Anal. Chem. 2005, 77, 1867-1875
Progressive Thermal Desorption of Vapor Mixtures from a Preconcentrator with a Porous Metal Foam Internal Architecture and Variable Thermal Ramp Rates Jay W. Grate,* Norman C. Anheier, and David L. Baldwin
Pacific Northwest National Laboratory, Richland, Washington 99352
A vapor preconcentrator has been designed with the porous polymer (Tenax) packed into a highly porous metal foam to facilitate thermal conductivity and temperature uniformity throughout the bed of the preconcentrator during heating. Vapors were desorbed using linear temperature programming from room temperature to a maximum temperature of 170 or 200 °C; the programmed duration of the thermal ramp was varied from 10 to 180 s. The partial separation of vapor mixtures that are thermally desorbed from the preconcentrator has been examined in terms of a metric for resolution, using methyl ethyl ketone, toluene, and dimethyl methylphosphonate as a test mixture. Vapors desorbed as a sequence of partially separated overlapping peaks, as observed with a polymer-coated flexural plate wave sensor. It was shown that vapor mixture resolution improved as the total time of the thermal ramp was extended from 30 to 120 s. In this way, the preconcentrator serves to act as a preseparator in addition to its usual functions for sampling, signal modulation, and improving sensitivity. Overlapping peaks were modeled, and peak areas were extracted using an exponentially modified Gaussian model. Peak areas were independent of the thermal ramp rate. Uses of such preconcentrators with multivariate detectors, such as sensor arrays, are discussed. The addition of a thermally desorbed, small-volume, solidsorbent preconcentrator prior to real-time chemical sensor measurement of organic vapors provides a means to automatically sample the ambient gas and improve the measurement sensitivity. During operation, a small volume of solid sorbent material collects analyte vapors from a large gas sample (e.g., at a given flow rate for a fixed period of time) and then releases the analyte vapors into a small gas volume during thermal desorption. This results in a concentrated chemical pulse that generates a rapid peak in the detector response. This signal modulation, where the initiation of the heating defines when analytes are delivered to the measurement system, overcomes difficulties with baseline drift and sensor rezeroing and facilitates automated feature extraction, that is, determining the magnitude of the response from the temporal data stream. Systems using preconcentrators can provide detection levels that are 10-1000 times lower than systems using 10.1021/ac049142s CCC: $30.25 Published on Web 02/09/2005
© 2005 American Chemical Society
direct sampling and analysis; thus, the process provides sampling, preconcentration, sample injection, and signal modulation functions. These features are particularly useful for continuous monitoring applications with portable or unattended devices. These types of preconcentrators were reported for use with sensor arrays by Grate et al. in 19931 and for gas chromatographic air monitors by Mitra et al., also in 1993.2 Previously, Kindlund had described a sorbent preconcentrator with a liquid preconcentrating film for use with a single sensor,3 whereas Mitra et al. had previously described solid sorbent “modulators” for use with gas chromatographic air monitors.4 Since these initial studies, Mitra et al. have continued to develop preconcentrators, which they refer to as microtraps, for gas chromatography5-11 while a number of groups have developed preconcentrators for sensor array-based detectors.1,12-27 The Zellers group has explored a (1) Grate, J. W.; Rose-Pehrsson, S. L.; Venezky, D. L.; Klusty, M.; Wohltjen, H. Anal. Chem. 1993, 65, 1868-1881. (2) Mitra, S.; Yun, C. J. Chromatogr. 1993, 648, 415-421. (3) Kindlund, A.; Sundgren, H.; Lundstrom, I. Sens. Actuators 1984, 6, 1-17. (4) Mitra, S.; Phillips, J. B. Rev. Sci. Instrum. 1988, 59, 1427-1428. (5) Mitra, S.; Lai, A. J. Chromatogr. Sci. 1995, 33, 285-289. (6) Mitra, S.; Zhu, N.; Zhang, X.; Kebbekus, B. J. Chromatogr., A 1996, 736, 165-173. (7) Mitra, S.; Xu, Y. H.; Chen, W.; Lai, A. J. Chromatogr., A 1996, 727, 111118. (8) Feng, C.; Mitra, S. J. Chromatogr., A 1998, 805, 169-176. (9) Mitra, S.; Feng, C.; Zhang, L.; Ho, W.; McAllister, G. J. Mass Spectrom. 1999, 34, 478-485. (10) Feng, C.; Mitra, S. J. Microcolumn Sep. 2000, 12, 267-275. (11) Kim, M.; Mitra, S. J. Chromatogr., A 2003, 996, 1-11. (12) Groves, W. A.; Zellers, E. T. Am. Ind. Hyg. Assoc. J. 1996, 57, 1103-1108. (13) Groves, W. A.; Zellers, E. T.; Frye, G. C. Anal. Chim. Acta 1998, 371, 131143. (14) Shaffer, R. E.; Rose-Pehrsson, S. L.; McGill, R. A. Field Anal. Chem. Technol. 1998, 2, 179-192. (15) Heller, E. J.; Hietala, V. M.; Kottenstette, R. J.; Manginell, R. P.; Matzke, C. M.; Lewis, P. R.; Casalnuovo, S. A.; Frye-Mason, G. C. Proc. - Electrochem. Soc. 1999, 99-23, 138-142. (16) Cai, Q.-Y.; Park, J.; Heldsinger, D.; Hsieh, M.-D.; Zellers, E. T. Sens. Actuators 2000, B62, 121-130. (17) Nakamoto, T.; Isaka, Y.; Ishige, T.; Moriizumi, T. Sens. Actuators, B 2000, B69, 58-62. (18) Nakamoto, T.; Sumitimo, E. IEEE Sens. J. 2004, in press. (19) Park, J.; Zellers, E. T. Analyst (Cambridge, U. K.) 2000, 125, 1775-1782. (20) Park, J.; Zhang, G.-Z.; Zellers, E. T. AIHAJ 2000, 61, 192-204. (21) Groves, W. A.; Zellers, E. T. Ann. Occup. Hyg. 2001, 45, 609-623. (22) Hughes, R. C.; Manginell, R. P.; Kottenstette, R. Proc. - Electrochem. Soc. 2001, 2001-18, 348-354. (23) Lu, C.-J.; Zellers, E. T. Anal. Chem. 2001, 73, 3449-3457. (24) Lu, C. J.; Zellers, E. T. Analyst (Cambridge, U. K.) 2002, 127, 1061-1068.
