Effects of temperature and humidity on the performance of polymer-coated surface acoustic wave vapor sensor arrays

A Novel Temperature Drift Compensation Algorithm for Liquid-Level Measurement Systems

Aiming at the problem that ultrasonic detection is greatly affected by temperature drift, this paper investigates a novel temperature compensation algorithm. Ultrasonic impedance-based liquid-level measurement is a crucial non-contact, non-destructive technique. However, temperature drift can severely affect the accuracy of experimental measurements based on this technology. Theoretical analysis and experimental research on temperature drift phenomena are conducted in this study, accompanied by the proposal of a new compensation algorithm. Leveraging an external fixed-point liquid-level detection system experimental platform, the impact of temperature drift on ultrasonic echo energy and actual liquid-level height is examined. Experimental results demonstrate that temperature drift affects the speed and attenuation of ultrasonic waves, leading to decreased accuracy in measuring liquid levels. The proposed temperature compensation method yields an average relative error of 3.427%. The error range spans from 0.03 cm to 0.336 cm. The average relative error reduces by 21.535% compared with before compensation, showcasing its applicability across multiple temperature conditions and its significance in enhancing the accuracy of ultrasonic-based measurements.

Analysis of Multivariable Sensor Responses to Multi-Analyte Gas Samples in the Presence of Interferents and Humidity

This work presents an adaptive sensor signal-processing approach to enable quantification, using a single gas sensor or a small sensor array, of multianalyte mixtures of aromatic hydrocarbons in the presence of various interferents and humidity for environmental-monitoring applications. Dynamic sensor responses are analyzed by extracting multivariable sensing parameters to provide necessary sensitivity and selectivity. This is achieved by integrating the Levenberg-Marquardt-modified, exponentially weighted, recursive-least-squares-estimation (LM-modified EW-RLSE) algorithm and principal-component analysis (PCA). Achieving measured detection limits as low as 3 μg/L (≤1 ppm by volume) for 6 target analytes, the system exhibits excellent PCA cluster separation for all analytes in the mixtures, with reliable identification and accurate quantification, even in the presence of various interferents. Concentration errors of approximately ±5% are obtained for mixtures containing up to 6 BTEX compounds (including chemical isomers) and up to 4 interferents. Additionally, the study investigates the impact of humidity on the polymer/plasticizer-coated shear-horizontal surface acoustic wave (SH-SAW) sensors, demonstrating accurate concentration estimation in a relative humidity range from dry nitrogen to 65%. This sensing-and-multivariate-signal-processing approach is a promising candidate for reliable environmental monitoring in real-world applications.

Hydrogen-Bond Acidic Materials in Acoustic Wave Sensors for Nerve Chemical Warfare Agents' Detection

The latest trends in the field of the on-site detection of chemical warfare agents (CWAs) involve increasing the availability of point detectors to enhance the operational awareness of commanders and soldiers. Among the intensively developed concepts aimed at meeting these requirements, wearable detectors, gas analyzers as equipment for micro- and mini-class unmanned aerial vehicles (UAVs), and distributed sensor networks can be mentioned. One of the analytical techniques well suited for use in this field is surface acoustic wave sensors, which can be utilized to construct lightweight, inexpensive, and undemanding gas analyzers for detecting CWAs. This review focuses on the intensively researched and developed variant of this technique, utilizing absorptive sensor layers dedicated for nerve CWAs' detection. The paper describes the mechanism of the specific interaction occurring between the target analyte and the sensing layer, which serves as the foundation for their selective detection. The main section of this paper includes a chronological review of individual achievements in the field, largely based on the peer-reviewed scientific literature dating back to the mid-1980s to the present day. The final section presents conclusions regarding the prospects for the development of this analytical technique in the targeted application.

Polymer-Plasticizer Coatings for BTEX Detection Using Quartz Crystal Microbalance

Sensing films based on polymer–plasticizer coatings have been developed to detect volatile organic compounds (VOCs) in the atmosphere at low concentrations (ppm) using quartz crystal microbalances (QCMs). Of particular interest in this work are the VOCs benzene, ethylbenzene, and toluene which, along with xylene, are collectively referred to as BTEX. The combinations of four glassy polymers with five plasticizers were studied as prospective sensor films for this application, with PEMA-DINCH (5%) and PEMA-DIOA (5%) demonstrating optimal performance. This work shows how the sensitivity and selectivity of a glassy polymer film for BTEX detection can be altered by adding a precise amount and type of plasticizer. To quantify the film saturation dynamics and model the absorption of BTEX analyte molecules into the bulk of the sensing film, a diffusion study was performed in which the frequency–time curve obtained via QCM was correlated with gas-phase analyte composition and the infinite dilution partition coefficients of each constituent. The model was able to quantify the respective concentrations of each analyte from binary and ternary mixtures based on the difference in response time (τ) values using a single polymer–plasticizer film as opposed to the traditional approach of using a sensor array. This work presents a set of polymer–plasticizer coatings that can be used for detecting and quantifying the BTEX in air, and discusses the selection of an optimum film based on τ, infinite dilution partition coefficients, and stability over a period of time.

