exist while the particle concentrations are substantially larger at least by a factor 1000; hence only low PAH surface coverages will result from real combustion processes except for residential wood combustion. Under these circumstances the photoelectric signal is likely to represent the sum of the single signals of all adsorbed PAHs. Analyzing cigarette smoke aerosols with the photoelectric aerosol sensor (A = 185 nm) and parallel wet-chemical techniques have confirmed the strong correlation between photoelectric signal and adsorbed PAH amounts (17). Also the applicability of this sensor as on-line and in situ detector for the measurement of PAHs in exhaust gases from waste combustion has been tested (18). Experiments with paraffin coatings have confirmed that aerosol photoemission only probes the surface composition of an aerosol system.

LITERATURE CITED Levsen, K. Fresenius' J. Anal. Chem. 1988,333,467-478. Partrklge, P. A.; Shah, F. J.; Cernansky, N. P.; Suffet, I . H. Envhon. Sci. Techno/. 1987,27,403-408. Davis, C. S.; Fellin, P.; Otson, R. J. Air Pollut. Control Assoc. 1987, 3 7 , 1397-1408. Szentpaly, L. V. J. Am. Chem. Soc. 1984, 706, 6021-6028. Tiwary, R. K.; Singh, T. P. N.; Gosh, S. K. Indian J. Environ. Rot. 1985,5 , 209-213. Niessner, R. J. Aerosol Sci. 1086, 17, 705-714. Niessner, R. Fresenius' J. And. Chem. 1988,329,406-409. Niessner, R.; Wilbring. P. Anal. Chem. lS89, 67, 708-714. Masuda, S.; Mizuono, A.; Tanaka, S. R o c . Symp. Aerosol Sci. Technol., 7st 1983, 35-37. Burtscher, H.; Schmidt-Ott, A. Sci. Total Environ. 1984, 365, 233-238. Niessner, R.; Robers, W.; Wilbring, P. Anal. Chem. 1989, 67, 320-325. Liu, B. Y. H.; Pui. D. Y. H.; Whitby, K. H.; Kittelson, D. E.; Kousaka, Y.; McKenzie, R. L. Atmos. Environ. 1978, 72, 99-104. Neue, G.; Niessner, R. J. C o l M Interface Sci., in press. b i n , C.; Whitesides, G. Anal. Chem. 1989,67, 1673-1679. Brown, K.; Gentry, J. Sci. TotalEnvkon. 1984. 36,225-232. Rader, D. J.; McMuny, P. H.; Smith, S. J. Aerosol Sci. 1987, 6 , 247-260. Niessner, R.;Walendzik, G. Fresenius' J. Anal. Chem. 1989, 333, 129-133. Zajc, A.; Uhlig, E.; Hackfort, H.; Niessner, R. J . Aerosol Sci. 1989, 20, 1465-1468.

RECEIVED for review February

26, 1990. Accepted June 2, 1990. We gratefully acknowledge financial support of Daimler-Benz AG (Stuttgart, FRG), Gossen GmbH (Erlangen, FRG), and the Deutsche Forschungsgemeinschaft.

Quantitative Analysis of Solids in Motion by Transient Infrared Emission Spectroscopy Using Hot-Gas Jet Excitation Roger W. Jones* and John F. McClelland

Center for Advanced Technology Development, Iowa State University, Ames, Iowa 50011

Quantitative compositlonal analysis of optically tMck SOW In motlon Is demonstrated by urbrg trandent Infrared emlsslon spectroocopy (TIRES). TIRES greatiy reduces the self-absorptkn that nonndly degrades comrenUona1emlsskn spectra so that they dosdy resembb Msckbody spectra. Quantltathre composltlonal analyses of poly[(methyl methacrylate)-co(butyl methacrylate)] and poly[ethylenaco-(vlnyl acetate)] with standard errors of predlctlon under 1% were achleved with only a few seconds of data acqulsition uslng prlnclpal compomtt regresgkn. Use of a hotgas jet in place of a laser In the TIRES technique allows study of materials that do not absorb strongly at common laser wavelengths whlle reducing cost and complexlty.