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number of preconcentrator configurations for array-based detection in several papers.12,13,16,19-21,23,24,28,29 In some cases, preconcentrators are combined with gas chromatographic columns and sensor array detectors.15,24,29 Microfabricated preconcentrators have been developed recently.11,15,29 Preconcentrators are also useful for other types of air monitoring detectors in addition to chemical sensors and gas chromatographs, including ion mobility spectrometers and mass spectrometers.9,30 The primary roles of the preconcentrators in such systems remain improving sensitivity and sample injection; however, preconcentrators also offer opportunities for improved selectivity. For example, permanent gases, humidity, or vapors from volatile vapors may be poorly collected on some preconcentrator sorbents, as compared to vapors from less volatile organic solvents, and are thus reduced as interferences in the analysis of vapors that are more quantitatively collected.1,9 In some cases, temporal separations of vapor mixtures can be obtained as different compounds desorb at different rates. Kindlund found that with suitable tubing between the silicon oil preconcentrator and the thickness shear mode (TSM) sensor, water vapor could be separated from the organic vapor of interest.3 In the original array study by Grate et al. using polymer-coated surface acoustic wave (SAW) sensors, it was observed that water vapor desorbed from the Tenax-packed preconcentrator tube much more rapidly than the vapor of interest, dimethyl methylphosphonate (DMMP).1 Hence, the organic vapor of interest was completely separated from water. In these studies, the preconcentrator tube increased in temperature from room temperature to 200 °C in 12 s. Park and Zellers later confirmed this effect using a porous styrenedivinylbenzene copolymer adsorbent (XUS43565.01) in combination with a SAW sensor array and demonstrated quantitatively that the calibrations for vapors desorbed after the initial humidity spike were independent of the sampled humidity.19 Grate et al. also observed that more volatile organic vapors desorb more rapidly than DMMP, providing a mechanism for discriminating against them.1 A similar system was later used by Shaffer et al. with the aim of using the temporal preseparation from the preconcentrator operation as one dimension of selectivity with the SAW sensor array as a second dimension of selectivity for a multiway chemometric analysis.14 Nakamoto explored preconcentrator approaches that take advantage of different desorption characteristics of vapors and included methods to adjust temperature programming or collection time for autonomous improvements in performance.17,31,32 Recently, Morris et al., described a deliberate programmed thermal desorption of vapors from a Tenax-loaded preconcentrator to a set of semiconductor sensors at a rate of 10 °C/min.25 It was shown that different vapors (25) Morris, L.; Caruana, D. J.; Williams, D. E. Meas. Sci. Technol. 2002, 13, 603-612. (26) Bender, F.; Barie, N.; Romoudis, G.; Voigt, A.; Rapp, M. Sens. Actuators, B 2003, B93, 135-141. (27) Hamacher, T.; Niess, J.; Schulze Lammers, P.; Diekmann, B.; Boeker, P. Sens. Actuators, B 2003, B95, 39-45. (28) Zellers, E. T.; Morishita, M.; Cai, Q. Y. Sens. Actuators, B 2000, B67, 244253. (29) Tian, W.-C.; Pang, S. W.; Lu, C.-J.; Zellers, E. T. J. Microelectromech. Syst. 2003, 12, 264-272. (30) Dworzanski, J. P.; Kim, M.-G.; Snyder, A. P.; Arnold, N. S.; Meuzelaar, H. L. C. Anal. Chim. Acta 1994, 293, 219-235. (31) Nakamoto, T.; Sukegawa, K.; Sumitomo, E. Proc. IEEE Sens. 2002, IEEE Int. Conf. Sens., 1st, 2002 2002, 1, 366-371. (32) Nakamoto, T.; Sumitimo, E. Sens. Actuators, B 2003, B89, 285-291.
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desorbed with peak maximums appearing at different times following the onset of heating, and multivariate curve resolution techniques were demonstrated to recover individual vapor response patterns and desorption traces from vapor mixtures Thus, there is considerable interest in using a vapor preconcentrator as part of the chemical selectivity of a preconcentratorcontaining detection instrument. Interest in the use of advanced chemometrics with preconcentrator/sensor-array systems in which the preconcentrator provides partial temporal separation is evident in the reports by Shaffer et al. and Morris et al.14,25 In each of these studies, the temporal resolution reported was described at only a single thermal ramp rate, which was very fast in the case of Shaffer et al. and very slow in the case of Morris et al. Shaffer used the resolution that was fortuitously observed at the fast thermal ramp, whereas Morris deliberately operated the preconcentrator in a programmed thermal ramp to observe temporal separation. The addition of an upfront separation method to a multivariate detector, such as a sensor array, even if it only provides partial separations, results in a second-order measurement system whose data can be advantageously processed using advanced chemometric methods.33 By contrast, a sensor array alone is a first order measurement that provides only one vector of data per sample. The additional information content from a second-order system can provide improved selectivity and the potential to quantify analytes in the presence of unknown interferences. The desired operation of a preconcentrator for partial separations is fundamentally different from a preconcentrator used primarily as a preconcentration and injection method. In the latter case, the preconcentrator desorption should be as fast and sharp as possible in order to obtain the tallest detection peaks, and to minimize band broadening due to injection if coupled with a chromatographic step. If preseparations are desired, however, then the vapors must be desorbed in a way that spreads them out over time. Accordingly, the influence of the thermal ramp rate on the partial separation of vapor mixtures is a factor in the design of a preconcentrator/multivariate detector/advanced-chemometrics instrument. However, the effect of the thermal ramp rate on vapor mixture resolution using a practical preconcentrator design operated at multiple thermal ramp rates has yet to be reported. In the current study, we have examined the temporal separation of desorbing vapors at varying linear rates of temperature increase, using a metric for resolution to determine if the rate of thermal desorption influences the resolution achieved in a practical preconcentrator configuration. The preconcentrator used in this study was designed to provide good thermal uniformity throughout the packed bed of solid adsorbent. This preconcentrator is described along with a rapid feedback system to control the thermal ramp rate. It is shown that peak resolution in the analysis of mixtures can be improved by decreasing the thermal ramp rate, as compared to heating the preconcentrator as rapidly as possible, although temporal separations are still observed in the most rapid case. We have also used curve fitting and modeling with an exponentially modified Gaussian function to extract peaks from a test mixture and determine peak areas. The potential advantages of using preconcentration with partial separations of desorbing vapors in conjunction with multivariate detectors are discussed. (33) Booksh, K. S.; Kowalski, B. R. Anal. Chem. 1994, 66, 782A-791A.
