Rapid analyte recognition in a device based on optical sensors and the olfactory system

We report here the development of a new vapor sensing device that is designed as an array of optically based chemosensors providing input to a pattern recognition system incorporating artificial neural networks. Distributed sensors providing inputs to an integrative circuit is a principle derived from studies of the vertebrate olfactory system. In the present device, primary chemosensing input is provided by an array of fiber-optic sensors. The individual fiber sensors, which are broadly yet differentially responsive, were constructed by immobilizing molecules of the fluorescent indicator dye Nile Red in polymer matrices of varying polarity, hydrophobicity, pore size, elasticity, and swelling tendency, creating unique sensing regions that interact differently with vapor molecules. The fluorescent signals obtained from each fiber sensor in response to 2-s applications of different analyte vapors have unique temporal characteristics. Using signals from the fiber array as inputs, artificial neural networks were trained to identify both single analytes and binary mixtures, as well as relative concentrations. Networks trained with integrated response data from the array or with temporal data from a single fiber made numerous errors in analyte identification across concentrations. However, when trained with temporal information from the fiber array, networks using "name" or "characteristic" output codes performed well in identifying test analytes.     

Ionic liquid high-temperature gas sensor array

A novel sensor array using seven room-temperature ionic liquids (ILs) as sensing materials and a quartz crystal microbalance (QCM) as a transducer was developed for the detection of organic vapors at ambient and elevated temperatures. Ethanol, dichloromethane, benzene, and heptane were selected as representative gas analytes for various kinds of environmental pollutants and common industrial solvents. The QCM/IL sensors responded proportionately and reversibly to the organic vapor concentrations (i.e., ethanol, heptane, and benzene) in the gas phase from 0 to 100% saturation at room and elevated temperatures (e.g., 120 degrees C) but deviated from this linear relationship at high concentrations for dichloromethane, a highly volatile compound. Linear discriminant analysis was used to analyze the sensing patterns. Excellent classifications were obtained for both known and unknown concentrations of vapor samples. The correct classifications were 100% for known concentration samples and 96% for samples with unknown concentrations. Thermodynamics and ATR-FT-IR studies were conducted to understand specific molecular interactions, the strength of the interaction between ILs and organic vapors, and the degree of ordering that takes place upon dissolution of the vapors in ILs. The different response intensity of the QCM/IL sensors to the organic vapors depends on the different solubilities of organic vapors in ILs and varying molecular/ion interactions between each organic vapor and IL. The diverse set of IL studied showed selective responses due to structural differences. Therefore, a sensor array of ILs would be able to effectively differentiate different vapors in pattern recognitions, facilitating discrimination by their distinctive patterns in response to organic vapors in both room and high temperatures.     

Simultaneous monitoring of protein adsorption kinetics using a quartz crystal microbalance and field-effect transistor integrated device

We developed an integrated device comprising a quartz crystal microbalance (QCM) and a field-effect transistor (FET) with a single common gold electrode in a flow chamber. An alternating current inducing oscillations in the piezoelectric quartz of the QCM sensor is electrically independent of the circuit for the FET output so that the two sensors in different detection mechanisms simultaneously record binding kinetics from a single protein solution on the same electrode. A conjunction of adsorbed mass from QCM with electric nature of bound protein from FET provided deeper understanding on a complex process of nonspecific protein adsorption and subsequent conformational changes at a solid/liquid interface. Lower apparent k(on) values obtained by FET than those obtained by QCM on hydrophobic surfaces are interpreted as preferred binding of protein molecules facing uncharged domains to the electrode surface, whereas higher k(off) values by FET than those by QCM imply active macromolecular rearrangements on the surfaces mainly driven by hydrophobic association in an aqueous medium. The advanced features of the combined sensor including in situ, label-free, and real-time monitoring provide information on structural dynamics, beyond measurements of affinities and kinetics in biological binding reactions.     

Dual-chemiresistor GC detector employing monolayer-protected metal nanocluster interfaces

The synthesis and testing of two gold-thiolate monolayer-protected (nano)clusters as interfacial layers on a dual-chemiresistor vapor sensor array are described. Responses (changes in dc resistance) to each of 11 organic solvent vapors are rapid, reversible, and linear with concentration at low vapor concentrations, becoming sublinear at higher concentrations. Limits of detection (LODs) range from 0.1 to 24 parts per million and vary inversely with solvent vapor pressure. When configured as a GC detector and used to analyze 0.5-L preconcentrated samples of the 11-vapor mixture, the array provides LODs of < or = 700 parts per trillion for most vapors, comparing favorably with those from an integrated array of polymer-coated surface acoustic wave sensors configured and tested similarly. This first report on the use of such an array as a GC detector shows that the combination of response patterns and GC retention times improves capabilities for vapor recognition compared to the sensor array alone or to single-detector GC systems. Spray-coated nanocluster thin films can be deposited reproducibly and exhibit response stability in air that ranges from fair to excellent for up to several months. Scaling the active device area down by a factor of 16 has no significant effect on sensitivity. Implications of these results for portable vapor sensing systems are discussed.     