INTRODUCTION Quantitative infrared spectroscopy of solids is limited by the high optical density of most solid samples. Such samples produce highly saturated transmission spectra because of their opacity and produce blackbody-like emission spectra because of self-absorption (1). Conventionally, dilution and physical thinning of samples are used to reduce optical density, but they preclude real-time analysis, destroy the physical structure of samples, are labor intensive, and are not always possible. 0003-2700/90/0362-2074$02.50/0

Recently a new technique called transient infrared emission spectroscopy (TIRES) was introduced that can analyze optically thick samples in motion by reducing self-absorption ( 2 , 3 ) . In TIRES a thin surface layer of the sample is rapidly heated and thermal emission from this layer is collected before it thickens and cools by thermal diffusion. Previous studies of TIRES have demonstrated qualitative analyses on moving samples with continuous-wave (2)and pulsed (3)lasers as the heat sources. This article examines the quantitative abilities of TIRES on moving samples and introduces the use of a versatile, much more economical heat source consisting of a hot-gas jet. In hot-jet-based TIRES, a stream of sample material moves through the field of view of a spectrometer, and a jet of heated gas is aimed onto the sample surface within the field of view. The jet initially produces a very thin, heated layer at the sample surface from which the spectrometer observes thermal emission. Because the layer is optically thin, the amount of self-absorptionis modest. The deposited heat quickly diffuses into the sample, and the emitting layer thickens and cools, but the thickening layer is also carried laterally out of the spectrometer field of view by the sample motion. The emitting layer leaves the observation zone before thickening results in an excessive increase in self-absorption. As a result, the spectrometer detects only the low-self-absorption emission from the thin layer initially produced. 0 1990 American Chemical Society

ANALYTICAL CHEMISTRY, VOL. 62, NO. 19, OCTOBER 1, 1990 NITROGEN

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There are, of course, cases where a laser source may be preferable to a hot jet. A laser is a cleaner, more precise energy source, and a jet could not be used on dusty or otherwise unconsolidated materials. A hot jet, however, has several advantages. A laser-based heat source only works on materials that have a high absorption coefficient at the laser wavelength. The hot-jet source removes this restriction and so broadens the range of samples accessible to TIRES. In addition, the smallness, economy, and reduced safety hazards of a hot-jet source relative to a laser source make hot-jet-based TIRES especially compatible with industrial settings and on-line applications. EXPERIMENTAL SECTION The setup used for TIRES with a hot jet is similar to the arrangement used for TIRES with a continuous-wave laser (2). Figure 1 shows the apparatus for hot-jet TIRES. A disk made of the sample material or a brass disk to which the sample material was clamped was attached to the shaft of a variable-speed motor and spun. The infrared source of a Perkin-Elmer 1800 spectrophotometer was removed and the motor was mounted so that the sample material occupied the usual source position and the spectrometer viewed the sample normal to its surface. A KCl window covered the entry port of the spectrometer. No optics were used to match the size of the emission source to the 8-mmwide field of view of the spectrometer. The spectrometer used a wide-band liquid-nitrogen-cooled HgCdTe detector (D*= 1 x 1O'O cm Hz112W-l), operated at a 1.50 cm/s optical-path-difference velocity and 8-cm-' nominal resolution, and accumulated, unless otherwise noted, 256 scans. The hot jet source consisted of a resistive heating element adapted from a heat gun and operated at 370 W. Nitrogen flowed through it at 0.17 L/s. The hot nitrogen was directed onto the sample surface by a 1-mm-inner-diameter stainless steel tube placed at a 45' angle relative to both the sample surface and the direction of sample motion through the spectrometer field of view. Aimed in this way, the heated gas tended to move in the same direction as the sample surface once the jet struck the surface. The tip of the tube was positioned within 2 mm of the sample surface and just outside the spectrometer field of view so that emission from the hot tube was not observed by the spectrometer.