Figure 1. Schematic diagram of a cross-section of the preconcentrator with a metal foam core in a Teflon flow cell consisting of Teflon tubing and machined inserts. A resistive heater (represented by the dashed lines above and below the preconcentrator) is wrapped around the tube. The wire mesh screens at each end of the metal foam core are not shown, neither is the attached thermocouple.
Figure 3. Wheatstone bridge used for preconcentrator temperature measurement for feedback control of the thermal ramp rate.
Figure 2. Photograph of a porous nickel foam.
EXPERIMENTAL Materials. Materials for this work included the preconcentrator solid sorbent packing, Tenax-TA, 60/80 mesh, from Supelco. Ampormat 200 series porous nickel foam in sheets of 60 pores/ in (PPI) material was obtained from Astro Met Inc. (Cincinnati, OH). The analyte test liquids were toluene (TOL), methyl ethyl ketone (MEK), and dimethyl methylphosphonate (DMMP), obtained from Aldrich. Preconcentrator Design. The preconcentrator core consisted of porous nickel foam that is 95% air with a mean pore diameter of 380 µm. The adsorbent porous polymer, Tenax TA, in the 60/ 80 mesh size has grain size diameters from 170 to 250 µm. A metal foam core was loaded with a total of 25 mg of Tenax. The core dimensions were ∼12.7 mm long by 4.8 mm diameter, consisting of two metal foam cylinders 4.8 mm in diameter cut from a sheet supplied at 6.35 mm thick. The metal foam core, two wire mesh screens (Inconel 600 wire mesh disks with 120 mesh size, 0.094 mm, Tri Screen Inc, Claremont, CA), and two opposing Teflon adapters were inserted into a 58-mm length of PTFE Teflon 8-gauge shrink tubing (SPC Technology Voltrex). The Teflon tubing was thermally shrunk to seal the connections. An additional layer of shrink tubing was used to secure a Kapton foil heater (Minco no. HK5573R5.1) and a type K thermocouple (Omega no. 5TC-TT-K-36-36-SMP-M) around the outer diameter of the metal foam pellet. The thermocouple was used to monitor the temperature during thermal calibration (see below) and while conducting thermal desorption experiments, but not for feedback. The preconcentrator design is shown schematically in Figure 1; a picture of the metal foam is shown in Figure 2. Preconcentrators prepared without metal foam were constructed similarly, minus the metal foam, inserting the Teflon
adapters farther into the tube, since the volume of the Tenax alone was slightly less than the volume of Tenax plus metal foam. In studies in which thermocouples were inserted into the preconcentrator to measure temperatures at the center and periphery of the adsorbent bed, we used an Omega type 5TC-TT-K-36-36 thermocouple. The thermocouple has a head diameter of ∼0.01 in., or 250 µm. This compares with Tenax particles of 170-250 µm. Preconcentrator Thermal Control. A simplified Wheatstone bridge circuit, shown in Figure 3, was used to monitor and control the heater temperature. The resistive heater, having resistance temperature detector (RTD) properties, served as one leg of the bridge, such that the bridge balance voltage was directly proportional to the RTD resistance and temperature. The bridge was initially balanced so that the bridge balance voltage is 0 at room temperature. A custom LabVIEW software program and a PCI6030E multifunction data acquisition card (National Instruments, Austin Texas) were used to control the thermal ramp. An input voltage, Vin, was supplied from a digital-to-analog converter (DAC) to raise the heater temperature. The bridge balance voltage, Vout, was measured using an analog-to-digital converter (ADC). The input voltage was slewed programmatically to obtain the desired ramp rate and end point while monitoring the bridge balance voltage at a 35 Hz update rate. The system was initially calibrated by independently monitoring the temperature with the thermocouple, and this calibration was used with the bridge balance voltage in the control algorithm. Flexural Plate Wave (FPW) Sensor. FPW devices individually mounted on separate alumina headers and oscillator circuits were obtained from Berkeley MicroInstruments, Berkeley, California. FPW devices have been described previously.34-38 These devices had a resonance frequency of 8 MHz, with etch pits 6 mm long and 0.5 mm wide. The alumina headers contained a window over which the dies were mounted, with the FPW etch (34) Wenzel, S. W.; White, R. M. IEEE Trans. Electron Devices 1988, 35, 735743. (35) Wenzel, S. W.; White, R. M. Appl. Phys. Lett. 1989, 54, 1976-1978. (36) Wang, Z.; Cheeke, J. D. N.; Jen, C. K. Electron. Lett. 1990, 26, 1511-1513. (37) Wenzel, S. W.; White, R. M. Sens. Actuators 1990, A21-A23, 700-703. (38) Grate, J. W.; Wenzel, S. W.; White, R. M. Anal. Chem. 1991, 63, 15521561.