Fault-tolerant sensor systems using evolvable hardware

This paper describes a system that is robust with respect to a sensor failure. The system utilizes multiple sensor inputs (three in this case) connected to a programmable device that averages the outputs from the sensors. The programmable device is programmed using evolvable hardware techniques. If one or more of the input sensors fail, then the controller detects the failure and initiates a reprogramming of the circuit. The system then continues to operate with a reduced number of sensors. The failure detection is accomplished by comparing the actual system output with a Kalman-filter estimate of the output. If the actual output and the filter estimate differ by an amount greater than the system uncertainty, then a failure is noted. The system is robust to several different failure modes: sensor fails as open circuit, sensor fails as short circuit, partial failures, multiple sensors fail, field programmable analog array input amplifier failure. This paper describes the experimental setup as well as results using actual temperature sensors. For all failure types, the system was able to recover to within 2% of the target value.     

A measurement system for odor classification based on the dynamic response of QCM sensors

In this paper, an innovative measurement system for odor classification, based on quartz crystal microbalances (QCMs), is presented. The application proposed in this paper is the detection of typical wine aroma compounds in mixtures containing ethanol. In QCM sensors, the sensitive layer is, e.g., a polymeric layer deposited on a quartz surface. Chemical mixtures are sorbed in the sensitive layer, inducing a change in the polymer mass and, therefore, in the quartz resonance frequency. In this paper, the frequency shift is measured by a dedicated, fully digital front-end hardware implementing a technique that allows reducing the measurement time while maintaining a high-frequency resolution . The developed system allows, therefore, measuring variations of the QCM resonance frequency shifts during chemical transients obtained with abrupt changes in odor concentration. Hence, the reaction kinetics can be exploited to enhance the sensor selectivity. In this paper, some measurements obtained with an array of four sensors with different polymeric sensitive layers are presented. An exponential fitting of the transient responses is used for feature extraction. Finally, to reduce data dimensionality, principal component analysis is used.     

A 0-phase circuit for QCM-based measurements in highly viscous liquid environments

Currently, the series resonant frequency f/sub s/ and the motional resistance Rm of liquid loaded quartz crystal microbalance (QCM) sensors are extracted either directly, through network analyzer (NWA) impedance measurements, or from QCM-stabilized oscillator circuits. Both methods have serious drawbacks that may affect measurement accuracy, especially if the sensor is operated under highly viscous load conditions and Rm exceeds 1 k/spl Omega/. This paper presents a simple passive low-loss impedance transformation LC network which greatly reduces additional electrical loading of the QCM by the measurement system or sensor electronics and maintains a symmetric resonance and a steep 0-phase crossing at f/sub s/, even if Rm increases by several orders of magnitude as a result of liquid loading. A simple S21 transmission measurement allows direct f/sub s/ reading at the 0-phase frequency, while Rm is obtained from the circuit loss at f/sub s/. Circuit operation was verified at 9 MHz by QCM measurements in a liquid with known density and viscosity. The agreement between predicted and experimental data, which was obtained by a temperature-controlled measurement, was within 1%, even in very high viscosity ranges in which Rm exceeds 10 k/spl Omega/.     

Olfactory receptor-based polypeptide sensor for acetic acid VOC detection

Rapid detection of food-borne pathogens in packaged food products can prevent the spread of infectious diseases. This study investigates the application of novel sensing material that is sensitive to specific indicator volatile organic compound (VOC) related to Salmonella contamination in packaged meat. Specifically, the objective was to develop an olfactory receptor-based synthetic polypeptide sensor for the detecting acetic acid in low concentrations and at room temperature. Synthetic polypeptide was deposited on a quartz crystal microbalance (QCM) electrode and was evaluated for detecting acetic acid at 10–100 ppm. Developed sensor exhibited repeatable response to a particular concentration of acetic acid and displayed reproducibility among multiple sensors during acetic acid detection. Mean estimated lower detection limits of these sensors were about 1–3 ppm and linear calibration models showed linear relationships. Thus, the QCM sensors exhibited a great potential for detecting low concentrations of acetic acid at room temperature and can be used in the sensor array for packaged meat spoilage and contamination detection.     