Sensitive Materials and Coating Technologies for Surface Acoustic Wave Sensors

Since their development, surface acoustic wave (SAW) devices have attracted much research attention due to their unique functional characteristics, which make them appropriate for the detection of chemical species. The scientific community has directed its efforts toward the development and integration of new materials as sensing elements in SAW sensor technology with a large area of applications, such as for example the detection of volatile organic compounds, warfare chemicals, or food spoilage, just to name a few. Thin films play an important role and are essential as recognition elements in sensor structures due to their wide range of capabilities. In addition, other requisites are the development and application of new thin film deposition techniques as well as the possibility to tune the size and properties of the materials. This review article surveys the latest progress in engineered complex materials, i.e., polymers or functionalized carbonaceous materials, for applications as recognizing elements in miniaturized SAW sensors. It starts with an overview of chemoselective polymers and the synthesis of functionalized carbon nanotubes and graphene, which is followed by surveys of various coating technologies and routes for SAW sensors. Different coating techniques for SAW sensors are highlighted, which provides new approaches and perspective to meet the challenges of sensitive and selective gas sensing.

A novel three-dimensional Ag nanoparticles/reduced graphene oxide microtubular field effect transistor sensor for NO2 detections

A novel three-dimensional (3D) microtubular NO2 field effect transistor (FET) sensor has been fabricated from 2D reduced graphene oxide (rGO) nanosheets decorated with Ag nanoparticles, by applying the self-roll-up technique. The electrical properties of 2D and 3D Ag NP/rGO FET sensors have been investigated and compared. Finally, the performance of the 3D sensors has been demonstrated, where the preliminary results show that our 3D Ag NP/rGO FET NO2 sensor exhibits a relatively fast response (response time of 116 s) to 20 parts per million NO2 with a response of 4.92% at room temperature at zero bias voltage and 2 V source-drain bias voltage. Moreover, characteristics of our 3D Ag NP/rGO FET sensors, e.g. response, response and recovery times, have been demonstrated to be tuned by adjusting the applied source-drain and gate biases. Compared to the 2D geometry, our 3D geometry occupies less device area, but with the same sensing area. This study provides a new way to optimize sensing device performance, and promotes its development for miniaturized and integrated gas-sensing applications for indoor health and safety detection, outdoor environmental monitoring, industrial pollution monitoring and beyond.

Effects of temperature and humidity on the performance of a PECH polymer coated SAW sensor

The influences of environment, such as temperature, humidity and interfering gases, on the performance of a surface acoustic wave (SAW) sensor in the detection of 2-chloroethyl ethyl sulfide (CEES) were invested. The 150 MHz SAW dual delay lines were used, coated with a poly(epichlorohydrin) (PECH) thin layer, and CEES was detected under different concentrations. Linear correlation between the frequency-shift and the exposure time of the sensor to CEES could be observed, and the limit of CEES could be detected as low as 1.5 mg m-3. Under different temperature (0-50 C°) and humidity (30-80% RH) conditions, CEES was detected by the fabricated SAW sensor coated with PECH, the frequency shifts were measured and the performance of the sensor was evaluated. The results proved that temperature and humidity were the most important factors to influence the performance of SAW sensors; with the decreasing of temperature and the increasing of humidity, there would be larger frequency shifts. In the interference experiments, it was found that most gases existing in the environment in high concentrations would not influence the detection of CEES. Then, the SAW sensor having been fabricated was kept under the conditions of 25 °C and 35% RH for 18 months to further verify the quality, and CEES was detected every so many months. It proved that the performance of the sensor would decrease about 16.39% after 18 months. Although it reflected the attenuation of the sensor to some extent, the sensor was still in good condition. Additionally, the related mechanisms were also discussed.

Electronic Nose for Recognition of Volatile Vapor Mixtures Using a Nanopore-Enhanced Opto-Calorimetric Spectroscopy

An electronic nose (e-nose) for identification and quantification of volatile organic compounds (VOCs) vapor mixtures was developed using nanopore-enhanced opto-calorimetric spectroscopy. Opto-calorimetric spectroscopy based on specific molecular vibrational transitions in the mid infrared (IR) "molecular fingerprint" regime allows highly selective detection of VOCs vapor mixtures. Nanoporous anodic aluminum oxide (AAO) microcantilevers, fabricated using a two-step anodization and simple photolithography process, were utilized as highly sensitive thermomechanical sensors for opto-calorimetric signal transduction. The AAO microcantilevers were optimized by fine-tuning AAO nanopore diameter in order to enhance their thermomechanical sensitivity as well as their surface area. The thermomechanical sensitivity of a bilayer AAO microcantilever with a 60 nm pore diameter was approximately 1 μm/K, which is far superior to that of a bilayer plain silicon (Si) microcantilever. The adsorbed molecules of VOCs mixtures on the AAO microcantilever were fully recognized and quantified by variations of peak positions and amplitudes in the opto-calorimetric IR spectra as well as by shifts in the resonance frequency of the AAO microcantilever with the adsorbed molecules. Furthermore, identification of complex organic compounds with a real industrial sample was demonstrated by this e-nose system.

