Effects of Temperature and Humidity on the Performance of Polymer-Coated Surface Acoustic Wave Vapor Sensor Arrays

Abstract

The influences of temperature and atmospheric humidity on the performance of an array of eight polymer-coated 158-MHz surface acoustic wave vapor sensors were investigated. Sensitivities to the seven organic vapors examined all exhibited negative Arrhenius temperature dependencies, with responses increasing by factors of 1.5-4.4 on going from 38 to 18 degrees C. The magnitudes of the temperature effects, while generally similar, differed sufficiently among certain sensor-vapor combinations to cause marked changes in vapor response patterns. In addition, it was found that operating identically coated sensors at different temperatures could provide a means for discriminating certain vapors. The changes in sensor responses with temperature agreed reasonably well with those expected assuming ideal vapor sorption behavior and indicated that changes in the moduli of the sensor coatings were not important mediating factors. Responses to relative humidity (RH) from 0 to 85% RH were important even for the nonpolar sensor coatings. Significant changes in the sensitivities to the organic vapors were observed as a function of atmospheric humidity for several sensor-vapor combinations, which, in turn, affected the patterns of responses obtained from the sensor array. Results indicate that small changes in temperature or humidity have a larger effect on baseline stabilities than on the responses to the vapors. Monte Carlo simulations of sensor responses show that the ability to discriminate vapors in binary and ternary mixtures using a four-sensor array remains high regardless of the operating temperature and ambient humidity, provided that temperature-or humidity-induced changes in the response patterns are taken into account.

Analysis of Solvent Vapors in Breath and Ambient Air with a Surface Acoustic Wave Sensor Array

“…Immunity from humidity effects was demonstrated here and is consistent with previous studies of this issue with SAW sensor arrays conducted over more limited ranges of RH (Park and Zellers, 2000a,b;Zellers and Han, 1996). This was accomplished by using a drying agent (Drierite®) to condition purge and sensor array air streams, and a specially selected adsorbent that permits purging of water vapor with retention of organic vapors in the preconcentration unit prior to thermal desorption.…”

“…PIB, PECH, PDPP, and ABC are amorphous rubbery solids and OV-275 is a viscous liquid at room temperature. These polymers were selected as sensor coatings for the array on the basis of previous studies indicating that response patterns derived from them provide a relatively high degree of selectively among solvent vapors within and between structural classes (Zellers and Han, 1996;Zellers et al, 1995) Coatings were applied to thicknesses in the range of 20-30 nm, corresponding to a frequency shift of~225 kHz (Grate and Klusty, 1991;, using an airbrush and a dilute solution of each polymer in chloroform.…”

“…SAW sensors detect changes in the mass and viscoelastic properties of interfacial surface-coating films (Grate and Zellers, 2000;Martin et al, 1994). Responses are rapid and reversible, isotherms are linear over fairly wide ranges of vapor concentration, and responses to vapor mixtures are generally additive Zellers and Han, 1996;Zellers et al, 1995). It has been shown that an array of only 3-6 SAW sensors coated with a diverse set of amorphous polymers can produce characteristic response patterns for identifying and quantifying a large number of individual vapors and the components of various vapor mixtures (Park et al, 1999Cai et al, 2000;Zellers and Han, 1996;Zellers et al, 1993Zellers et al, , 1995Grate et al, 1993;Patrash and Zellers, 1993; al., 1988;Wohltjen, 1984).…”

“…Responses are rapid and reversible, isotherms are linear over fairly wide ranges of vapor concentration, and responses to vapor mixtures are generally additive Zellers and Han, 1996;Zellers et al, 1995). It has been shown that an array of only 3-6 SAW sensors coated with a diverse set of amorphous polymers can produce characteristic response patterns for identifying and quantifying a large number of individual vapors and the components of various vapor mixtures (Park et al, 1999Cai et al, 2000;Zellers and Han, 1996;Zellers et al, 1993Zellers et al, , 1995Grate et al, 1993;Patrash and Zellers, 1993; al., 1988;Wohltjen, 1984). Previous studies from our laboratory have shown that instrumentation similar to that reported on here can be used for several occupational hygiene applications, including personal exposure monitoring and the determination of solvents permeating through chemical protective clothing Park and Zellers, 2000a,b).…”

“…Among these is the extended disjoint principal components regression (EDPCR) method that we have used to analyze SAW sensor array response data in a number of recent studies (Zellers et al, , 1995Park et al, 2000;Cai et al, 2000;Park et al, 1999;Zellers and Han, 1996;Park and Zellers, 2000a,b). Artificial neural networks (ANN) have also been successfully applied to the problem of classifying sensor responses Eklov and Lundstrom, 1999;Jurs et al, 2000;Hierlemann et al, 1995;Gardner et al, 1992;Shaffer and RosePehrsson, 1999).…”