Optical multibead arrays for simple and complex odor discrimination

A fiber optic bead-based sensor array platform has been employed to discriminate between six different odors and air carrier gas. Six different bead sensor types, with over 250 replicates of each, were monitored before, during, and after odor exposure to produce time-dependent fluorescence response patterns that were unique for each sensor-analyte combination. A total of 2,683 sensors were analyzed with respect to changes in their fluorescence, and signals from identical sensor beads were averaged to improve signal-to-noise ratios. Analyte classification rates of 100% were achieved for three complex (coffee bean) odors and three pure (simple) odors (toluene, acetone, 1,3-dinitrotoluene) measured at their highest relative concentrations. When lower odor concentrations were employed, the system exhibited better than 85% classification rates for analyte discrimination. Sensor response repeatability to these odor stimuli has also been quantified statistically, which is vital in defining the detection limit of the overall system. These results demonstrate, for the first time, the utility of our bead array technology for discriminating between different odor types at various dilution levels.     

Information coding in artificial olfaction multisensor arrays

High-density sensor arrays were prepared with microbead vapor sensors to explore and compare the information coded in sensor response profiles following odor stimulus. The coded information in the sensor-odor response profiles, which is used for odor discrimination purposes, was extracted from the microsensor arrays via two different approaches. In the first approach, the responses from individual microsensors were separated (decoded array) and independently processed. In the second approach, response profiles from all microsensors within the entire array, i.e., the sensor ensemble, were combined to create one response per odor stimulus (nondecoded array). Although the amount of response data is markedly reduced in the second approach, the system shows comparable odor discrimination rates for the two signal extraction methods. The ensemble approach streamlines system resources without decreasing system performance. These signal compression approaches may simulate or parallel information coding in the mammalian olfactory system.     

Convergent, self-encoded bead sensor arrays in the design of an artificial nose.

We report a new approach to designing an artificial nose based on high-density optical arrays that directly incorporate a number of structural and operational features of the olfactory system. The arrays are comprised of thousands of microsphere (bead) sensors, each belonging to a discrete class, randomly dispersed across the face of an etched optical imaging fiber. Beads are recognized and classified after array assembly by their unique, "self-encoded" response pattern to a selected vapor pulse. The high degree of redundancy built into the array parallels that found in nature and affords new opportunities for chemical-sensor signal amplification. Since each bead is independently addressable through its own light channel, it is possible to combine responses from same-type beads randomly distributed throughout the array in a manner reminiscent of the sensory-neuron convergence observed in the mammalian olfactory system. Signal-to-noise improvements of approximately n1/2 have been achieved using this method.     

Identification of odors using a sensor array with kinetic working temperature and Fourier spectrum analysis

A method for the identification of odors using a dynamically driven sensor array has been developed, in which transient responses of the sensor array were used to recognize target odors. Fourier transformation was used to transform the transient response curves of the sensor array into Fourier spectra, and patterns composed of some of the magnitudes in the spectra were used in the pattern recognition to identify the odors. Identification of odors was performed using this method with three kinds of 10% ethanol solution of tea extract and three kinds of Japanese soy sauce. In consequence, the sample odors could be correctly recognized without any pretreatment device for separation of minor components from the main component.     

Fundamental study of odor recorder for multicomponent odor using recipe exploration method based on singular value decomposition

A new method for the odor recorder, electronically recording the recipe of odors or scents made up of many components, was proposed. Although apple flavors have been recorded with a mixture of five components using the odor recorder in previous work, the number of odor components should be increased to expand the applicable range of odors. Since the collinearity problem of the odor sensor array became apparent with the increase of components, a new method based on variable transformation using singular value decomposition was developed in this paper, to extract the effective subspace of the sensor outputs for recipe exploration. As a result, the sensor-array response pattern of the reproduced odor, with the eight-component recipe, almost agreed with that of the target apple flavor. Furthermore, human sensory tests revealed that the smell of the approximated odor was identical to that of the target flavor.     

Sensor Selection for Machine Olfaction Based on Transient Feature Extraction

Machine olfaction devices, which are often called electronic noses (e-noses), are gaining favor for odor assessment applications in several industrial sectors, such as beverage, perfumery, and food. From a design point of view, the number of sensors in these devices for a particular odor application should be minimized without degrading classification accuracy. This paper deals with selecting sensors for e-noses to make small portable devices with fast response times and reduced cost possible. Prior research efforts have been reported in the open literature and have shown that many advantages can be gained by properly selecting the input features before forwarding to a pattern classification algorithm. This selection process can reduce the dimensionality of the feature space, remove redundant and irrelevant features, speed up classification, and improve classification performance. In this paper, the transient features of an array of sensors obtained by applying a multiresolutional approximation technique from the discrete wavelet transform (DWT) are investigated to search for an optimal sensor array to be implemented in the e-nose system. A genetic algorithm is adapted to tailor a gas sensor array for two different odor data sets (coffee and soda). From the experimental results, the input features obtained by applying the DWT to the transient sensor responses not only provide a significant reduction in the number of sensors when compared to traditional features but also improve the classification rate to near 100%.     