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A jet of helium chilled by passage through a liquid-nitrogen bath was directed onto the heated surface track left by the hot jet outside the spectrometerfield of view. "'his removed the deposited heat so that the sample surface was near ambient temperature as it reentered the hot jet and the spectrometer field of view one rotation later. In this way the rotating sample could mimic the behavior of a continuous flow of fresh material along a conveyor belt or other material transport system. Both conventional and TIRES emission spectra vary in intensity with wavenumber in a manner similar to blackbody emission curves. To compensate for this, and to give the emission spectra a form equivalent to absorbance spectra, they can be converted to emittance spectra. This has been done by ratioing the emission spectra against blackbody spectra in the same manner as reported before (2,3). Noise produced zero and negative values in the weak, high-wavenumber tails of the various emission curves. To avoid division by zero, a small constant was added to the spectra before ratioing, as has been done previously (2). The sample surface is at a range of temperatures within the observed area during a TIRES experiment. As a result, the intensities of TIRES and blackbody emission curves do not depend on wavenumber in exactly the same way, and when they are ratioed, the resulting emittance spectra often have sloped baselines. The baselines of the spectra in Figure 3 and the bottom half of Figure 2 have been corrected. In addition, these same spectra have been clarified by the spectral subtraction of water vapor and carbon dioxide, when needed, and by nine-point (18 cm-') Savitsky-Golay smoothing. The quantitative analyses were done with commercial principal-component-regression (PCR) software (CIRCOM from Perkin-Elmer (4-6)). A similar factor-analysis approach has previously been used for the precise quantitative analysis of conventional emission spectra. Pel1 et al. (7)used partial least-squares analysis on the emission spectra of optically thin samples of poly[ethylene-co-(vinyl acetate)]. Since TIRES is envisioned as an on-line technique providing real-time data, we wished to minimize the number of mathematical manipulations done on the spectra prior to PCR analysis. Accordingly, all of the analyses reported here were done on the unconverted emission spectra since the conversion from emission to emittance is not necessary for PCR analysis. This also avoids the need for the addition of small constants and other manipulations described in the previous paragraph. Prior to PCR analysis, the spectra were scaled to constant intensity of either the whole wavenumber range or a single composition-independentfeature. No other data pretreatment was done. It should be noted that the precision of PCR analyses depends on the wavenumber range included for analysis in a nonstraightfonvard way. The ranges used here were arrived at by trial and error and are not necessarily optimum. CIRCOM automatically selects the number of factors it uses for each separate regression. The number of factors used varied from 1to 6 for the data reported here, but averaged 3.7 for the results reported in Table I and 3.4 for the cross validation of the poly[ethylene-co-(vinylacetate)] samples. There were no consistent trends between the number of factors used and either the sample speed or the number of scans coadded. A conventional emission spectrum is included for comparison in Figure 2. It was recorded in the same manner as the TIRES spectra except that the sample was stationary, the hot and cold jets were removed, and the sample was heated from the back with heating tape. The conventional spectrum was recorded under conditions that produced the same total signal intensity as was observed for the TIRES spectrum with which it is compared. Absorbance spectra observed by using photoacoustic detection are also presented for comparisonwith some of the TIRES spectra. An MTEC Model 200 photoacoustic detector was mounted in the FT-IR spectrometer (with its normal IR source in place) and 32 cycles were accumulated at a 0.05 cm/s optical-path-difference velocity and 8-cm-' nominal resolution. Samples of poly[(methyl methacrylate)-co-(butylmethacrylate)] were made as 10-cm disks averaging 3 mm thick in the same way that methacrylate-based histological embeddings are polymerized (8). The catalyst benzoyl peroxide was dissolved (1g/100 mL of solution) in the desired mixture of liquid monomers (all from Polysciences, Inc., Warrington, PA), and the solution was sealed overnight in a Teflon mold at 60 "C. The compositions of the