DNA gold nanoparticle nanocomposite films for chemiresistive vapor sensing

Chemiresistive vapor sensors combining functionalized gold nanoparticles and single-stranded DNA oligomers are investigated to enhance specificity in chemical sensing. Sensors are made by depositing DNA-functionalized gold nanoparticles onto microfabricated electrodes using four distinct sequences. Sensor performance is evaluated for response to relative humidity and exposure to vapor analytes including ethanol, methanol, hexane, dimethyl methylphosphonate, and toluene under different relative humidity. It is found that sensors display a nonmonotonic resistance change toward increasing humidity due to the combined effects of hydration induced swelling and ionic conduction. Responses to vapor analytes show sequence-dependent patterns as well as a strong influence of humidity. Overall, the findings are encouraging for using DNA oligomers to enhance specificity in chemical sensing.

A Passive Radio-Frequency Identification (RFID) Gas Sensor With Self-Correction Against Fluctuations of Ambient Temperature

Uncontrolled fluctuations of ambient temperature in the field typically greatly reduce accuracy of gas sensors. In this study, we developed an approach for the self-correction against fluctuations of ambient temperature of individual gas and vapor sensors. The main innovation of our work is in the temperature correction which is accomplished without the need for a separate uncoated reference sensor or a separate temperature sensor. Our sensors are resonant inductor-capacitor-resistor (LCR) transducers coated with sensing materials and operated as multivariable passive (battery-free) radio-frequency identification (RFID) sensors. Using our developed approach, we performed quantitation of an exemplary vapor over the temperature range from 25 to 40 °C. This technical solution will be attractive in numerous applications where temperature stabilization of a gas sensor or addition of auxiliary temperature or uncoated reference sensors is prohibitive.

The impact of water and hydrocarbon concentration on the sensitivity of a polymer-based quartz crystal microbalance sensor for organic compounds

Long-term environmental monitoring of organic compounds in natural waters requires sensors that respond reproducibly and linearly over a wide concentration range, and do not degrade with time. Although polymer coated piezoelectric based sensors have been widely used to detect hydrocarbons in aqueous solution, very little information exists regarding their stability and suitability over extended periods in water. In this investigation, the influence of water aging on the response of various polymer membranes [polybutadiene (PB), polyisobutylene (PIB), polystyrene (PS), polystyrene-co-butadiene (PSB)] was studied using the quartz crystal microbalance (QCM). QCM measurements revealed a modest increase in sensitivity towards toluene for PB and PIB membranes at concentrations above 90 ppm after aging in water for 4 days. In contrast, the sensitivity of PS and PSB coated QCM sensors depended significantly on the toluene concentration and increased considerably at concentrations above 90 ppm after aging in water for 4 days. Attenuated total reflectance Fourier transform infrared spectroscopy (ATR-FTIR) showed that there is a change in the sorption mechanism at higher toluene levels for PS and PSB. Positron annihilation lifetime spectroscopy (PALS) studies were performed to investigate the free volume properties of all polymers and to monitor any changes in the free volume size and distribution due to water and toluene exposure. The PALS did not detect any considerable variation in the free volume properties of the polymer films as a function of solution composition and soaking time, implying that viscoelastic and/or interfacial processes (i.e. surface area changes) are probably responsible for variations in the QCM sensitivity at high hydrocarbon concentrations. The results suggest that polymer membrane conditioning in water is an issue that needs to be considered when performing QCM measurements in the aqueous phase. In addition, the study shows that the hydrocarbon response is concentration dependant for polymers with a high glass transition temperature, and this feature is often neglected when comparing sensor sensitivity in the literature.

Environmental monitoring of hydrocarbons: a chemical sensor perspective

Assessing the environmental impact of organic pollutants requires reliable analytical tools that can rapidly screen them with minimal sample handling. Chemical sensors are expected to play an increasing role in environmental monitoring, and recent technological advances are certain to facilitate the application of chemical sensing devices. The search for highly selective, sensitive, low cost, stable, and robust sensors for hydrocarbons is an area of interest that is reflected by many publications on this topic. This report surveys some of the work that has been undertaken using sensors to detect hydrocarbons in the gas and liquid phase. The analytical capabilities of various sensors are compared and discussed in terms of their selectivity, sensitivity, and detection limit. It was found that the sensitivity is highly dependent on the experimental conditions used in the preparation of the sensing surface. Many sensors display acceptable sensitivity under controlled laboratory conditions; however, very few are selective enough to distinguish among several hydrocarbons in complex mixtures. Selectivity is still a challenge that is hindering the widespread application of chemical sensors for environmental monitoring of hydrocarbons and a number of strategies have been proposed to help overcome some of these problems.

