Sensing array for coherence analysis of modulated aquatic chemical plumes

Here we show that an array of sensors can provide information about the spatial and temporal distribution of chemicals in liquid turbulent plumes. Planar laser induced fluorescence (PLIF) and amperometric sensor arrays were used to record signals from modulated chemical plumes released into a recirculating flume. Coherence analysis was applied to extract the frequency components contained in the sensor response. Effects due to release distance, modulation frequency, and array orientation were investigated. This study has demonstrated that frequency encoded information can be extracted from a turbulent chemical plume using an array of amperometric sensors with optimized three-dimensional geometry and tuning.     

Neuromorphic Processing for Optical Microbead Arrays: Dimensionality Reduction and Contrast Enhancement

This paper presents a neuromorphic approach for sensor-based machine olfaction that combines a portable chemical detection system based on microbead array technology with a biologically inspired model of signal processing in the olfactory bulb. The sensor array contains hundreds of microbeads coated with solvatochromic dyes adsorbed in, or covalently attached on, the matrix of various microspheres. When exposed to odors, each bead sensor responds with corresponding intensity changes, spectral shifts, and time-dependent variations associated with the fluorescent sensors. The bead array responses are subsequently processed using a model of olfactory circuits that capture the following two functions: chemotopic convergence of receptor neurons and center on-off surround lateral interactions. The first circuit performs dimensionality reduction, transforming the high-dimensional microbead array response into an organized spatial pattern (i.e., an odor image). The second circuit enhances the contrast of these spatial patterns, improving the separability of odors. The model is validated on an experimental dataset containing the responses of a large array of microbead sensors to five different analytes. Our results indicate that the model is able to significantly improve the separability between odor patterns, compared to that available from the raw sensor response     

Frequency-coded chemical sensors

We have developed a new method to intelligently sample analytes and introduce the analytes to sensors. The method automatically adjusts sampling duration according to the sensors' response to the analytes and converts the amplitude of the sensor output to a frequency output, giving us another opportunity to reduce noise in the signal. It also addresses some of the common sensor issues such as response time, saturation, chemical dynamic range, and sensor protection, saving precious detection time, protecting sensors, and enabling sensitive sensors built for low-concentration detection to be used for high-concentration detection as well. We have put together a system using a tuning fork chemical sensor as a sample sensor to demonstrate the feasibility and benefits of the new sensing technique.     

Real-time detection of organic compounds in liquid environments using polymer-coated thickness shear mode quartz resonators

The selection of sensitive coatings is a critical task in the design and implementation of chemical sensors using coated thickness shear mode quartz crystal resonators (QCRs) for detection in liquid environments. This design or selection is performed through a study of the sorption process in terms of the partition coefficients of the analytes in the coatings. The partition coefficient, which is controlled by the chemical and physical properties of the coating materials, determines the inherent selectivity and sensitivity toward analyte molecules. The selection of the coatings is logically determined by the interactions between coating and target analyte molecules, but can also be made through a systematic variation of the coating's properties. The determination of the partition coefficients is only accurate if all contributions to the total measured frequency shifts, deltafs, of the coated QCR can be established. While mass loading is often assumed to be the dominant factor used in determining partition coefficients, viscoelastic effects may also contribute to deltafs. Both the effect of viscoelastic properties and the effect of mass loading on the sensor responses are investigated by using a network analyzer and oscillator circuit and by characterizing the total mechanical impedance of the loaded sensor. Different types of coatings including rubbery and glassy polymers are investigated, and the targeted analytes include classes of polar compounds (methanol), nonpolar compounds (toluene, xylenes), and chlorinated hydrocarbons (trichloroethylene, tetrachloroethylene, etc). It is seen that changes in viscoelastic properties due to analyte sorption may be significant enough to place the sensor in the nongravimetric regime. However, for most applications involving the detection of relatively low concentrations of organic compounds and the use of acoustically thin films, changes in the complex shear modulus of the coatings contribute less than 5% of the total shift in the series resonant frequency, depending on the coating. In that case, the measured deltafs and, hence, the calculated approximate classification and selection of the coatings for operation in a complex solution of water/analyte molecules.     