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.     

Creating gold nanoprisms directly on quartz crystal microbalance electrodes for mercury vapor sensing

A novel electrochemical route is used to form highly {111}-oriented and size-controlled Au nanoprisms directly onto the electrodes of quartz crystal microbalances (QCMs) which are subsequently used as mercury vapor sensors. The Au nanoprism loaded QCM sensors exhibited excellent response-concentration linearity with a response enhancement of up to ～ 800% over a non-modified sensor at an operating temperature of 28?°C. The increased surface area and atomic-scale features (step/defect sites) introduced during the growth of nanoprisms are thought to play a significant role in enhancing the sensing properties of the Au nanoprisms toward Hg vapor. The sensors are shown to have excellent Hg sensing capabilities in the concentration range of 0.123-1.27 ppm(v) (1.02-10.55 mg m(-3)), with a detection limit of 2.4 ppb(v) (0.02 mg m(-3)) toward Hg vapor when operating at 28?°C, and 17 ppb(v) (0.15 mg m(-3)) at 89?°C, making them potentially useful for air monitoring applications or for monitoring the efficiency of Hg emission control systems in industries such as mining and waste incineration. The developed sensors exhibited excellent reversible behavior (sensor recovery) within 1 h periods, and crucially were also observed to have high selectivity toward Hg vapor in the presence of ethanol, ammonia and humidity, and excellent long-term stability over a 33 day operating period.     

Digital correction techniques for accuracy improvement in measurements of SnO/sub 2/ sensor impedance

In this paper, the performance improvement of a gas-sensing system by digital correction techniques is discussed. The considered system operates as a vectorial impedance meter and performs impedance measurements of eight sensors arranged in an array in the frequency range 10 Hz-15 MHz. The measurements of the chemical sensors' impedance is an innovative technique that allows highlighting different adsorption mechanisms taking place when the sensors are exposed to gases. Of course, impedance analyzers are commercially available, but they usually make measurements on only one device at time and they are very expensive. The proposed PC-based impedance analyzer is a versatile one and shows good performances for gas-sensing applications. A digital correction technique is used in this work to improve the impedance measurement accuracy of each channel of the gas-sensing system (eight sensors /spl rarr/ eight channels), in order to compensate for the conditioning electronics response. The latter is evaluated in a characterization procedure. A linear black box two-port model is used to take into account crosstalk, amplitude, and phase distortions. Two different techniques to evaluate the response of the measurement system are discussed in this paper, and experimental results are presented on both the measure of reference impedances and on the measure of chemical sensors.     

A comparison among different setups for measuring on-waferintegrated inductors in RF applications

This paper presents a comparison to study the most suitable setup for measuring an integrated inductor using a vector network analyzer. It assumes that the inductor will be modeled with the Π model, the lumped equivalent circuit most often used by designers. We have demonstrated that measuring an inductor with a one-port analyzer is not suitable for an accurate characterization of this type of device. Instead, we propose that the best method is measuring the inductor placed in series between the two ports of the analyzer. The method presented can be extrapolated to the study of how to measure other two-port devices in which the lumped equivalent circuit used to characterize its performance is previously known     

A CMOS Integrable Oscillator-Based Front End for High-Dynamic-Range Resistive Sensors

A new oscillating circuit is proposed to estimate the resistance and parallel parasitic capacitance of resistive chemical sensors. The circuit is able to reveal the resistance in a wide range (from tens of kiloohms to more than 100 $hbox{G}Omega$) due to the adopted resistance-to-time technique. In addition, the parallel capacitance (up to 50 pF) can be estimated. The circuit, which does not need any initial calibration, is very simple and compact and is suitable to be integrated with a standard CMOS technology to obtain a low-cost and low-power device for a sensor array interface. Different kinds of postlayout simulations concerning the CMOS integrated implementation have been conducted. Experimental results obtained using a discrete prototype board, both on passive components and on real sensors (metal–oxide sensors), have shown good linearity and reduced percentage error with respect to the theoretical expectations.      

Realtime stable isotope monitoring of natural waters by parallel-flow laser spectroscopy

A parallel-flow H(2)O(liquid)-H(2)O(vapor) equilibration and laser spectroscopy method provides a new way to monitor the hydrogen and oxygen stable isotopic composition of water from rivers or lakes or in hydrologic tracer tests in real time. Two custom-built equilibrator devices and one commercial membrane device were tested to determine if they could be used to convert natural water samples (lakes, rivers, groundwater) to a H(2)O gas phase for continuous online δ(18)O and δD isotopic analysis by laser spectroscopy. Both the commercial minimodule device and the marble-filled equilibrator produced water vapor in isotopic equilibrium with the flowing liquid water, suggesting that unattended field measurement using these devices is possible. Oxygen isotope disequilibrium was indicated using the minimodule device at low temperatures.     