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pit facing away from the header and the metallized side exposed through the bottom of the header, where electrical connections were made. The same type of FPW device has been used in an array-on-a-chip format in which six such devices were fabricated right next to one another.16,39 Prior to coating, the FPW sensor was well-rinsed with dichloromethane and air-dried, then cleaned by a UV-ozone cleaning method in a Jelight UVO Cleaner, model 342. The FPW sensor was coated with the polymer poly(dimethylsiloxane) (PDMS) using the spray coating technique to a frequency shift of 100 kHz. The film was examined by optical microscopy with a Nikon Optiphot M microscope using reflected light Nomarski differential interference contrast after being applied. The coated sensor was mounted in an aluminum flow cell with a gas inlet and gas outlet, with the entire flow cell plus associated electronics maintained at 25 °C. The inlet and outlet channels of the flow cell were placed at each end of the device etch pit, and the etch pit channel was used for flow over the sensing film to minimize dead volumes. The flow cell was connected by 1/16-in. Teflon tubing directly to the preconcentrator outlet. Frequency Measurements. For all the initial studies, the frequency data from the FPW sensor oscillator were recorded every 2 s using a Hewlett-Packard 53131A High Performance Universal Counter with a medium stability timebase, transferring the data to a Macintosh computer using the IEEE-488 bus and collecting data with Labview software. For studies at higher data collection rates, we instituted a fast frequency data collection method to be described in more detail elsewhere. Briefly, the sensor frequency was measured using the counters on a National Instruments PCI-6602, 8-channel, 32-bit counter PCI card with an internal 80-MHz timebase. Two counters were used: the first counter (counter 0) counted a user-specified number of FPW frequency cycles, and the second counter (counter 1) timed how long it took to count the specified number of cycles, using the internal 80 MHz timebase as the clock. Therefore, the measured frequency of the FPW signal is the userspecified number of cycles counted divided by the elapsed time required to count them, where the elapsed time is measured as the number of cycles counted on the second counter divided by 80 000 000. The frequency measurements were transferred directly to the computer CPU via the 133-MHz PCI bus (rather than by slower methods such as a GPIB bus). Custom LabView software was developed to read, display, and log the frequency data. Vapor Generation. Test vapors were generated from our vapor blending system (VBS), which generates vapors in dry nitrogen carrier gas from bubbler sources and dilutes these vapor streams to preprogrammed concentrations with nitrogen carrier gas. The instrument output is either the diluted vapor stream or clean carrier gas, each at a flow rate of 100 mL/min. The instrument is equipped with four bubbler sources housed in a temperature-controlled aluminum block maintained at 15 °C. Each bubbler has independent electronic mass flow controllers (MFC) to regulate the input carrier gas flow, using either a 500-sccm range MFC for higher bubbler flows or a 20-sccm range MFC for lower bubbler flows. Choice from two MFCs for each bubbler provides better precision over a larger range than the use of a (39) Grate, J. W.; Kaganove, S. N.; Nelson, D. A. Chem. Innovations 2000, 30 (11), 29-37.
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single MFC would, whereas independent MFC pairs for each bubbler enables independent variation of each vapor concentration in a mixture. The outputs from one or more bubblers are combined in a manifold prior to further dilution, allowing vapor mixtures consisting of one to four vapor species to be generated. In any given programmed experiment, the output from one bubbler can be varied to obtain a series of output concentrations, while those from other bubblers are maintained at some constant flow rate. Preconcentrator Experiments. The preconcentrator column was placed in series between the vapor generator output and the single FPW sensor acting as the detector. A standard vaporcollection time of 2 min was used throughout this work, which means the VBS system output the test vapor mixture for 2 min, and this mixture was collected on the preconcentrator sorbent material. At the end of each 2-min vapor-collection phase, the VBS switched back to pure purge gas. The preconcentrator control program was programmed with a 10-s delay to allow transport of all test vapors to the preconcentrator and for the sensor baseline to restabilize from any pressure upset. The thermal ramp was then started at a preset ramp rate, ranging from 0.8 to 15 °C/s for this work, to a maximum preset temperature of 170 °C for the early portion of the project, later increased to 200 °C maximum. At the top of the thermal ramp, the temperature was held for a preselected period, typically 40 s, to allow for the test vapors to fully desorb. At the end of the ramp hold period and the vapor desorption, the preconcentrator was allowed to thermally cool back to ambient in preparation for the next cycle. The system was programmed for repetitive preconcentration and desorption experiments as follows: An initial period with pure purge gas flow of 7 min allowed the sensor and preconcentrator to flush out. After the standard vapor-collection time of 2 min, a desorption period of 7 min allowed time for the preconcentrator to thermally ramp at the preselected ramp rate, hold at a preselected temperature for a preselected hold time, and then stop the current to the heater so that the tube could thermally cool back to ambient temperature. Repeated cycles of vapor-concentration and vapor-desorption steps were used for covering a range of vapor concentrations or to provide peak precision information. Modeling. Data analysis software, “IGOR Pro Version 4” from Wavemetrics Inc, Lake Oswego, OR, was used to curve fit and model the analyte vapor peaks observed in response to preconcentrator thermal desorption. The specific IGOR Pro routine, called MultiPeakFit, was adapted to allow a selection of various peak models to be tested for fit. We worked with Wavemetrics to incorporate an exponentially modified Gaussian (EMG) peak model not already included in their software (MultiPeakFit version 1.4 BETA 01). The routine was set up to plot the as-modeled cumulative curve fit for the peaks, the as-modeled deconvoluted individual peak shapes, and the residuals plotted along the same axis; the peak area of each peak based on the individual modeled peak shape was also determined. Two software parameters have been adjusted to better model our desorption peaks. First, a method of fitting a sloping baseline using a cubic polynomial model has been used; it gives a better fit of our data, since our response profiles show varying degrees of baseline slope. Second, the exponential decay constant in the EMG may be constrained or unconstrained, that is, held constant for all peaks, or allowed