矢量水听器阵列自适应子空间跟踪算法

矢量水听器能同时共点获得声场中声压和振速,与其他水听器相比,能获得更多的信息量,具有很好的应用前景。矢量水听器阵列的MUSIC算法能实现360°无模糊方位估计,然而对于方位时变的目标源,该算法很难完成对上述目标源方位进行实时跟踪估计。鉴于此,将MALASE算法和MUSIC算法相结合,提出了一种矢量水听器阵列的自适应子空间跟踪算法。仿真结果表明,该算法既保留了MUSIC算法的性能,又实现了对目标源进行实时跟踪估计,且方位估计误差仅为0．4°左右。     

Preparation and properties of vapor detector arrays formed from poly(3,4-ethylenedioxy)thiophene-poly(styrene sulfonate)/insulating polymer composites

Poly(3,4-ethylenedioxy)thiophene-poly(styrene sulfonate) (PEDOT-PSS) was used as the conductive component in a matrix of chemically different insulating polymers to form an array of vapor detectors. Such composites produced larger relative differential resistance responses when exposed to polar analytes than did the corresponding carbon black filled polymer composite detectors. However, the PEDOT-PSS composites produced smaller responses than carbon black composites when exposed to nonpolar analytes. The resolving power of a PEDOT-PSS detector array was compared to that of a carbon black composite array for a broadly construed set of organic vapors. The PEDOT-PSS array exhibited better, on average, discrimination between pairs of polar analytes and polar/nonpolar analytes than did the carbon black composite array. The carbon black composite array out-performed the PEDOT-PSS array in discriminating between nonpolar compounds. The addition of PEDOT-PSS composites to an array of carbon black composite detectors therefore can produce improved overall discrimination in a vapor sensor system when used in tasks to differentiate between of a broad set of analyte vapors.     

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%.     

3,3',5,5'-tetramethyl-N-(9-anthrylmethyl)benzidine: a dual-signaling fluorescent reagent for optical sensing of aliphatic aldehydes

A new optical chemical sensor for continuous monitoring of aliphatic aldehydes has been proposed based on the reversible chemical reaction between a new sensing reagent, 3,3',5,5'-tetramethyl-N-(9-anthrylmethyl)benzidine (TMAB), and the analytes. TMAB, containing two receptors and two fluorescent reporters, can perform dual fluorescence responses corresponding to the reactions of hydrogen ion and carbonyl compound. When immobilized in a plasticized poly(vinyl chloride) membrane, TMAB extracts aliphatic aldehydes from aqueous solution into the bulk membrane phase and reacts with the analyte by forming a Schiff base. Since the extraction equilibrium and chemical reaction are accompanied by fluorescence increase of the sensing membrane, the chemical recognition process could be directly translated into an optical signal. At pH 3.20, the sensor exhibits a dynamic detection range from 0.017 to 4.2 mM n-butyraldehyde with a limit of detection of 0.003 mM. The forward response time (t95) of the sensor is 3-5 min, and the reverse response time is 5-7 min. The responses of the sensor toward different kinds of aldehydes and ketones depend on the lipophilicity and the reactivity of the analytes. Since the fluorescence enhancement of the sensing membrane at 296 nm/410 nm is only related to the formation of Schiff base, the measurement of aldehydes is independent of pH.     

Detection of moving point objects against a moving background

The temporal spectral characteristics of a dim moving point object and a moving background, as observed by a sensor array, are analyzed. This type of problem occurs in remote sensing, machine vision, and many other applications. The diffraction limitation of the sensor optics ensures that the temporal spectrum of the background moving with a finite velocity has a finite maximum bandwidth, regardless of background structure. Because the outputs of the sensor array are time sampled, its spectrum is infinitely replicated over an interval of temporal frequency equal to the reciprocal of the sampling time. If this interval is at least twice as large as the maximum background temporal frequency, there is a region with no background components in the middle of each interval. However, because the point object temporal spectrum in the sampled sensor array output is continuously distributed, this region will contain part of the point object signal. Thus, a criterion for the existence of an effective background suppression filter is that the point object fundamental frequency must be greater than the maximum background temporal frequency. When this criterion is satisfied, the amount of background leakage in the filter depends on the sharpness of its passband response and its stopband characteristics. In general, higher-order filters have sharper response and hence better performance. If the criterion is not met, all types of filter lose their effectiveness since the background signal will leak through the passband of the filter. The fundamental concepts developed here were examined for some typical parameter values. It is shown that for this system the point object can be effectively discriminated. In some cases the point object and background temporal spectral responses vary significantly with spatial position within the field of view. Because the filter's center frequency must match the point object temporal fundamental frequency, it is necessary to use an adaptive filter in these situations.     

Chemical sensor based on microfabricated wristwatch tuning forks

We report here a chemical sensor based on detecting the mechanical response of a thin (approximately 10-microm) polymer wire stretched across the two prongs of a wristwatch quartz tuning fork (QTF). When the fork is set to oscillate, the wire is stretched and compressed by the two prongs. The stretching/compression force changes upon adsorption of analyte molecules onto/into the polymer wire, which is detected by the QTF with pico-Newton force sensitivity. An array of such sensors with different polymer wires is used for simultaneous detection of several analytes and for improvement of pattern recognition. The low cost (approximately 10 cent) of the QTF, together with that an array of QTFs can be driven to oscillate simultaneously and their resonance frequencies detected with the same circuit, promises a high performance, low cost, and portable sensor for detecting various chemical vapors. We demonstrate here detection of parts-per-billion-level water, ethylnitrobenzene, and ethanol vapors using the QTF arrays.     