Facile hyphenation of gas chromatography and a microcantilever array sensor for enhanced selectivity

The very simple coupling of a standard, packed-column gas chromatograph with a microcantilever array (MCA) is demonstrated for enhanced selectivity and potential analyte identification in the analysis of volatile organic compounds (VOCs). The cantilevers in MCAs are differentially coated on one side with responsive phases (RPs) and produce bending responses of the cantilevers due to analyte-induced surface stresses. Generally, individual components are difficult to elucidate when introduced to MCA systems as mixtures, although pattern recognition techniques are helpful in identifying single components, binary mixtures, or composite responses of distinct mixtures (e.g., fragrances). In the present work, simple test VOC mixtures composed of acetone, ethanol, and trichloroethylene (TCE) in pentane and methanol and acetonitrile in pentane are first separated using a standard gas chromatograph and then introduced into a MCA flow cell. Significant amounts of response diversity to the analytes in the mixtures are demonstrated across the RP-coated cantilevers of the array. Principal component analysis is used to demonstrate that only three components of a four-component VOC mixture could be identified without mixture separation. Calibration studies are performed, demonstrating a good linear response over 2 orders of magnitude for each component in the primary study mixture. Studies of operational parameters including column temperature, column flow rate, and array cell temperature are conducted. Reproducibility studies of VOC peak areas and peak heights are also carried out showing RSDs of less than 4 and 3%, respectively, for intra-assay studies. Of practical significance is the facile manner by which the hyphenation of a mature separation technique and the burgeoning sensing approach is accomplished, and the potential to use pattern recognition techniques with MCAs as a new type of detector for chromatography with analyte-identifying capabilities.

Multianalyte Chemical Identification and Quantitation Using a Single Radio Frequency Identification Sensor

We demonstrate an approach for multianalyte chemical identification and quantitation using a single conventional radio frequency identification (RFID) tag that has been adapted for chemical sensing. Unlike other approaches of using RFID sensors, where a special tag should be designed at a much higher cost, we utilize a conventional RFID tag and coat it with a chemically sensitive film. As an example, we demonstrate detection of several vapors of industrial, health, law enforcement, and security interest (ethanol, methanol, acetonitrile, water vapors) with a single 13.56-MHz RFID tag coated with a solid polymer electrolyte sensing film. By measuring simultaneously several parameters of the complex impedance from such an RFID sensor and applying multivariate statistical analysis methods, we were able to identify and quantify several vapors of interest. With a careful selection of the sensing film and measurement conditions, we achieved parts-per-billion vapor detection limits in air. These RFID sensors are very attractive as ubiquitous multianalyte distributed sensor networks.

Chamber evaluation of a portable GC with tunable retention and microsensor-array detection for indoor air quality monitoring

The evaluation of a novel prototype instrument designed for on-site determinations of VOC mixtures found in indoor working environments is described. The instrument contains a miniature multi-stage preconcentrator, a dual-column separation module with pressure-tunable retention capabilities, and an integrated array of three polymer-coated surface acoustic wave sensors. It was challenged with dynamic test-atmospheres of a set of 15 common indoor air contaminants at parts-per-billion concentrations within a stainless-steel chamber under a range of conditions. Vapours were reliably identified at a known level of confidence by combining column retention times with sensor-array response patterns and applying a multivariate statistical test of pattern fidelity for the chromatographically resolved vapours. Estimates of vapour concentrations fell within 7% on average of those determined by EPA Method TO-17, and limits of detection ranged from 0.2 to 28 ppb at 25 degrees C for 1 L samples collected and analyzed in <12 min. No significant humidity effects were observed (0-90% RH). Increasing the chamber temperature from 25 to 30 degrees C reduced the retention times of the more volatile analytes which, in turn, demanded alterations in the scheduling of column-junction-point pressure (flow) modulations performed during the analysis. Reductions in sensor sensitivities with increasing temperature were predictable and similar among the sensors in the array such that most response patterns were not altered significantly. Short-term fluctuations in concentration were accurately tracked by the instrument. Results indicate that this type of instrument could provide routine, semi-autonomous, near-real-time, multi-vapour monitoring in support of efforts to assess air quality in office environments.