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Figure 2. Upper panel: Emission spectra of 3-mmthick polycarbonate made by the TIRES method (top)and by uniformly heating the sample (middle)compared to a blackbody emission spectrum (bottom). Lower panel: Emittance spectra of polycarbonate derived from the upperpanel spectra compared to an absorbance spectrum of polycarbonate

recorded photoacoustically. samples were known to f0.4 mol % . the samples of copolymerized ethylene and vinyl acetate were received as molding pellets (E. I. du Pont de Nemours and Co., and Scientific Polymer Products, Inc., Ontario, NY) and were used in that form. The pellets were spheroidal, measuring 4 to 7 mm across. For the TIRES experiments the pellets were placed single file in a circular groove cut in a brass disk. The pellets were held in place by brass plates that screwed to the disk and overlapped the edges of the groove. The vinyl acetate content of the pellets was determined by titration. The pellets were dissolved in xylene and the copolymer was saponified with NaOH at 70 "C. The remaining base was then titrated with p-toluenesulfonic acid to a thymol blue end point. The standard deviation for the determinations was 0.09 mass 70. RESULTS AND DISCUSSION The top panel of Figure 2 compares emission spectra from a 3-mm-thick polycarbonate disk with a blackbody spectrum from carbon black. The spectra have not been corrected for the response function of the spectrometer and detector. The differences between the blackbody spectrum and the conventional emission spectrum of polycarbonate are small and subtle because of self-absorption, By contrast, the TIRES spectrum is strongly structured. The largest features in the TIRES spectrum are taller than the blackbody background above which they appear. The lower panel of Figure 2 shows the emittance spectra derived from the upper-panel emission spectra and compares them to an absorbance spectrum of polycarbonate. The conventional emittance spectrum shows the severe effects of self-absorption. Only the strongest spectral features are apparent, and they have a dispersive shape. The TIRES emittance spectrum, on the other hand, is the equivalent of the absorbance spectrum. The noise increases in both emittance spectra with increasing wavenumber because they were generated by ratioing emission spectra that decrease in intensity with increasing wavenumber.

Despite this, even the smallest features below 3000 cm-' in the absorbance spectrum are also discernible in the TIRES emittance spectrum. The TIRES-related heating caused no damage or visible change in the polycarbonate sample. Figure 3 contains TIRES emittance spectra from a 3-mmthick disk of poly(methy1 methacrylate) at two different sample velocities and an absorbance spectrum of the material. The two TIRES spectra, which were taken under identical conditions except for sample speed, demonstrate the effects of speed. As discussed previously (2),increasing sample speed (or reducing the spectrometer field of -view) reduces the amount of self-absorption in the observed emission and so reduces the amount of saturation in the spectrum. The 408 cm/s TIRES spectrum does indeed have less saturation than the 40.8 cm/s spectrum; it has about as much saturation as the absorbance spectrum. The higher-speed TIRES spectrum has a signal-to-noise ratio about 0.4 times that of the lowerspeed one (prior to smoothing). This is because an increase in sample velocity without an increase in the power of the heat source results in lower sample-surface temperatures and reduced emission intensity. It is difficult to measure the surface temperatures of the TIRES samples since they are in motion, are in contact with a jet of hot gas, and produce structured (nonblackbody) emission. Nevertheless, by using temperature-indicating paints (Tempilaq) we estimate that the peak surface temperatures of the poly(methy1 methacrylate) disk were 140 f 10 "C when the 408 cm/s spectrum was recorded and 200 f 10 "C when the low-speed spectrum was recorded. The temperature of the gas jet was 410 f 10 "C at the nozzle tip. The momentary TIRES heating caused no damage or visible change in the sample disk. To assess the quantitative abilities of TIRES, a group of 11 copolymers of methyl methacrylate and n-butyl methacrylate were examined by TIRES and the spectra were analyzed by principal component regression (PCR). The samples were matte-finished disks averaging 3 mm thick that were made in-house and spanned the range 0 to 100% methyl methacrylate. TIRES spectra were recorded for all 11samples by coadding 1,4,16,64,and 256 scans a t both 40.8 and 408 cm/s sample velocities. Each of these ten sets of spectra was then analyzed by a PCR cross validation using just the 1100-790 cm-' range of the spectra (9, IO). For the cross validation, each of the 11 samples was chosen in turn as the unknown, the other 10 samples acted as standards to generate a regression model, and then the model was used to predict the composition of the unknown. The resulting 11 predicted