Protein sensing and cell discrimination using a sensor array based on nanomaterial-assisted chemiluminescence

Cross-reactive sensor arrays, known as "chemical noses", offer an alternative to time-consuming analytical methods. Here, we report a sensor array based on nanomaterial-assisted chemiluminescence (CL) for protein sensing and cell discrimination. We have found that the CL efficiencies are improved to varied degrees for a given protein or cell line on catalytic nanomaterials. Distinct CL response patterns as "fingerprints" can be obtained on the array and then identified through linear discriminant analysis (LDA). The sensing of 12 kinds of proteins at three concentrations, as well as 12 types of human cell lines among normal, cancerous, and metastatic, has been performed. Compared with most fluorescent or colorimetric approaches which rely on the strong interaction between analytes and sensing elements, our array offers the advantage of both sensitivity and reversibility.     

Bioinspired methodology for artificial olfaction

Artificial olfaction is a potential tool for noninvasive chemical monitoring. Application of "electronic noses" typically involves recognition of "pretrained" chemicals, while long-term operation and generalization of training to allow chemical classification of "unknown" analytes remain challenges. The latter analytical capability is critically important, as it is unfeasible to pre-expose the sensor to every analyte it might encounter. Here, we demonstrate a biologically inspired approach where the recognition and generalization problems are decoupled and resolved in a hierarchical fashion. Analyte composition is refined in a progression from general (e.g., target is a hydrocarbon) to precise (e.g., target is ethane), using highly optimized response features for each step. We validate this approach using a MEMS-based chemiresistive microsensor array. We show that this approach, a unique departure from existing methodologies in artificial olfaction, allows the recognition module to better mitigate sensor-aging effects and to better classify unknowns, enhancing the utility of chemical sensors for real-world applications.     

Trace-Level,Multi-Gas Detection for Food Quality Assessment Based on Decorated Silicon Transistor Arrays

Multiplexed gas detection at room temperature is critical for practical applications, such as for tracking the complex chemical environments associated with food decomposition and spoilage. An integrated array of multiple silicon-based, chemical-sensitive field effect transistors (CSFETs) is presented to realize selective, sensitive, and simultaneous measurement of gases typically associated with food spoilage. CSFETs decorated with sensing materials based on ruthenium, silver, and silicon oxide are used to obtain stable room-temperature responses to ammonia (NH₃), hydrogen sulfide (H₂S), and humidity, respectively. For example, one multi-CSFET sensor signal changes from its baseline by 13.34 in response to 1 ppm of NH₃, 724.45 under 1 ppm H₂S, and 23.46 under 80% relative humidity, with sensitive detection down to 10 ppb of NH₃ and H₂S. To demonstrate this sensor for practical applications, the CSFET sensor array is combined with a custom-printed circuit board into a compact, fully integrated, and portable system to conduct real-time monitoring of gases generated by decomposing food. By using existing silicon-based manufacturing methodologies, this room-temperature gas sensing array can be fabricated reproducibly and at low cost, making it an attractive platform for ambient gas measurement needed in food safety applications.     

Hybrid amperometric and conductometric chemical sensor based on conducting polymer nanojunctions

We report on a hybrid chemical sensor that can perform either amperometric or conductometric detection alone or simultaneously. It consists of an array of electrode pairs in which the two electrodes in each pair are separated with micrometer to nanometer-scale gaps. The gaps are bridged with conducting polymer (polyaniline) so that one can measure the conductance of the polymer bridge like a conventional Chem-FET. The electrode geometries are designed to allow simultaneously detection of electrochemical current like a conventional microelectrode amperometric sensor. The hybrid device provides increased selectivity for detection of analytes in complex matrixes and may provide new insights into the electrochemical reaction mechanisms of analytes. As an example, we have demonstrated the detection of dilute neurotransmitter (dopamine) in the presence of its concentrated major physiological interferent, ascorbic acid, which is not possible using either the amperometric or the conductometric techniques alone.     

Discriminative detection of volatile sulfur compound mixtures with a plasma-polymerized film-based sensor array installed in a humidity-control system

We demonstrated the discrimination of volatile sulfur compound mixtures with different mixing ratios by using an array of the plasma-polymerized film (PPF)-coated quartz crystal resonators. The PPF sensor array, which contains PPFs prepared from amino acids and synthetic polymers, exhibited different response patterns to mono or mixed volatile sulfur compounds (VSCs) (hydrogen sulfide and methanethiol) under a dry environment. The sensor array was installed in a desktop-size relative humidity controller. The relative humidity and temperature conditions of the sample flow to the sensor cell were equalized to those of the inner atmosphere of the sensor cell based on the concept of the two-separate-temperatures method. In this way, the baseline drift of PPF sensor response caused by the introduction of a highly humid sample was successfully suppressed. We compared the sensor array responses under the controlled humidity conditions. Presorption of water molecules by PPFs caused a decrease of sensor sensitivity, but the films still had the ability to discriminate sub-ppmv VSC mixtures having 6:1, 1:1, and 1:6 mixture ratios of hydrogen sulfide and methanethiol.     