Ionic liquids: a new class of sensing materials for detection of organic vapors based on the use of a quartz crystal microbalance

A QCM device employing ionic liquids as the sensing materials for organic vapors has been developed and evaluated. The sensing mechanism is based on the fact that the viscosity of the ionic liquid membrane decreases rapidly due to solubilization of analytes in the ionic liquids. This change in viscosity, which varies with the chemical species of the vapors and the types of ionic liquids, results in a frequency shift of the corresponding quartz crystal. The QCM sensor demonstrated a rapid response (average response time of less than 2 s) to organic vapors with an excellent reversibility because of the fast diffusion of analytes in ionic liquids. Furthermore, the ionic liquids, with zero vapor pressure and stable chemical properties, ensure a long-term shelf life for the sensor.     

High-throughput screens for postgenomics: studies of protein crystallization using microsystems technology

This paper describes the fabrication of a micromachined miniaturized array of chambers in a 2-mm-thick single crystal (100) silicon substrate for the combinatorial screening of the conditions required for protein crystallization screening (including both temperature and the concentration of crystallization agent). The device was fabricated using standard photolithography techniques, reactive ion etching (RIE) and anisotropic silicon wet etching to produce an array of 10 x 10 microchambers, with each element having a volume of 5 microL. A custom-built temperature controller was used to drive two peltier elements in order to maintain a temperature gradient (between 12 and 40 degrees C) across the device. The performance of the microsystem was illustrated by studying the crystallization of a model protein, hen egg white lysozyme. The crystals obtained were studied using X-ray diffraction at room temperature and exhibited 1.78 A resolution. The problems of delivering a robust crystallization protocol, including issues of device fabrication, delivery of a reproducible temperature gradient, and overcoming evaporation are described.     

High-speed fluorescence detection of explosives-like vapors

In this paper, we report on the preparation of novel cross-reactive optical microsensors for high-speed detection of low-level explosives and explosives-like vapors. Porous silica microspheres with an incorporated environmentally sensitive fluorescent dye are employed in high-density sensor arrays to monitor fluorescence changes during nitroaromatic compound (NAC) vapor exposure. The porous silica-based sensor materials have good adsorption characteristics, high surface areas, and surface functionality to help maximize analyte-dye interactions. These interactions occur immediately upon vapor exposure, i.e., in less than 200 ms and are monitored with a high-speed charge-coupled device camera to produce characteristic and reproducible vapor response profiles for individual sensors within an array. Employing thousands of identical microsensors permits sensor responses to be combined, which significantly reduces sensor noise and enhances detection limits. Normalized response profiles for 1,3-dinitrobenzene (1,3-DNB) are independent of analyte concentration, analyte exposure time, or sensor age for an array of one sensor type. Explosives-like NACs such as 2,4-dinitrotoluene and DNB are detected at low part-per-billion levels in seconds. Sensor-analyte profiles of some sensor types are more sensitive to low-level NAC vapor even when in a higher organic vapor background. We show that single-element arrays permit the detection of low-level nitroaromatic compound vapors because of sensor-to-sensor reproducibility and signal averaging.     

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.     

Evaluation of multitransducer arrays for the determination of organic vapor mixtures

A study of vapor recognition and quantification by polymer-coated multitransducer (MT) arrays is described. The primary data set consists of experimentally derived sensitivities for 11 organic vapors obtained from 15 microsensors comprising five cantilever, capacitor, and calorimeter devices coated with five different sorptive-polymer films. These are used in Monte Carlo simulations coupled with principal component regression models to assess expected performance. Recognition rates for individual vapors and for vapor mixtures of up to four components are estimated for single-transducer (ST) arrays of up to five sensors and MT arrays of up to 15 sensors. Recognition rates are not significantly improved by including more than five sensors in an MT array for any specific analysis, regardless of difficulty. Optimal MT arrays consistently outperform optimal ST arrays of similar size, and with judiciously selected 5-sensor MT arrays, one-third of all possible ternary vapor mixtures are reliably discriminated from their individual components and binary component mixtures, whereas none are reliably determined with any of the ST arrays. Quaternary mixtures could not be analyzed effectively with any of the arrays. A "universal" MT array consisting of eight sensors is defined, which provides the best possible performance for all analytical scenarios. Accurate quantification is predicted for correctly identified vapors.