Limits of recognition for simple vapor mixtures determined with a microsensor array

The "limit of recognition" (LOR) has been defined as the minimum concentration at which reliable individual vapor recognition can be achieved with a multisensor array, and methodology for determining the LORs of individual vapors probabilistically on the basis of sensor array response patterns has been reported. This article explores the problems of defining and evaluating LORs for vapor mixtures in terms of the absolute and relative component vapor concentrations, where the mixture must be discriminated from those component vapors and from the subset of possible lower-order component mixtures. Monte Carlo simulations and principal components regression analyses of an extant database of calibrated responses to a set of 16 vapors from an array of 6 diverse polymer-coated surface acoustic wave sensors are used to illustrate the approach and to examine trends in LOR values among the 120 possible binary mixtures and 560 possible ternary mixtures in the data set. At concentrations exceeding the LOD, 89% of the binary mixtures could be reliably recognized (<5% error) over some composite concentration range, while only 3% of the ternary mixtures could be recognized. Most binary mixtures could be recognized only if the constituent vapor relative concentration ratio, defined in terms of multiples of the LOD for each vapor, was < or =20. Correlations with the Euclidean distance(s) separating the normalized constituent vapor response vectors allow reasonably accurate predictions of the limiting recognizable mixture composition ranges for binary and ternary cases. Results are considered in the context of using microsensor arrays for vapor detection and recognition in microanalytical systems.

Laboratory and field evaluation of a SAW microsensor array for measuring perchloroethylene in breath

This article describes the laboratory and field performance evaluation of a small prototype instrument employing an array of six polymer-coated surface acoustic wave (SAW) sensors and a thermal desorption preconcentration unit for rapid analysis of perchloroethylene in breath. Laboratory calibrations were performed using breath samples spiked with perchloroethylene to prepare calibration standards spanning a concentration range of 0.1-10 ppm. A sample volume of 250 mL was preconcentrated on 40 mg of Tenax GR at a flow rate of 100 mL/min, followed by a dry air purge and thermal desorption at a temperature of 200 degrees C. The resulting pulse of vapor was passed over the sensor array at a flow rate of 20 mL/min and sensor responses were recorded and displayed using a laptop computer. The total time per analysis was 4.5 min. SAW sensor responses were linear, and the instrument's limit of detection was estimated to be 50 ppb based on the criterion that four of the six sensors show a detectable response. Field performance was evaluated at a commercial dry-cleaning operation by comparing prototype instrument results for breath samples with those of a portable gas chromatograph (NIOSH 3704). Four breath samples were collected from a single subject over the course of the workday and analyzed using the portable gas chromatograph (GC) and SAW instruments. An additional seven spiked breath samples were prepared and analyzed so that a broader range of perchloroethylene concentrations could be examined. Linear regression analysis showed excellent agreement between prototype instrument and portable GC breath sample results with a correlation coefficient of 0.99 and a slope of 1.04. The average error for the prototype instrument over a perchloroethylene breath concentration range of 0.9-7.2 ppm was 2.6% relative to the portable GC. These results demonstrate the field capabilities of SAW microsensor arrays for rapid analysis of organic vapors in breath.

Adaptation and evaluation of a personal electronic nose for selective multivapor analysis

The evaluation of a commercial, belt-mountable "electronic nose" modified for the rapid recognition and quantification of individual solvent vapors and simple vapor mixtures at low ppm concentrations is described. Marketed under the name VaporLab this direct-reading instrument was designed for qualitative determinations of the presence or absence of selected individual vapors and was adapted in this study for quantitative determinations of vapors and vapor-mixture components. Vapor samples are concentrated on a small adsorbent bed and then thermally desorbed for analysis by an array of four polymer-coated surface acoustic wave sensors. Tests were performed with 13 organic solvent vapors individually and in selected binary, ternary, and quaternary mixtures at concentrations ranging from 0.1 to 12 times the respective American Conference of Governmental Industrial Hygienists' (ACGIH) threshold limit value (TLV). Pattern recognition analyses yielded a library of response patterns to which subsequent actual and virtual (i.e., Monte-Carlo simulated) samples were compared to assess performance. Limits of detection >0.025 x TLV are achieved (based on the most sensitive sensors) for 0.25 L of preconcentrated air samples collected over a 2-min period. Individual vapors from different functional group classes can be recognized, quantified, and discriminated from other vapors with little error, and discrimination of the components of binary mixtures is possible where the component vapor response patterns are sufficiently different. Within-class individual vapor and binary-mixture discriminations are more difficult and most ternary and higher-order mixtures could not be analyzed with acceptable accuracy. Changes in ambient humidity have no effect on responses and changes in temperature lead to well-behaved and compensable changes in responses. Tests of fluctuating concentrations demonstrate the capability for accurately tracking short-term variations in exposure. Overall, results suggest that this instrument could serve effectively as a personal exposure monitor in previously characterized occupational environments with proper revisions in design.

