Douglas C. Meier

Coupling Nanowire Chemiresistors with MEMS Microhotplate Gas Sensing Platforms

Recent advances in nanotechnology have yielded materials and structures that offer great potential for improving the sensitivity, selectivity, stability, and speed of next-generation chemical gas sensors. To fabricate practical devices, the “bottom-up” approach of producing nanoscale sensing elements must be integrated with the “top-down” methodology currently dominating microtechnology. In this letter, the authors illustrate this approach by coupling a single-crystal SnO2 nanowire sensing element with a microhotplate gas sensor platform. The sensing results obtained using this prototype sensor demonstrate encouraging performance aspects including reduced operating temperature, reduced power consumption, good stability, and enhanced sensitivity.

Chemical warfare agent detection using MEMS-compatible microsensor arrays

Microsensors have been fabricated consisting of TiO/sub 2/ and SnO/sub 2/ sensing films prepared by chemical vapor deposition (CVD) on microelectromechanical systems array platforms. Response measurements from these devices to the chemical warfare (CW) agents GA (tabun), GB (sarin), and HD (sulfur mustard) at concentrations between 5 nmol/mol (ppb) and 200 ppb in dry air, as well as to CW agent simulants CEES (chloroethyl ethyl sulfide) and DFP (diisopropyl fluorophosphate) between 250 and 3000 ppb, are reported. The microsensors exhibit excellent signal-to-noise and reproducibility. The temperature of each sensor element is independently controlled by embedded microheaters that drive both the CVD process (375/spl deg/C) and sensor operation at elevated temperatures (325/spl deg/C-475/spl deg/C). The concentration-dependent analyte response magnitude is sensitive to conditions under which the sensing films are grown. Sensor stability studies confirm little signal degradation during 14 h of operation. Use of pulsed (200 ms) temperature-programmed sensing over a broad temperature range (20/spl deg/C-480/spl deg/C) enhances analyte selectivity, since the resulting signal trace patterns contain primarily kinetic information that is unique for each agent tested.

Detecting Chemical Hazards with Temperature-Programmed Microsensors: Overcoming Complex Analytical Problems with Multidimensional Databases*

Complex analytical problems, such as detecting trace quantities of hazardous chemicals in challenging environments, require solutions that most effectively extract relevant information about a samples composition. This review presents a chemiresistive microarray-based approach to identifying targets that combines temperature-programmed elements capable of rapidly generating analytically rich data sets with statistical pattern recognition algorithms for extracting multivariate chemical fingerprints. We describe the chemical-microsensor platform and discuss its ability to generate orthogonal data through materials selection and temperature programming. Visual inspection of data sets reveals device selectivity, but statistical analyses are required to perform more complex identification tasks. Finally, we discuss recent advances in both devices and algorithms necessary to deal with practical issues involved in long-term deployment. These issues include identification and correction of signal drift, challenges surrounding real-time unsupervised operation, repeatable device manufacturability, and hierarchical classification schemes designed to deduce the chemical composition of untrained analyte species.

Detecting and recognizing chemical targets in untrained backgrounds with temperature programmed sensors

Applications for artificial olfaction typically require analytical performance in the context of diverse backgrounds. Therefore, to deal with practical challenges posed by chemical species recognition in the presence of pre-trained and untrained backgrounds, a desirable feature is the ability to rapidly detect fresh analyte introductions (foreground odor) and segment their contributions from the foreground-background response cocktail. Here, we present a simple approach for this purpose based on the moving-window pair-wise correlation between sensor responses measured at multiple temperatures. We show that pairwise-correlation across isotherm segments can be used as a robust measure to rapidly detect chemical events (onset and offset), as well as to track and compensate for sensor baseline changes due to background variations. We demonstrate this approach for the problem of identifying three toxic industrial chemicals-ammonia, hydrogen cyanide, and chlorine-in several untrained backgrounds. Additionally, we show that the proposed scheme could be used to reduce baseline differences in response signatures between sensors of equivalent manufacture and thereby allow training and testing using different but comparable sensors.

Characterization of SiGe films for use as a National Institute of Standards and Technology Microanalysis Reference Material (RM 8905).

Bulk silicon-germanium (SiGe) alloys and two SiGe thick films (4 and 5 microm) on Si wafers were tested with the electron probe microanalyzer (EPMA) using wavelength dispersive spectrometers (WDS) for heterogeneity and composition for use as reference materials needed by the microelectronics industry. One alloy with a nominal composition of Si0.86Ge0.14 and the two thick films with nominal compositions of Si0.90Ge0.10 and Si0.75Ge0.25 on Si, evaluated for micro- and macroheterogeneity, will make good microanalysis reference materials with an overall expanded heterogeneity uncertainty of 1.1% relative or less for Ge. The bulk Ge composition in the Si0.86Ge0.14 alloy was determined to be 30.228% mass fraction Ge with an expanded uncertainty of the mean of 0.195% mass fraction. The thick films were quantified with WDS-EPMA using both the Si0.86Ge0.14 alloy and element wafers as reference materials. The Ge concentration was determined to be 22.80% mass fraction with an expanded uncertainty of the mean of 0.12% mass fraction for the Si0.90Ge0.10 wafer and 43.66% mass fraction for the Si0.75Ge0.25 wafer with an expanded uncertainty of the mean of 0.25% mass fraction. The two thick SiGe films will be issued as National Institute of Standards and Technology Reference Materials (RM 8905).