Ordered‐Assembly Conductive Nanowires Array with Tunable Polymeric Structure for Specific Organic Vapor Detection

An artificial organic vapor sensor based on a finite number of 1D nanowires arrays can provide a strategy to allow classification and identification of different analytes with high efficiency, but fabricating a 1D nanowires array is challenging. Here, a coaxial Ag/polymer nanowires array is prepared as an organic vapor sensor with specific recognition, using a strategy combining superwettability‐based nanofabrication and polymeric swelling‐induced resistance change. Such organic vapor sensor containing commercial polymers can successfully classify and identify various organic vapors with good separation efficiency. An Ag/polymer nanowires array with synthetic polyethersulfone polymers is also fabricated, through molecular structure modification of the polymers, to distinguish the similar organic vapors of methanol and ethanol. Theoretical simulation results demonstrate introduction of specific molecular interaction between the designed polymers and organic vapors can improve the specific recognition performance of the sensors.     

Design of a MEMS acoustical beamforming sensor microarray

This paper describes the design methodology for a microelectromechanical systems (MEMS)-based acoustical beamforming sensor microarray. The proposed acoustical array offers the potential of controlled directional sensitivity with constant beamwidth when used in conjunction with the appropriate digital signal processor. The array has been designed for use in a hearing instrument with a digital beamsteering engine to provide controlled directional sensitivity and constant beamwidth over the audio frequency range to improve speech intelligibility in noisy and reverberant environments. A MEMS-based packaging solution that allows the sensor array to be mounted in the ear canal is also described. The MEMS sensor-package interface features microspring contacts that enable low impedance connectivity between the sensor array and the related microelectronics. This allows the array to be easily removed for cleaning or replacement purposes.     

Fluorescent polymer sensor array for detection and discrimination of explosives in water

A fluorescent polymer sensor array (FPSA) was made from commercially available fluorescent polymers coated onto glass beads and was tested to assess the ability of the array to discriminate between different analytes in aqueous solution. The array was challenged with exposures to 17 different analytes, including the explosives trinitrotoluene (TNT), tetryl, and RDX, various explosive-related compounds (ERCs), and nonexplosive electron-withdrawing compounds (EWCs). The array exhibited a natural selectivity toward EWCs, while the non-electron-withdrawing explosive 1,3,5-trinitroperhydro-1,3,5-triazine (RDX) produced no response. Response signatures were visualized by principal component analysis (PCA), and classified by linear discriminant analysis (LDA). RDX produced the same response signature as the sampled blanks and was classified accordingly. The array exhibited excellent discrimination toward all other compounds, with the exception of the isomers of nitrotoluene and aminodinitrotoluene. Of particular note was the ability of the array to discriminate between the three isomers of dinitrobenzene. The natural selectivity of the FPSA toward EWCs, plus the ability of the FPSA to discriminate between different EWCs, could be used to design a sensor with a low false alarm rate and an excellent ability to discriminate between explosives and explosive-related compounds.     

Tunable Fabry-Perot etalon-based long-wavelength infrared imaging spectroradiometer

Imaging spectrometry enables passive, stand-off detection and analysis of the chemical composition of gas plumes and surfaces over wide geographic areas. We describe the use of a long-wavelength infrared imaging spectroradiometer, comprised of a low-order tunable Fabry-Perot etalon coupled to a HgCdTe detector array, to perform multispectral detection of chemical vapor plumes. The tunable Fabry-Perot etalon used in this research provides coverage of the 9.5-14-mum spectral region with a resolution of 7-9 cm(-1). The etalon-based imaging system provides the opportunity to image a scene at only those wavelengths needed for chemical species identification and quantification and thereby minimize the data volume necessary for selective species detection. We present initial results using a brassboard imaging system for stand-off detection and quantification of chemical vapor plumes against near-ambient-temperature backgrounds. These data show detection limits of 22 parts per million by volume times meter (ppmv x m) and 0.6 ppmv x m for dimethyl methyphosphonate and SF(6), respectively, for a gas/background DT of 6 K. The system noise-equivalent spectral radiance is approximately 2 muW cm(-2) sr(-1) mum(-1). Model calculations are presented comparing the measured sensitivity of the sensor to the anticipated signal levels for two chemical release scenarios.