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co-(butyl methacrylate)] samples. Compositions are (top to bottom) 100.0, 93.1, 85.7, 77.8, 69.2, 60.0, 50.0,39.1, 27.3, 14.3, and 0.0 mol % methyl methacrylate. Table I. PCR Analysis of TIRES Spectra for Methyl Methacrylate Content in Methacrylate Copolymers std errors of prediction, mol %

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where there are m samples, c^, is the predicted composition, and c, is the reference composition of sample i. None of the samples suffered damage as a result of the TIRES heating, although after numerous experiments the samples with high butyl methacrylate content developed an increased surface gloss along the track of the hot jet. One of the ten sets of emission spectra is arranged in Figure 4 in order of composition from pure poly(methy1 methacrylate) at the top to pure poly(buty1 methacrylate) at the bottom. The set was taken at a sample speed of 40.8 cm/s by coadding 16 scans (6.4-s acquisition time corresponding to the sample traveling 2.5 m). The signal-to-noise ratio for these spectra is very good, despite the short acquisition time. The spectra have obvious composition-dependent features, but there is extensive overlap of the methyl-related and butyl-related bands. Figure 5 is a plot of the compositions predicted by the cross validation of these spectra against the true compositions known from the synthesis of the samples. The SEP for this particular set of spectra is 0.75 mol %. Table I presents the SEPs for all of the sets of spectra. It can be seen from the SEPs that it takes only a few seconds of data acquisition at the lower sample speed to achieve such a good signal-to-noise ratio that further data acquisition does not reduce the error. The higher-sample-speed spectra consistently have higher SEPs than their lower-speed counterparts.

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This is probably caused by a number of factors, but the most important is that the high-speed spectra are less intense than the others, just like the previously discussed spectra in Figure 3. In addition, the high-speed spectra have more noise both because increased sample and motor vibration is transmitted to the interferometer and because lower (and stronger) harmonics of the sample rotation rate fall within the range of interferometer modulation frequencies. It has already been noted that the precision of PCR depends in a complex manner on the frequency range chosen for analysis. All of the SEPs in Table I are from analysis of the 1100-790-~m-~ range so that comparisons can be made among the data sets. This range should not be considered to be either optimum for a particular data set or equally good for all of the sets. For example, if the range is extended to include 1100-700-~m-~, the SEPs for the low-speed sets of 1 , 4 , and 16 scans all improve (becoming 1.10, 1.05, and 0.55 mol %, respectively) while the SEP for the low-speed, 256-scan set rises to 0.81 mol %. An explanation for such behavior is beyond the scope of this article, but it likely reflects an interplay between the amount of compositional information and the amount of confounding noise within the added 90-cm-' band of each data set. Although PCR was used above to determine the compositions of the methacrylate copolymers, quantitative TIRES does not have a greater need for such advanced data analysis methods than other infrared methods do. If a spectrum contains a characteristic band for the component to be measured that is neither excessively overlapped nor overly strong (and therefore especially susceptible to self-absorption), then a simple peak height or peak area versus concentration calibration is possible. Although there is extensive overlap in the methacrylate spectra, there is a band at 706 cm-' which fits the criteria. The heights of this feature in the Figure 4 spectra were measured and are plotted against composition in Figure 6. The curve in the figure is a fit to the data of the equation h = a - b exp(-cd), where c is the composition, h is the peak height and a, b, and d are constants. The form of the equation comes from McMahon (II), who showed that the emission intensity from a uniformly heated, low reflectance, partially transmitting sample is proportional to 1- T , where T is the transmittance. The heated, emitting layer produced in TIRES should behave much like such a sample, although the inexact position of the induced temperature gradient prevents the determination of any physical parameters (e.g., absorptivity, layer thickness) from the mathematical fit in the figure. The root-mean-square deviation of the data from the curve is 4.5 mol %, which is certainly worse than