Extending the longevity of fluorescence-based sensor arrays using adaptive exposure

Fluorescent microbead sensor arrays were prepared to determine sensor array longevity. Sensor longevity is limited by photobleaching of the dyes attached to the microbeads and presents one of the biggest drawbacks of most fluorescent dye-based arrays. Responses of an array of organic vapor sensors were acquired for 2 weeks to evaluate the sensor performance over time. Photobleaching effects were overcome in two ways: (1) by limiting the excitation light power and gradually increasing the power at a rate comparable to the sensor photobleaching rates and (2) by illuminating subsections of the array through an optical slit. Both approaches extended the longevity of a sensor array. During the longevity study, the sensor arrays were employed to test their ability to correctly distinguish between responses to seven vapors. A high classification accuracy (99.8%) was obtained after 17,700 exposures for vapor responses collected over two weeks using only approximately 8% of the array's surface area.     

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.     

Optimization of gas-sensitive polymer arrays using combinations of heterogeneous and homogeneous subarrays

Results for optimizing an array of conducting polymer gas sensors for sensing one of five analytes in the presence of up to four interferents are presented. The optimized array consists of subarrays of homogeneous (like) sensors contributing to a larger heterogeneous array of up to ten points (unlike sensors) in multidimensional sensor space. The optimization techniques presented here are linear, since the polymer sensors in their useful (low concentration) operating range exhibit linear and additive response characteristics. The optimization of these arrays produces maximum separability between analytes, demonstrating the trade-off between the addition of both information and variability induced by increasing the size of the heterogeneous array. Optimization results for sensing acetone, hexane, THF, toluene, and ethanol in the presence of interferents result in array sizes that are significantly less than the maximum available number of sensors (ten in the heterogeneous partition of the array). This result adds fuel to the argument that fewer sensors are better; the argument for more sensors, however, is also made in the context of the electronic nose systems where significant chemical diversity is required. Homogeneous subarrays of up to four elements each improve the separability of analytes in these optimized heterogeneous arrays by over 10% and also effectively flag broken or unhealthy sensors in a manner that is independent of analyte and concentration.     

DNA hybridization and discrimination of single-nucleotide mismatches using chip-based microbead arrays

The development of a chip-based sensor array composed of individually addressable agarose microbeads has been demonstrated for the rapid detection of DNA oligonucleotides. Here, a "plug and play" approach allows for the simple incorporation of various biotinylated DNA capture probes into the bead-microreactors, which are derivatized in each case with avidin docking sites. The DNA capture probe containing microbeads are selectively arranged in micromachined cavities localized on silicon wafers. The microcavities possess trans-wafer openings, which allow for both fluid flow through the microreactors/analysis chambers and optical access to the chemically sensitive microbeads. Collectively, these features allow the identification and quantitation of target DNA analytes to occur in near real time using fluorescence changes that accompany binding of the target sample. The unique three-dimensional microenvironment within the agarose bead and the microfluidics capabilities of the chip structure afford a fully integrated package that fosters rapid analyses of solutions containing complex mixtures of DNA oligomers. These analyses can be completed at room temperature through the use of appropriate hybridization buffers. For applications requiring analysis of < or = 10(2) different DNA sequences, the hybridization times and point mutation selectivity factors exhibited by this bead array method exceed in many respects the operational characteristics of the commonly utilized planar DNA chip technologies. The power and utility of this microbead array DNA detection methodology is demonstrated here for the analysis of fluids containing a variety of similar 18-base oligonucleotides. Hybridization times on the order of minutes with point mutation selectivity factors greater than 10000 and limit of detection values of approximately 10(-13) M are obtained readily with this microbead array system.     

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.     