to vary with each peak. Fitting using an unconstrained decay constant generally results in unrealistic area values for the finaldesorbing DMMP analyte vapor. Therefore, the exponential decay parameter has been constrained to the same value as the first peak in a series, assuming all peaks in a series should have a similar exponential decay parameter, resulting in better area values for DMMP. RESULTS AND DISCUSSION Preconcentrator Design The outer preconcentrator structure was similar to past preconcentrators with a tube containing the adsorbent material and a resistive heater around the tube for thermal desorption, as shown schematically in Figure 1. However, we implemented a new design for the core of the preconcentrator with two objectives in mind. First, because we were interested in controlled thermal desorption of the vapors from the adsorbent material, we required an effective means of heating of the entire bed of adsorbent across the diameter of the tube. Nonuniform temperature of the adsorbent material would tend to release vapors nonuniformly throughout the temperature ramp cycle, leading to broader peaks and less peak resolution. Second, in prior work1 it was observed that some preconcentrators would suddenly fail. In observations made then and also made more recently in the current study, it has been seen that repeated thermal cycling of porous polymer adsorbents resulted in agglomeration of the material into a single mass of material. As a working hypothesis, we have presumed that preconcentration failures were related to gas stream channeling around the agglomerated mass instead of flow through the adsorbent material. In the new design, the adsorbent material is packed in a cylinder of a highly porous nickel foam. The foam structure, shown in Figure 2, is 95% empty space. This cylinder forms the core of the preconcentrator tube. The metal foam provides rapid heat conduction from the outer heated surface of the preconcentrator to the center of the core. At the same time, dispersal of the adsorbent particles in the metal foam prevents agglomeration into a single mass. We used Tenax as the adsorbent material. The design and construction of the tube to hold the Tenax-loaded metal foam is provided in the Experimental Section. With a metal foam core, Teflon end caps and Teflon tubing, the most thermally conductive component is the metal foam core containing the Tenax sorbent. The thermal characteristics of preconcentrators with and without a metal foam core, each having the same amount of Tenax packing, are compared in Figure 4. Thermal measurements were made at the center of the core and at the periphery of the core inside the preconcentrator tube using thermocouples whose ends were comparable in diameter to a particle of Tenax. Hence, these measurements represent the thermal environment that a Tenax particle experiences. In addition, a measurement was made at the heater on the outside of the tube. Results are shown for a 60-s temperature ramp. Without the metal foam, there is a significant and observable difference between the center and peripheral temperatures as the preconcentrator heats. The periphery of the core heats to the heater temperature, and there is over 10° difference in temperature across the radius of the core. Using the metal foam, the temperature at the center of the core more closely tracks the temperature at the periphery of the core. Hence, the preconcentrator core maintains a much more uniform tem-
Figure 4. Thermal profiles of the preconcentrator without and with a nickel foam core. Both are packed with 25 mg of Tenax. The ramp time is 60 s.
perature across its radius, as intended. We have observed in preliminary experiments conducted at the outset of this investigation and in confirmatory experiments afterward that similarly constructed preconcentrators without metal foam (see the Experimental Section) lead to broader, more overlapped peaks on desorption of vapor mixtures. We also note that no preconcentrator with metal foam has suddenly stopped preconcentrating in our laboratory testing, whereas in the past, unpredictable failures to preconcentrate would occur with Tenax-packed beds. The design, therefore, is achieving our goals. Additional potential advantages of this design are that rapid thermal conduction through the core could prevent localized overheating of the porous polymer, which could lead to adsorbent decomposition and degradation of adsorption behavior and that, in addition, we previously observed a significant flow restriction through packed Tenax preconcentrators at elevated temperatures due to thermal expansion of the polymer,1 whereas this effect is much less when the particles are dispersed in the porous metal in the current design. The preconcentrator temperature was ramped at controllable rates under software control by monitoring the temperature and adjusting the voltage to the resistive heater at an update rate of 35 Hz. This resistive heater was also used to obtain rapid heater temperature feedback due to its resistance temperature detector (RTD) properties. Having the heater as the temperature sensor provides the fast temperature sensor response needed to accurately control fast thermal ramping. Heater control schemes employing separate heater and temperature sensor elements typically suffer from thermal offset and overshoot. To minimize these problems, the temperature control must be sufficiently damped. An overly damped system, however, cannot provide the fast response needed to precisely control the large ∆T (up to 200 °C) preconcentrator thermal ramps. The rapid heater RTD feedback facilitates fast thermal ramping with minimal thermal offset or overshoot. The resistive heater was included as a leg of a simplified Wheatstone bridge, shown in Figure 3. Increasing the input voltage increased current through the heater, increasing the temperature, and changing its resistance. The change in resistance then led to a change in the bridge balance voltage, which was monitored and fed into the temperature control algorithm to Analytical Chemistry, Vol. 77, No. 6, March 15, 2005
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Figure 5. Response profiles for a three-vapor mixture as a function of preconcentrator heating ramp rate, at 10, 60, 120, and 180 s. The vapors are released in the order of MEK, TOL, and DMMP. The traces are offset for clarity.