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Table 11. PCR Analysis of TIRES Spectra of Compositionally Nonuniform Poly[ethylene-co-(vinyl acetate)] Samples" compositions of component pellets 18.00 and 18.00 and 9.18 and 9.18 and

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the 0.75 mol 70SEP for the PCR analysis of the same spectra. This is not surprising since the peak-height correlation uses only a single datum from each spectrum. The sensitivity of quantitative TIRES to variations in sample speed was also tested by using PCR analysis of the methacrylate spectra. Spectra at 40.8 cm/s for all but the 50 mol % methyl methacrylate sample were used to calibrate a PCR model. Spectra of the 50 mol % sample were then taken at a variety of sample speeds and analyzed by this model. Figure 7 shows how the analysis results varied with sample speed. The relation is roughly linear with a slope of only -0.067 mol % per cm/s. In this particular case the sensitivity to sample speed is weak. This weak relationship may not be a universal feature of TIRES analyses, but it does show that quantitative TIRES need not be overly sensitive to sample speed. When sample speed does have a large effect, it can still be compensated for by monitoring speed and correcting. Ten samples of poly[ethylene-co-(vinyl acetate)] ranging from 8.73 to 51.06 mass % vinyl acetate were chosen for use in examining other aspects of quantitation by TIRES. This set of samples provided a test of quantitative TIRES on lumpy materials since the samples were spheroidal molding pellets. TIRES spectra of the 10 copolymers made a t 40.8 cm/s by coadding 256 scans are shown in Figure 8. A PCR cross validation on the 1170 to 570 cm-' region of these spectra gave the predictions illustrated in Figure 9 and a SEP of 0.83 mass % vinyl acetate. Obviously the irregular surface presented by the pellets was not a barrier to quantitative analysis. The sample pellets were not damaged by the TIRES process, although they all showed an increased surface gloss because of the repeated heating. In addition, pellets high in vinyl acetate tended to bond together as a result of both the repeated heating and the pressure applied by the clamps holding the pellets in place. As a test of the response of TIRES to compositionally nonuniform materials, four TIRES samples were prepared in which half of each sample was pellets of one composition and the other half was pellets of another composition. The two kinds of pellets were arranged in each TIRES sample either

40 50 60 70 80 Sample Velocity (cm/s)

Flgwe 7. Compositions of a 50 mol % methyl methacrylate polymer sample predicted by prlncipal component regression from TIRES spectra of the sample taken at various velocities. Calibration spectra for the regression were taken at 40.8 cm/s.

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in a random order, so that the composition observed by the spectrometer changed many times during each scan, or in separate half circles, so that the composition changed only one or two times during each scan. Spectra of these mixed samples were taken by coadding 256 scans and were analyzed with a PCR model calibrated by using the ten spectra in Figure 8. The compositions and analysis results for the mixed samples are given in Table 11. The predicted values d l fall with 0.7 mass % of the true average values, which is even less than the SEP found for the cross validation of the compositionally uniform samples. Nonuniformity of composition obviously does not hamper quantitative results with TIRES. Of course,

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ACKNOWLEDGMENT We wish to thank James B. Callis of the Center for Process Analytical Chemistry, University of Washington, for providing poly[ethylene-co-(vinyl acetate)] samples, Larry Bright of Du Pont for supplying both samples of poly[ethylene-co-(vinyl acetate)] and information on their analysis, and Siquan Luo of Ames Laboratory for carrying out the titration analyses of these samples. LITERATURE CITED

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if the thermal or emissive properties of a material varied greatly with composition, TIRES would weight the more strongly emitting components of a sample mixture, but a properly designed calibration could minimize this effect. The results reported here show that TIRES can be used for excellent quantitative measurements on both smooth and irregular materials over a range of sample speeds. Quantitative TIRES is neither overly sensitive to sample speed changes nor hindered by compositonal variations. The hot-jet source is much simpler and more economical than the laser sources used previously (2,3). It allows analysis of transparent and low-absorptivity materials not accessible with a laser source.