Micropatterned polymeric gratings as chemoresponsive volatile organic compound sensors: implications for analyte detection and identification via diffraction-based sensor arrays

Micropatterned polymeric diffraction gratings have been fabricated and evaluated as volatile organic chemical sensors. When operated under nonresonant conditions, sensor elements were found to respond in a rapid (response time 5-15 s) and reproducible fashion to each analyte investigated. Relative response magnitudes were found to be in qualitative agreement with those obtained via surface acoustic wave techniques. Preliminary limits of detection as determined by investigations with micropatterned polyepichlorohydrin, polyisobutylene, and polybutadiene gratings, respectively, were found to be 8, 11, and 7 ppm for toluene, 25, 258; and 72 ppm for methyl ethyl ketone; 41, 102, and 34 ppm for chloroform; and 460, 60, and 59 ppm for hexane. While generally less than 1 order of magnitude higher than those observed for identical polymer/analyte combinations in SAW studies, the observed limits of detection were at or below governmental standards (OSHA-PEL and NIOSH-REL) for each analyte evaluated. These diffraction-based sensors show promise for integration into an array-based sensor system, providing simultaneous identification and quantification of unknown analytes and simple analyte mixtures.

Properties of vapor detector arrays formed through plasticization of carbon black-organic polymer composites

Arrays of vapor detectors have been formed through addition of varying mass fractions of the plasticizer diethylene glycol dibenzoate to carbon black-polymer composites of poly(vinyl acetate) (PVAc) or of poly(N-vinylpyrrolidone). Addition of plasticizer in 5% mass fraction increments produced 20 compositionally different detectors from each polymer composite. Differences in vapor sorption and permeability that effected changes in the dc electrical resistance response of these compositionally different detectors allowed identification and classification of various test analytes using standard chemometric methods. Glass transition temperatures, Tg, were measured using differential scanning calorimetry for plasticized polymers having a mass fraction of 0, 0.10, 0.20, 0.30, 0.40, or 0.50 of plasticizer in the composite. The plasticized PVAc composites with Tg < 25 degrees C showed rapid responses at room temperature to all of the test analyte vapors studied in this work, whereas composites with Tg > 25 degrees C showed response times that were highly dependent on the polymer/analyte combination. These composites showed a discontinuity in the temperature dependence of their resistance, and this discontinuity provided a simple method for determining the Tg of the composite and for determining the temperature or plasticizer mass fraction above which rapid resistance responses could be obtained for all members of the test set of analyte vapors. The plasticization approach provides a method for achieving rapid detector response times as well as for producing a large number of chemically different vapor detectors from a limited number of initial chemical feedstocks.

A portable, high-speed, vacuum-outlet GC vapor analyzer employing air as carrier gas and surface acoustic wave detection

Vacuum-outlet GC with atmospheric-pressure air as the carrier gas is implemented at outlet pressures up to 0.8 atm using a low-dead-volume polymer-coated surface acoustic wave (SAW) detector. Increases in the system outlet pressure from 0.1 to 0.8 atm lead to proportional increases in detector sensitivity and significant increases in column efficiency. The latter effect arises from the fact that optimal carrier gas velocities are lower in air than in more conventional carrier gases such as helium or hydrogen due to the smaller binary diffusion coefficients of vapors in air. A 12-m-long, 0.25-mm-i.d. tandem column ensemble consisting of 4.5-m dimethyl polysiloxane and 7.5-m trifluoropropylmethyl polysiloxane operated at an outlet pressure of 0.5 atm provides up to 4 x 10(4) theoretical plates and a peak capacity of 65 (resolution, 1.5) for a 3-min isothermal analysis. At 30 degrees C, mixtures of vapors ranging in vapor pressure from 8.6 to 76 Torr are separated in this time frame. The SAW detector cell has an internal volume of < 2 microL, which allows the use of higher column outlet pressures with minimal dead time. The sensor response is linear with solute mass over at least 2-3 decades and provides detection limits of 20-50 ng for the vapors tested. The combination of atmospheric-pressure air as carrier gas, modest operating pressures, and SAW sensor detection is well-suited for field instrumentation since it eliminates the need for support gases, permits smaller, low-power pumps to be used, and provides sensitivity to a wide range of vapor analytes.

Detection and classification characteristics of arrays of carbon black/organic polymer composite chemiresistive vapor detectors for the nerve agent simulants dimethylmethylphosphonate and diisopropylmethylphosponate

Arrays of conducting polymer composite vapor detectors have been evaluated for performance in the presence of the nerve agent simulants dimethylmethylphosphonate (DMMP) and diisopropylmethylphosponate (DIMP). Limits of detection for DMMP on unoptimized carbon black/ organic polymer composite vapor detectors in laboratory air were estimated to be 0.047-0.24 mg m(-3). These values are lower than the EC50 value (where EC50 is the airborne concentration sufficient to induce severe effects in 50% of those exposed for 30 min) for the nerve agents sarin (methylphosphonofluoridic acid, 1-methylethyl ester) and soman (methylphosphonofluoridic acid, 1,2,2-trimethylpropyl ester), which has been established as approximately 0.8 mg m(-3). Arrays of these vapor detectors were easily able to resolve signatures due to exposures to DMMP from those due to DIMP or due to a variety of other test analytes (including water, methanol, benzene, toluene, diesel fuel, lighter fluid, vinegar, and tetrahydrofuran) in a laboratory air background. In addition, DMMP at 27 mg m(-3) could be detected and differentiated from the signatures of the other test analytes in the presence of backgrounds of potential interferences, including water, methanol, benzene, toluene, diesel fuel, lighter fluid, vinegar, and tetrahydrofuran, even when these interferents were present in much higher concentrations than that of the DMMP or DIMP being detected.