determine the next input voltage. Further details are provided in the Experimental Section. With this technique, the preconcentrator tube could be ramped from room temperature to 170 °C in a linear fashion in 30 s or longer. When attempting to ramp the same range in 10 s, the heating could not quite keep up with the desired rate. Vapor Mixture Separation. The primary goal of this work was to demonstrate and measure peak separation and resolution by varying the controlled thermal ramp rate of the packed column preconcentrator. We will not focus on the degree of preconcentration, although in general, we have obtained preconcentration factors of 20-25 in this work using 2-min vapor collection periods, for which the degree of preconcentration is determined from peak height. Preconcentration factors depend on how long one collects vapor and at what flow rate and, thus, are not strictly an intrinsic property of the preconcentrator by itself. Ternary mixtures of vapors were generated consisting of methyl ethyl ketone (MEK), toluene (TOL), and dimethyl methylphosphonate (DMMP). These represent a number of vapors with differing functionality and volatility to demonstrate varying desorption rates from the preconcentrator. Vapors desorbed from the preconcentrator were detected with a single polymer-coated FPW device in a low dead volume flow cell. This sensor is described in the Experimental Section. The sensor response peaks observed were nonsymmetrical in shape. Morris has described several reasons why peak tailing may occur in a thermal desorption experiment. 25 We do not attribute the tailing to the FPW sensor response behavior, since we have used similar FPW sensors to detect gas chromatographic peaks with baseline peak widths as small as 1 s and without tailing. The effect of the preconcentrator thermal ramp rate on peak shape and separation is seen clearly in Figure 5. The figure shows response profiles for a three-vapor mixture at four thermal ramp rates, resulting in a family of curves. The thermal ramp rate profiles are shown in the lower traces (referenced to the right y axis), and the vapor peaks detected with the FPW sensor are shown in the upper traces (referenced to the left y axis). The four thermal ramp rates ranged from 15 °C/s (10-s ramp) to 0.83 °C/ (180-s ramp). The ramp maximum temperature was ∼170 °C, and nitrogen sweep gas flow rate was 100 sccm. The vapor concentrations were 2230 mg/m3 MEK, 220 mg/m3 TOL, and 110 mg/m3 DMMP. As the thermal ramp rate becomes slower, the positions of the peak maximums shift to longer time positions and are more 1872 Analytical Chemistry, Vol. 77, No. 6, March 15, 2005
Figure 6. Response profiles for the tertiary vapor mixture of MEK/ TOL/DMMP at a 60-s preconcentrator (2.5 °C/s) thermal ramp. The temperature profile of the preconcentrator thermal ramp is overlaid. First two peaks are constant MEK and TOL concentrations with the third peak due to varying DMMP concentrations. The traces are offset for clarity.
widely separated. At the same time, the peak heights become lower as the peaks become broader. A second family of response profiles is shown in Figure 6. The family of curves shown is for the single preconcentrator thermal ramp rate of 2.5 °C/s (60 s ramp). These are the response profiles for the tertiary vapor mixture of MEK/TOL/DMMP, with varying DMMP vapor concentrations, at 6.9, 13.7, 27.4, 54.8, and 110 mg/ m3, and constant MEK and TOL concentrations, at 2230 mg/m3 and 220 mg/m3, respectively. The preconcentrator ramp temperature is overlaid, referenced on the right-hand y axis. The plot shows the effect of varying one component (DMMP) while maintaining constant the other components (MEK and TOL). The MEK and TOL peak shapes and separation are unaffected by the changing third component (DMMP). Peak areas and peak heights for DMMP increase with increasing DMMP test concentration, as expected. A series of binary mixture tests of MEK-TOL and TOL-DMMP were conducted for comparison to the MEK/TOL/DMMP tertiary mixture tests to determine the impact of adding a third component to a binary mixture. In comparing peak separation times between the pairs of peaks in both the binary mixture tests and tertiary mixture tests, we find there is no significant difference between test results. The addition of a third component did not change the respective peak parameters for the other two components. Peak Resolution. Peaks for all three vapors are seen and partially resolved at all the ramp rates considered in these experiments. At fast ramp rates, the peaks are narrower and the peak heights are greater, but the peak positions are closer together. At slower ramp rates the peak maximum positions are farther apart but the peaks are also much broader. Therefore, it is not immediately obvious to the eye when the peaks are best resolved. Peak resolution is a chromatography term used to quantify the resolution or amount of peak overlap for pairs of peaks.40,41 In general, figures of merit for resolution are calculated as a ratio containing the difference in position of the peak maximums in the numerator and the sum of the peak widths in the denominator. (40) Giddings, J. C. Unified Separation Science; Wiley-Interscience: New York, 1991. (41) Rood, D. A Practical Guide to the Care, Maintenance, and Troubleshooting of Capillary Gas Chromatographic Systems; 3rd rev. ed.; Wiley-VCH: New York, 1999; pp 32-33.
Figure 7. Peak resolution increasing as a function of temperature ramp time. The left axis shows Rs, the peak resolution as described in the text, where squares correspond to resolution of MEK and TOL and the circles correspond to resolution between TOL and DMMP. The peak heights as a function of ramp time are shown as dashed lines referenced to the right y axis, where the triangles pointing up are for DMMP, the triangles pointing down are for TOL, and the diamonds are for MEK.
These formulas are generally derived assuming symmetrical Gaussian peaks and equal height peaks. The peak width may be expressed in terms of peak width at half-height (pwhh) although it may be expressed in terms of peak width at the base or peak width in terms of the standard deviation, σ, of a Gaussian distribution. Recognizing that our peaks are not Gaussian, we avoided definitions in terms of standard deviation, σ. And since the peak width at the baseline is not measurable in our mixture analyses, we used peak width at half-height. We used the expression shown in eq 1 for peak resolution factor, Rs, as an empirical formula to provide a measure of peak overlap, where tr values are peak retention times for the two peaks. 41
Rs ) 1.18(tr1 - tr2 )/(pwhh1 + pwhh2)
(1)
(The value of the coefficient in eq 1 depends on the measure of peak width being used.) The values obtained provide an indication of peak resolution where higher values indicate less overlap between two peaks. For Gaussian peaks of equal height in chromatography, a value greater than 0.5 is required to observe separate peak maximums; a value greater than 1.5 indicates baseline resolution with increasing baseline between the peaks as the value becomes larger. Peak resolutions calculated as just described are plotted in Figure 7 with reference to the left y axis. Peak heights referenced to the right y axis are included for comparison. It can be seen that by this measure, the resolution improves with increasing thermal ramp time up to ∼120 s. Resolution improved even as the peaks were getting broader. Therefore, a controlled thermal ramp can improve separation, which was the goal of this work. A slower thermal ramp, however, results in broader peaks and lower peak heights at the same time that it improves resolution.