An examination of kernite (Na2B4O6(OH)2·3H2O) using X-ray and electron spectroscopies: quantitative microanalysis of a hydrated low-Z mineral.

Mineral borates, the primary industrial source of boron, are found in a large variety of compositions. One such source, kernite (Na2B4O6(OH)2·3H2O), offers an array of challenges for traditional electron-probe microanalysis (EPMA)-it is hygroscopic, an electrical insulator, composed entirely of light elements, and sensitive to both low pressures and the electron beam. However, the approximate stoichiometric composition of kernite can be analyzed with careful preparation, proper selection of reference materials, and attention to the details of quantification procedures, including correction for the time dependency of the sodium X-ray signal. Moreover, a reasonable estimation of the minerals water content can also be made by comparing the measured oxygen to the calculated stoichiometric oxygen content. X-ray diffraction, variable-pressure electron imaging, and visual inspection elucidate the structural consequences of high vacuum treatment of kernite, while Auger electron spectroscopy and X-ray photoelectron spectroscopy confirm electron beam-driven migration of sodium and oxygen out of the near-surface region (sampling depth ≈ 2 nm). These surface effects are insufficiently large to significantly affect the EPMA results (sampling depth ≈ 400 nm at 5 keV).

Fourier Transform Infrared Absorption Spectroscopy for Quantitative Analysis of Gas Mixtures at Low Temperatures for Homeland Security Applications

Performance standard specifications for point chemical vapor detectors are established in ASTM E 2885-13 and ASTM E 2933-13. The performance evaluation of the detectors requires the accurate delivery of known concentrations of the chemical target to the system under test. Referee methods enable the analyte test concentration and associated uncertainties in the analyte test concentration to be validated by independent analysis, which is especially important for reactive analytes. This work extends the capability of a previously demonstrated method for using Fourier transform infrared (FT-IR) absorption spectroscopy for quantitatively evaluating the composition of vapor streams containing hazardous materials at Acute Exposure Guideline Levels (AEGL) to include test conditions colder than laboratory ambient temperatures. The described method covers the use of primary reference spectra to establish analyte concentrations, the generation of secondary reference spectra suitable for measuring analyte concentrations under specified testing environments, and the use of additional reference spectra and spectral profile strategies to mitigate the uncertainties due to impurities and water condensation within the low-temperature (7 °C, -5 °C) test cell. Important benefits of this approach include verification of the test analyte concentration with characterized uncertainties by in situ measurements co-located with the detector under test, near-real-time feedback, and broad applicability to toxic industrial chemicals.

Fourier Transform Infrared Absorption Spectroscopy for Quantitative Analysis of Gas Mixtures for Homeland Security Applications

Chemical detectors are crucial tools for first responders during emergency-response scenarios and for continuous monitoring of public spaces for general safety. For those who depend upon chemical detectors for safety and security, ensuring that detectors alarm at specified levels is critical. During detector performance evaluation, the accurate delivery of known concentrations of the chemical target to the detector is a key aspect of the test. Referee methods enable the analyte test concentration and associated uncertainties in the analyte test concentration to be validated by independent analysis, which is especially important for reactive analytes. This work demonstrates a method to use Fourier transform infrared (FT-IR) absorption spectroscopy for quantitatively evaluating the composition of vapor streams containing hazardous materials at acute exposure guideline levels (AEGL) under test conditions defined in recently published standard specifications for chemical vapor detectors. The described method covers the use of primary reference spectra to establish analyte concentrations, the generation of secondary reference spectra suitable for measuring analyte concentrations under specified testing environments, and the use of referee feedback to compensate for depletion of the test analyte. Important benefits of this approach included verification of the test analyte concentration with characterized uncertainties by in situ measurements co-located with the detector under test, near-real-time feedback, and broad applicability to toxic industrial chemicals.

A MEMS-based approach that uses temperature-dependent sensing responses to recognize chemical targets in untrained backgrounds

A major practical challenge for solid state microsensors is the detection of trace chemical species over time and in complex gas-phase backgrounds. We describe a MEMS-based, chemiresistive technology that has succeeded in such problems by combining oxide nanomaterials on microscale platforms, acquisition of dense temperature-dependent response data streams, and novel signal processing methods. Unlike the operation and analysis employed with many electronic noses, our higher dimensional approach captures surface electronic implications of changing adsorptive/reactive phenomena caused by rapid thermal cycling. Here, we demonstrate new capabilities for recognizing toxic targets over extended time periods, even in untrained backgrounds that contain aggressive contaminants at higher concentrations. The approach involves a moving-window, correlation-based methodology to identify chemical events and decouple the foreground conditions from the background.

Enabling MEMS Chemical Microsensor Arrays for Trace Analyte Detection

We describe the development of a conductometric gas microsensor technology that combines, in an optimized manner, nanostructured sensing films, MEMS microhotplate array platforms, and artificial neural networks signal processing. Individually addressable microelements, including varied semiconducting oxides, are temperature modulated to produce analytically rich data streams that allow recognition of low concentration target analytes in background mixtures. This brief report emphasizes: 1) recently developed selection and processing methods for incorporation of high performance sensing materials on the MEMS platforms, 2) special operational modes and data acquisition approaches for ensuring good signal quality while maximizing information content, and 3) signal analysis techniques that include preprocessing routines and advanced recognition algorithms.