Griffiths, Peter R. Appl. Spectrosc. 1972. 26, 73-76. Jones, Roger W.; McClelland, John F. Anal. Chem. 1989, 67, 650-656. Jones, Roger W.; McClelland, John F. Anal. Chem. 1980, 67, 1810-1815. Fredericks, Peter M.; Osborn, Paul R.; Swinkels, Dom A. J. Anal. Chem. 1985, 57, 1947-1950. Frederlcks. Peter M.; Moxon, Neville T. Fuel 1988, 65, 1531-1538. Malinowski, Edmund R.; Howery, Darryl G. Factor Analysis In Chemktry; Wlley: New York, 1980. Pell, Randy J.; Erickson. Brice C.; Hannah, Robert W.; Callis, James 6.; Kowalskl, Bruce R. Anal. Chem. 1988, 60, 2824-2827. Glauert. A. M. I n Practical Methcds In Electron Microscopy; Olauert, A. M., Ed.; North-Holland: Amsterdam, 1974; Vol. 3, pp 153-155. Haaland, David M.; Thomas, Edward V. Anal. Chem. 1988, 60, 1193- 1202. Haaland, David M.; Thomas, Edward V. Anal. Chem. 1988, 60, 1202-1208. McMahon, H. 0. J. Opt. Soc.Am. 1950, 4 0 , 376-380.

RECEIVED for review April 24, 1990. Accepted July 9, 1990. This work was funded by the Center for Advanced Technology Development, which is operated for the U S . Department of Commerce by Iowa State University under Grant No. ITA 87-02, and in part (J.F.M.) by Ames Laboratory, which is operated for the U S . Department of Energy by Iowa State University under Contract No. W-7405-ENG-82, supported by the Assistant Secretary for Fossil Energy.

Feasibility of Using Liquid Crystals for the Development of Molecularly Selective Fiber-optic Chemical Sensors Chu Zhu and Gary M. Hieftje*

Department of Chemistry, Indiana University, Bloomington, Indiana 47405

A new type of flber-optlc chemical sensor has been developed for the determlnation and dlfferenilatlon of geometric Isomers. The operation of the sensor Is based upon the m e e lcua lr-e absorptkn of poiymdear aromatic hydrocarbons (PAH) on a llquld crystal. The selectlve Interaction of a PAH with a llquldtrystal substrate causes quenching of the llquklcrystalfluorescence. Detection limits of such a device for PAH compounds approach lO-'O mol/ cm'; the sensor response t h e Is about 2 mln. Because the sensor Is based upon physical absorption, It Is reusable and reversible.

INTRODUCTION Polynuclear aromatic hydrocarbons (PAHs) are products of the incomplete combustion of organic matter and often exhibit carcinogenic (I) and mutagenic (2) properties. Importantly, however, these properties are isomer-specific. *Author to whom correspondence should be sent. 0003-2700/90/0362-2079$02.50/0

Unfortunately, many conventional analytical methodologies (such as UV-visible absorption spectrophotometry) are not useful for the determination of isomer mixtures, because of the structural similarity of molecular isomers. It is therefore necessary to explore new methods for the differentiation and determination of molecular isomers; liquid-crystal-based sensors constitute a new class of such selective methods. Liquid crystals are a form of fluid in which there occurs an order in the arrangement of the molecules, caused by rather rigid molecular structures. Further, a thermotropic liquid crystal is one that possesses one or more mesophases over a certain temperature range. In turn, the rigid structure of the liquid-crystal molecules in an anisotropic mesophase enables the selective absorption of appropriately structured organic species. This property led to the application of liquid crystals as stationary phases in gas chromatography as early as 1963 ( 3 ) . Since then, many liquid-crystal phases have been successfully used in gas chromatography, especially for the separation of geometric isomers (4-8),because of the unique ordered arrangement of the liquid-crystalline molecules. Many theories have been proposed to interpret the retention data from these experiments. From these theories, it is rather 0 1990 American Chemical Society