A fiber-optic lactate sensor based on bacterial cytoplasmic membranes

A new type of fiber-optic biosensor based on bacterial cytoplasmic membranes (CPM) as the biological recognition element and an oxygen sensitive dye layer as the transducer is described for the detection of lactate. CPMs from bacteria with an induced lactate oxidase system are adsorbed onto a cellulose disk. The disk is fixed mechanically over an oxygen sensitive siloxane layer on the distal end of an optical fiber. This system detects lactate with no interference from glucose, fructose or glutamic acid.

Graphite microparticles as coatings for quartz crystal microbalance-based gas sensors

The use of graphite particles (1-2 microm) as coatings on quartz crystal microbalances (QCMs) for detection and monitoring of toluene and other volatile organic compounds (VOCs) is described. Unlike the more commonly used polymeric coatings with low glass transition temperatures (Tg), particulate graphitic coatings are not as susceptible to loss of acoustic energy when coating thickness or operational temperature increases. This situation enables the use of relatively thick coatings, which increases the absolute amount of vapor sorbed in the coating and, consequently, lowers the level of detection and enhances operation over a wide temperature range. The use of small size particles also results in a coating with a more porous structure, which facilitates uptake and release of VOCs in comparison to coatings made from high Tg polymers, which have a lower porosity. These attributes, coupled with the inherent stability of graphitic materials, make particulate graphite coatings especially suitable for applications at high temperatures. The advantages of using particulate graphite as a coating on QCMs are demonstrated by comparison to the performance of a few low-Tg polymers [i.e., poly(isobutylene) and poly(diphenoxyphosphazene)] and high-Tg polymers (i.e., polystyrene).

Conferring selectivity to chemical sensors via polymer side-chain selection: thermodynamics of vapor sorption by a set of polysiloxanes on thickness-shear mode resonators

Entropy of mixing is shown to be the driving interaction for the endothermic physisorption process of organic vapor partitioning into seven systematically side-chain-modified (polar, acidic, basic, polarizable side groups and groups interacting via H-bridges) polysiloxanes on thickness-shear mode resonators. Each sensor was exposed to seven analytes, selected for their diversity of functional groups. This systematic investigation of sorption yields benchmarking data on physisorption selectivity: response data and modeling reveal a direct correlation of partition coefficients with interactions between specific polymer side chains and analyte functional groups. Partition coefficients were determined for every polymer/analyte pairing over the 273-343 K range at 10 K intervals; from partition coefficient temperature dependence, overall absorption enthalpies and entropies were calculated. By subtracting the enthalpy and entropy of condensation for a given pure analyte, its mixing entropy (primarily combinatorial) and mixing enthalpy (associated with intermolecular interactions) with each polymer matrix were determined. These two crucial thermodynamic parameters determine the chemical selectivity patterns of the polymers for the analytes. Simple molecular modeling based on the polymer contact surface share of the modified side group or the introduced functional group reveals a direct correlation between the partition coefficients and the side-group variation.

Amperometric quantification of polar organic solvents based on a tyrosinase biosensor

A novel amperometric biosensor for quantification of the electrochemically inert polar organic solvents based on tyrosinase electrode was preliminarily reported. The biosensor was fabricated by simply syringing an aqueous solution of tyrosinase/PVAVP (PVAVP: copolymer of poly(vinyl alcohol) grafting with 4-vinylpyridine) onto glassy carbon electrode surface followed by drying the modified electrode at +4 degrees C in a refrigerator. The current generated from electrochemical reduction of quinone is a probe signal. The biosensor can be used for quantification of polar organic solvents, and its mechanism was characterized with in situ steady-state amperometry-quartz crystal microbalance experiments. The detection limit, sensitivity, and dynamic range for certain organic solvents are dependent on the kind and concentration of the substrate probe and the hydrophobicity of the immobilization matrix. The response time for all the tested organic solvents is less than 2 min.