If peak heights are used as the measure of vapor quantity, increasing the resolution reduces the sensitivity, which partially offsets the gain in sensitivity obtained by preconcentration. It is interesting to note, however, that the proportional reduction in peak height is much lower for the more slowly desorbing species, DMMP, than for the more rapidly desorbing species, MEK (see Figures 5 and 7). Therefore, the significance of a decrease in sensitivity as defined by peak height depends on the analyte of interest. For DMMP, a simulant for more toxic organophosphorus compounds, the loss in sensitivity as defined by peak heights is only a factor of ∼2. Peak Modeling. Traditionally, the measured signal from preconcentrator desorption peaks has been the peak height. In principle, the peak area should also provide a quantitative measure related to the amount of vapor desorbed. However, these areas can be hard to obtain, particularly for nonsymmetrical desorption peaks and overlapping peaks. We investigated curve-fitting methods to model the detected desorption peaks and to extract individual peaks from overlapping peak profiles. Several different peak models were tested for best fit to single vapor and vapor mixture peak profiles obtained upon preconcentrator desorption, with primary emphasis on the symmetric Gaussian and the nonsymmetric exponentially modified Gaussian (EMG). In general, models assuming symmetrical peak shapes performed poorly, whereas the EMG model performed the best. The model reported by Morris et al.25 was also examined but did not fit our curves very well. Curve-fitting models using EMG functions are based on combining the symmetric Gaussian model with an exponential decay model. Such models have been used for modeling gas chromatographic peaks and detector peaks in flow injection analysis42,43 The result provides an expression, such as that in eq 2, that works over the full range of symmetric to nonsymmetric peaks with varying degrees of exponential decay.
[ ( ) ( )] ∫
1 σG A hEMG(t) ) exp τ 2 τ
2
-
t - tG τ
z
-∞
exp((-y2/2))
x2π
dy (2)
Key parameters in this equation for the peak height at time t, hEMG(t), are the retention time, tG, the standard deviation of the Gaussian component, σG, and the time constant of the exponential decay component, τ. The parameter z is (t - tG)/σG - (σG/τ). The peak area is given by A. Figure 8 shows an example of the curve-fitting and modeling we have done on one of our typical tertiary mixture response profiles, selected at the thermal ramp rate of 2.5 °C/s. The figure shows the raw sensor response profile data as open circles, the best-fit EMG-modeled cumulative curve fit over the three-peak subset as a solid thick line, and the as-modeled deconvoluted individual peaks as solid, thin lines. The preconcentrator desorption ramp temperature is plotted on the main plot, referenced to the righthand y axis. The residuals are plotted above the main plot. We found that modeling with a simple Gaussian model or other models assuming symmetrical peaks may result in residuals that are up to nearly 2 orders of magnitude higher than those obtained using the EMG modeling procedure. (42) Jeansonne, M. S.; Foley, J. P. J. Chromatogr. Sci. 1991, 29, 258-266. (43) Jeansonne, M. S.; Foley, J. P. J. Chromatogr. 1992, 594, 1-8.
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Figure 8. Plot of modeled peaks, using the exponentially modified Gaussian fit. The open circles are the raw data, the solid curve is the composite modeled peaks, and the underlying peak traces are the individual modeled peaks. The linear ramp is the preconcentrator temperature with reference to the right y axis.
Figure 9. Comparison of mixture to pure compound. Mixture of MEK + TOL + DMMP peaks compared with pure compound DMMP, plus modeled DMMP peak from mixture, all at 2.5 °C/s ramp rate. DMMP test concentration was 55 mg/m3.
Figure 9 compares the modeled peak from a mixture test compared with the peak shape obtained from a single vapor test. The top curve is the raw response profile of the tertiary mixture, with DMMP as the third peak. The middle curve is the modeled DMMP peak extracted from the mixture response profile using the EMG modeling. The bottom curve is the DMMP peak obtained in single vapor measurements. All are obtained using a 2.5 °C/s thermal desorption ramp rate for the preconcentrator and a DMMP concentration of 55 mg/m3. The modeled peak extracted from the mixture data provides a reasonable match to the single-vapor data. Peak Areas. The curve-fit and peak modeling method allows peak areas to be extracted as a measure of vapor quantity. Ideally, these areas would be independent of thermal ramp rate. However, the 2 s/data point rate of data collection was insufficient for good modeling of peaks at fast thermal ramp rates, since there were an inadequate number of points per peak. We developed a faster data acquisition method, described in the Experimental Section, to obtain faster data collection while maintaining good frequency resolution. For example, an 8-MHz signal can be counted with 1-Hz resolution in 0.1 s using the fast frequency counting method. 1874 Analytical Chemistry, Vol. 77, No. 6, March 15, 2005
Figure 10. DMMP peak areas determined using an exponentially modified Gaussian model for curve-fitting and peak area calculation, shown for varying preconcentrator thermal ramp rates. The DMMP was present in ternary mixtures containing methyl ethyl ketone and toluene at concentrations of 559 mg/m3 and 130 mg/m3, respectively, with a maximum preconcentrator temperature of 200 °C.
