Biomedical subjects

W A Groves

Publications and source records attributed to W A Groves.

6 recordsLinked to original sources

PubMed2006

Surface acoustic wave (SAW) microsensor array for measuring VOCs in drinking water.

Exposure to volatile organic chemicals (VOCs) in drinking water has been linked to a number of adverse health effects including cancer, liver, and kidney damage. However, the large number of potential contaminants and the cost and complexity of existing analytical methods limits the extent to which water quality is routinely characterized. This project focused on the laboratory development and evaluation of an instrument for field analysis of VOCs in drinking water. The instrument is based on an array of six polymer-coated surface-acoustic-wave microsensors. A test-set consisting of dichloromethane, chloroform, 1,1,1-trichloroethane, perchloroethylene, and m-xylene was used in a series of experiments designed to optimize the purge-trap preconcentration system, calibrate the instrument over the concentration range of 0.2-2 times the USEPA maximum contaminant levels (MCLs), and compare results to those of a reference laboratory. The primary goal was to develop a cost-effective alternative for on-site evaluation of VOCs in water. Calibration and evaluation test results for spiked water samples demonstrate adequate sensitivity for 19 of the 21 regulated VOCs considered using a ten minute sampling and analysis cycle. Monte Carlo simulations characterized the performance of trained artificial neural networks (ANNs) which had correct classification rates of 99%, 90%, and 80% for the five individual test-set vapors and their binary and ternary mixtures, respectively. These results demonstrate the excellent potential of this technology for addressing the need for improved VOC field-screening methods for water supplies.

Acoustics↗

PubMed2001

Analysis of solvent vapors in breath and ambient air with a surface acoustic wave sensor array.

This article describes the development and evaluation of a small prototype instrument employing an array of four polymer-coated surface acoustic wave (SAW) sensors for rapid analysis of organic solvent vapors in exhaled breath and ambient air. A thermally desorbed adsorbent preconcentrator within the instrument is used to increase sensitivity and compensate for background water vapor. Calibrations were performed for breath and dry nitrogen samples in Tedlar bags spiked with 16 individual solvents and selected binary mixtures. Responses were linear over the 50- to 400-fold concentration ranges examined and mixture responses were additive. The resulting library of vapor calibration response patterns was used with extended disjoint principal components regression and a probabilistic artificial neural network to develop vapor-recognition algorithms. In a subsequent analysis of an independent data set all individual vapors and most binary mixture components were correctly identified and were quantified to within 25% of their actual concentrations. Limits of detection for a 0.25 l. sample collected over a 2.5-min period were <0.3xTLV for 14 of the 16 vapors based on the criterion that all four sensors show a detectable response. Results demonstrate the feasibility of this technology for workplace analysis of breath and ambient air.

Acoustics↗

PubMed1999

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.

Chemistry Techniques, Analytical↗

PubMed1998

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.

Calibration↗

PubMed1996

Prototype instrument employing a microsensor array for the analysis of organic vapors in exhaled breath.

A prototype portable instrument capable of selectively measuring organic vapors in breath at low- and sub-ppm concentrations was tested. The instrument employs an array of four polymer-coated surface-acoustic-wave (SAW) resonators and microprocessor-controlled pumps, valves, and heating elements for preconcentration and thermal desorption of breath samples. Response data are passed to an external personal computer for processing. Sensor responses are based on the reversible changes in the mass and viscoelasticity of the polymeric coatings accompanying vapor sorption. Calibrations were performed for perchloroethylene, trichloroethylene, and methoxyflurane at 100% relative humidity using 15 mg of TenaxTA as the preconcentrator adsorbent. Analyses were then conducted of 250-mL breath samples prepared in Tedlar bags spiked with one of the three solvents within the range of 2 to 18 ppm. Differences between concentrations measured using the prototype instrument and those measured by gas chromatography ranged from -6 to 17% for perchloroethylene. Similar results were obtained for trichloroethylene and methoxyflurane with larger differences occurring at lower concentrations. Estimated limits of detection of 0.7, 0.6, and 4 ppm were achieved for perchloroethylene, trichloroethylene, and methoxyflurane, respectively. These preliminary results demonstrate the feasibility of using SAW sensor technology for field breath analysis.

Breath Tests↗

PubMed1996

Investigation of organic vapor losses to condensed water vapor in Tedlar bags used for exhaled-breath sampling.

This study evaluated the potential loss of organic vapors to condensed water in bags used for breath sampling. "Wet" test atmospheres were prepared by transferring nitrogen into 1-L Tedlar bags and spiking with water and each of several organic solvents (methanol, acetone, 2-butanone,m-xylene, 1,1,1 trichloroethane, and perchloroethylene) to yield atmospheres representative of a 500-mL breath sample collected at 37 degrees C and cooled to 25 degrees C. Vapor concentrations were compared with those in bags prepared without water. Differences between mean concentrations in wet and dry bags were significant only for methanol, which yielded a mean wet-bag concentration approximately 10% lower than for dry bags. In a second series of experiments the same initial concentration of solvent vapor was generated in 1 dry bag and 5 bags containing 1 to 20 times the amount of water expected to condense in a 500-mL breath sample. Significant differences between wet and dry bag concentrations were seen for methanol, acetone, and 2-butanone; however, the quantity of water required to produce this difference in the acetone and 2-butanone bags exceeded three times that expected to condense in a breath sample. Results were in good agreement with predictions based on Henry's law. In both experiments permeation of water vapor out of the bags led to a decrease in the quantity of condensed water, thereby reducing the extent of organic vapor partitioning. These results indicate that solvent vapor loss to condensed water is not likely to be significant under typical conditions.

Body Water↗