Differentiation of chemical components in a binary solvent vapor mixture using carbon/polymer composite-based chemiresistors

We demonstrate a "universal solvent sensor" constructed from a small array of carbon/polymer composite chemiresistors that respond to solvents spanning a wide range of Hildebrand solubility parameters. Conductive carbon particles provide electrical continuity in these composite films. When the polymer matrix absorbs solvent vapors, the composite film swells, the average separation between carbon particles increases, and an increase in film resistance results, as some of the conduction pathways are broken. The adverse effects of contact resistance at high solvent concentrations are reported. Solvent vapors including isooctane, ethanol, diisopropylmethylphosphonate (DIMP), and water are correctly identified ("classified") using three chemiresistors, their composite coatings chosen to span the full range of solubility parameters. With the same three sensors, binary mixtures of solvent vapor and water vapor are correctly classified; following classification, two sensors suffice to determine the concentrations of both vapor components. Poly(ethylenevinyl acetate) and poly(vinyl alcohol) (PVA) are two such polymers that are used to classify binary mixtures of DIMP with water vapor; the PVA/carbon particle composite films are sensitive to less than 0.25% relative humidity. The Sandia-developed visual-empirical region of influence (VERI) technique is used as a method of pattern recognition to classify the solvents and mixtures and to distinguish them from water vapor. In many cases, the response of a given composite sensing film to a binary mixture deviates significantly from the sum of the responses to the isolated vapor components at the same concentrations. While these nonlinearities pose significant difficulty for (primarily) linear methods such as principal component analysis, VERI handles both linear and nonlinear data with equal ease. In the present study, the maximum speciation accuracy is achieved by an array containing three or four sensor elements, with the addition of more sensors resulting in a measurable accuracy decrease.

Vapor recognition with small arrays of polymer-coated microsensors. A comprehensive analysis

A comprehensive analysis of vapor recognition as a function of the number of sensors in a vapor-sensor array is presented. Responses to 16 organic vapors collected from six polymer-coated surface acoustic wave (SAW) sensors were used in Monte Carlo simulations coupled with pattern recognition analyses to derive statistical estimates of vapor recognition rates as a function of the number of sensors in the array (< or = 6), the polymer sensor coatings employed, and the number and concentration of vapors being analyzed. Results indicate that as few as two sensors can recognize individual vapors from a set of 16 possibilities with < 6% average recognition error, as long as the vapor concentrations are > 5 x LOD for the array. At lower concentrations, a minimum of three sensors is required, but arrays of 3-6 sensors provide comparable results. Analyses also revealed that individual-vapor recognition hinges more on the similarity of the vapor response patterns than on the total number of possible vapors considered. Vapor mixtures were also analyzed for specific 2-, 3-, 4-, 5-, and 6-vapor subsets where all possible combinations of vapors within each subset were considered simultaneously. Excellent recognition rates were obtainable for mixtures of up to four vapors using the same number of sensors as vapors in the subset. Lower recognition rates were generally observed for mixtures that included structurally homologous vapors. Acceptable recognition rates could not be obtained for the 5- and 6-vapor subsets examined, due, apparently, to the large number of vapor combinations considered (i.e., 31 and 63, respectively). Importantly, increasing the number of sensors in the array did not improve performance significantly for any of the mixture analyses, suggesting that for SAW sensors and other sensors whose responses rely on equilibrium vapor-polymer partitioning, large arrays are not necessary for accurate vapor recognition and quantification.

Establishing a limit of recognition for a vapor sensor array

Organic vapor analysis with microsensor arrays relies principally on two output parameters: the response pattern, which provides qualitative information, and the response sensitivity, which determines the limit of detection (LOD). The latter is used to define the operating limit in the low-concentration range, under the implicit assumption that, if a vapor can be detected, it can be identified and differentiated from other vapors on the basis of its response pattern. In this study, the performance of an array of four polymer-coated surface acoustic wave vapor sensors was explored using calibrated response data from 16 solvent vapors in Monte Carlo simulations coupled with pattern recognition analysis. The statistical modeling revealed that the ability to recognize a vapor from its response pattern decreases with decreasing vapor concentration, as expected, but also that the concentration at which errors in vapor recognition become excessive is well above the calculated LOD in most cases, despite the LOD being based on the least sensitive sensor in the array. These results suggest the adoption of a limit of recognition (LOR), defined as the concentration below which a vapor can no longer be reliably recognized from its response pattern, as an additional criterion for evaluating the performance of multisensor arrays. A generalized method for estimating the LOR is presented, as well as a means for improving the LOR via residual error analysis.

Randomly ordered addressable high-density optical sensor arrays

Array-based sensors provide an architecture for multianalyte sensing. In this paper, we report a new approach for array fabrication. Sensors are made by immobilizing different reactive chemistries on the surfaces of microspheres. Sensor arrays are prepared by randomly distributing a mixture of microsphere sensors on an optical substrate containing thousands of micrometer-scale wells. The sensors occupy a different location from array to array; thus the identity of each sensor is ascertained and registered on the detector using encoding schemes, rather than by a predetermined location in the array. The approach thereby shifts the demand from fabrication to signal processing. The availability of commercial image analysis software makes such a shift both cost-effective and time efficient.