Using this faster data collection method, we collected another data set and determined calibration peak areas for DMMP in ternary mixtures at various thermal ramp rates. Results for thermal ramp times of 30, 60, and 120 s duration are shown in Figure 10, which represents the range over which resolution improves with increasing ramp time (decreasing ramp rate). The calibration curves using peak areas are essentially independent of the thermal ramp rate. Finally, repeatability was evaluated by extracting peak areas for DMMP in a ternary mixture over 10 replicates, using a thermal ramp time of 30 s, a maximum preconcentrator temperature of 200 °C, and vapor concentrations of DMMP at 82.3 mg/m3, toluene at 130 mg/m3, and methyl ethyl ketone at 559 mg/m3. The relative standard deviation was 8.6%. Discussion. We have demonstrated a new preconcentrator architecture designed for the partial separation of vapor mixtures through a programmed thermal desorption process. Previously, partial preseparation of vapors was observed for preconcentrators ramping from room temperature to temperatures around 200 °C at rates from over 10 °C/s1 to rates as slow as 10 °C/min.25 Recently, Nakamoto et al. have shown partial separation of a twocomponent mixture from a preconcentrator with linear ramping at 6 and 1.5 °C/s. 18 In this paper, we have examined the effect of the ramping time on the resolution of peaks from such preconcentrators. Furthermore, we designed the preconcentrator specifically for this purpose, developing an architecture for rapid thermal transfer from the outer heated periphery to the center of the core, using metal foam as the thermal conduction medium. The approach is extensible to other sorbent materials in addition to Tenax. For example, we have recently used Carboxen 569, crushed and sieved to a 60/80 mesh size from the as-received 20/40 mesh, as the sorbent packed in the metal foam. We observed that toluene/DMMP mixtures produced a single peak when ramped from room temperature to 370 °C in 60 s, whereas two-peak maximums were observable when the ramp duration was 180 s. Although preconcentrator operation has been demonstrated in this paper using a single polymer-coated microsensor as the detector, our ultimate aim is that such preconcentrators will be used with a multivariate detector and advanced chemometrics. The detector could be a sensor array, an ion mobility spectrom-
eter, or even a mass spectrometer. The use of a multivariate detector, such as a sensor array in combination with at least partial temporal vapor separation, creates a system that can take advantage of advanced chemometric methods for better chemical information extraction. Mathematically, this approach represents a second-order system, whereas a sensor array by itself is only a first-order system.33 Unlike a simple array, a second-order system can quantify analytes in the presence of unknown interferences. This is an important capability to obtain, since unknown interferences are likely in field applications. Hence, the addition of a preconcentrator and advanced chemometrics to a sensor array system can overcome some of the limitations of the array alone, even if the preseparation achieved with the preconcentrator does not provide baseline resolution (i.e., resolution values of 1.5 or better). Initial work toward using a preconcentrator/SAW array system as a multiway system was reported by Shaffer et al.14 A further advantage of the preseparator combination with a multivariate detector is that multivariate curve resolution techniques can be used to mathematically resolve the overlapping peaks, even at low resolutions.44-48 These methods are used to quantify analytes in mixtures and to obtain the pure component spectra, even at resolutions below 0.5 where separate peak maximums are not seen. In our own modeling studies with a six(44) Gargallo, R.; Tauler, R.; Cuesta-Sanchez, F.; Massart, D. L. TrAC, Trends Anal. Chem. 1996, 15, 279-286. (45) Osten, D. W.; Kowalski, B. R. Anal. Chem. 1984, 56, 991-995. (46) Rodriguez-Cuesta, M. J.; Boque, R.; Xavier Rius, F. Anal. Chim. Acta 2003, 476, 111-122. (47) Strasters, J. K.; Billiety, A. H.; deGalan, L.; Vandeginste, B. G. M.; Kateman, G. Anal. Chem. 1988, 60, 2745-2751. (48) Tauler, R. Chemom. Intel. Lab. Sys. 1995, 30, 133-146. (49) Wise, B. M.; Gallagher, N. B.; Grate, J. W. Unpublished results. (50) Grate, J. W.; Wise, B. M.; Abraham, M. H. Anal. Chem. 1999, 71, 45444553. (51) Grate, J. W.; Wise, B. M. Anal. Chem. 2001, 73, 2239-2244. (52) Grate, J. W.; Patrash, S. J.; Kaganove, S. N.; Abraham, M. H.; Wise, B. M.; Gallagher, N. B. Anal. Chem. 2001, 73, 5247-5259. (53) Wise, B. M.; Gallagher, N. B.; Grate, J. W. J. Chemom. 2003, 17, 463-469. (54) Grate, J. W.; Wise, B. M.; Gallagher, N. B. Anal. Chim. Acta 2003, 490, 169-184.
SAW sensor array and two overlapping Gaussian peaks, we have also found good performance at resolutions below 0.5.49 Hence, there is great value in obtaining even partial temporal resolution of vapor mixtures. Morris et al. reported the use of multivariate curve resolution in conjunction with their thermally ramped preconcentrator and semiconductor sensor array.25 Finally, the ability to obtain pure component patterns from multivariate curve resolution techniques enables the use of new classification techniques. We have developed a method of classification that transforms pure component vapor patterns into descriptors of the vapor solubility properties.50-54 It was originally derived for sensors responding to the amount of the vapor sorbed regardless of other vapor properties, where the amount is a mass. It was then extended to sensors responding to the amount of sorbed vapor as a volume, and it has more recently been shown to be useful for the single vapor responses of polymer-coated SAW devices even if the response is not purely gravimetric. However, it has not yet been extended to vapor mixtures. Using a preseparator/array instrument and multivariate curve resolution, pure component patterns can be extracted which could then be classified by this new method. ACKNOWLEDGMENT The authors are grateful for funding from the United States Department of Energy, National Nuclear Security Administration, Office of Nonproliferation Research and Engineering, NA-22. The research was performed at the W. R. Wiley Environmental Molecular Sciences Laboratory, a national scientific user facility sponsored by the U.S. Department of Energy’s Office of Biological and Environmental Research and located at Pacific Northwest National Laboratory. The Pacific Northwest National Laboratory is a multiprogram national laboratory operated for the Department of Energy by Battelle Memorial Institute. Received for review June 10, 2004. Accepted December 24, 2004. AC049142S
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