DNA-decorated carbon nanotubes for chemical sensing

We demonstrate a new, versatile class of nanoscale chemical sensors based on single-stranded DNA (ss-DNA) as the chemical recognition site and single-walled carbon nanotube field effect transistors (swCN-FETs) as the electronic read-out component. swCN-FETs with a nanoscale coating of ss-DNA respond to gas odors that do not cause a detectable conductivity change in bare devices. Responses of ss-DNA/swCN-FETs differ in sign and magnitude for different gases and can be tuned by choosing the base sequence of the ss-DNA. ss-DNA/swCN-FET sensors detect a variety of odors, with rapid response and recovery times on the scale of seconds. The sensor surface is self-regenerating: samples maintain a constant response with no need for sensor refreshing through at least 50 gas exposure cycles. This remarkable set of attributes makes sensors based on ss-DNA decorated nanotubes very promising for "electronic nose" and "electronic tongue" applications ranging from homeland security to disease diagnosis.     

A Multiplexed Impedance Analyzer for Characterizing Polymer-Coated QCM Sensor Arrays

This paper describes the development and evaluation of a custom-built impedance analyzer, which uses a multiplexing bridge circuit to characterize an array of polymer-coated quartz crystal microbalance (QCM) sensors. The analyzer is constructed on a single printed circuit board with minimum components and is sufficiently compact for integration into a handheld format. The custom-built device is used to observe the changes that occur in QCM sensors when experimental conditions such as polymer coating film thickness, odorant vapor pressure, and relative molecular mass are varied. An equivalent electric circuit for a QCM is used to model the conductance and susceptance data captured by the analyzer. The measured response of an array of QCM sensors demonstrates that the custom-built device is a suitable instrument for detecting different gases and understanding polymer–vapor interactions.     

Odor Recorder Capable of Wide Dynamic Recordable Range Based on Higher Order Sensing and Signal Extraction Technique for Small Signal

The odor recording method for extending dynamic recordable range was proposed. In this method, the enriched information obtained from higher order sensing based on preconcentrator with variable temperature was utilized so that the contribution of component with small ratio to sensor response could be separately extracted from that of the main component. Then, the signal extraction technique for small signal was developed using Savitzky-Golay filter for qualitative and quantitative detection of component with small ratio, and then this extracted information was used in recording process. It was found that the target odors including component with small ratio down to 1% were successfully recorded using this proposed method. This method is useful to extend the dynamic recordable range especially in the case that the component with high contribution in impression has low contribution to sensor responses.     

Application of an array sensor based on plasma-deposited organic film coated quartz crystal resonators to monitoring indoor volatile compounds

The basic response ability of an array sensor based on plasma-deposited organic film-coated quartz crystal resonators (QCRs) was investigated with a view to their use for indoor air monitoring. The array of plasma-deposited organic film-coated QCRs was applied to detect and separate volatile organic compounds (VOCs) including alkanes, aromatic carbons, chlorocarbons, ketones, and alcohols. Continuous monitoring tests were tried in a real room environment (a refreshment area and a smoking area) with an array of plasma-deposited organic film-coated QCRs along with commercial sensors for indoor monitoring, a relative humidity/temperature sensor, a carbon dioxide sensor, and a three-dimensional micro-ultrasonic airflow meter. To provide a comparison commercial VOC detectors based on a photo-ionization detector and a semiconductor for indoor monitoring tests were used. The plasma-deposited organic film-coated QCRs exhibited fast pulse responses to volatile compounds in the room air along the baseline shift correlated with relative humidity changes and more sensitive responses compared with commercial organic gas detectors.     

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.     

An optoelectronic nose: "seeing" smells by means of colorimetric sensor arrays

A new approach to general sensors for odors and volatile organic compounds (VOCs) using thin films of chemically responsive dyes as a colorimetric sensor array is described. This optoelectronic "nose," by using an array of multiple dyes whose colors change based on the full range of intermolecular interactions, provides enormous discriminatory power among odorants in a simple device that can be easily digitally imaged. High sensitivities (ppb) have been demonstrated for the detection of biologically important analytes such as amines, carboxylic acids, and thiols. By the proper choice of dyes and substrate, the array can be made essentially nonresponsive to changes in humidity.     

Transition Metal Exchanged Zeolite Layers for Selectivity Enhancement of Metal-Oxide Semiconductor Gas Sensors

A novel method of improving the selectivity of metal oxide gas sensors has been developed by using catalytically active molecular sieve materials. They have been successfully introduced into a proprietary sensor array. The cracking patterns of linear alkanes over transition metal exchanged zeolite Y have been measured using a zeolite bed/GC/MS experimental set-up within a temperature range of 300degC to 400degC. Studies have been carried out regarding the effects of metal loading, zeolite type, material fabrication techniques, and operating temperature in relation to catalytic activity and selectivity. The composite sensors utilising the novel zeolite materials have been used in a custom built sensor rig that houses three dual electrode sensors and can measure real-time responses of these sensors to an introduced headspace generated from organic liquids