Mimicking the biological olfactory system: a Portable electronic Mucosa

In this study the authors report on the development of a new type of electronic nose (e-nose) instrument, which the authors refer to as the Portable electronic Mucosa (PeM) as a continuation of previous research. It is designed to mimic the human nose by taking significant biological features and replicating them electronically. The term electronic mucosa or simply e-mucosa was used because our e-nose emulates the nasal chromatographic effect discovered in the olfactory epithelium, located within the upper turbinate. The e-mucosa generates spatio-temporal information that the authors believe could lead to improved odour discrimination. The PeM comprises three large sensor arrays each containing a total of 576 sensors, with 24 different coatings, to increase the odour selectivity. The nasal chromatographic effect provides temporal information in the human olfactory system, and is mimicked here using two-coated retentive channels. These channels are coated with polar and non-polar compounds to enhance the selectivity of the instrument. Thus, for an unknown sample, the authors have both the spatial information (as with a traditional e-nose) and the temporal information. The authors believe that this PeM may offer a way forward in developing a new range of low-cost e-noses with superior odour specificity.     

A novel method for reducing the dimensionality in a sensor array

Specific types of gas sensors are normally produced by adding different dopants to a common substrate. The advancement of technology has made the fabrication of many dopants and consequently various sensors possible. As a result, in each family of gas sensors, one can find tens of different sensors which are only slightly different in the spectrum of response to various volatile compounds. The wide variety of available gas sensors creates a selection problem for any specific application. Sensor selection/reduction becomes even more important when cost and technology limitations are issues of concern. Accordingly, a methodology by which one can tailor a sensor array to a specific need is highly desirable. In this paper, a novel method is introduced to address this task using data from an electronic nose that uses polymer gas sensors. This method has been delineated based on the geometry of eigenvectors in Karhunen-Loeve expansion. The methodology is general and therefore suitable for many other feature selection problems     

Hybrid optical-electrochemical electronic nose system based on Zn-porphyrin and multi-walled carbon nanotube composite

In this work, we have enhanced the capability of an e-nose system based on combined optical and electrochemical transduction within a single gas sensor array. The optical part of this e-nose is based on detection of the absorption changes of light emitted from eight light emitting diodes (LEDs) as measured by a CMOS photo-detector. The electrochemical part works by measuring the change in electrical resistivity of the sensing materials upon contact with the sample vapor. Zinc-5,10,15,20-tetra-phenyl-21H,23H-porphyrin (ZnTPP) and multi-walled carbon nanotube (MWCNT) composite was used as the sensing materials based on its good optoelectronic properties. This sensing layer was characterized by UV-Vis spectroscopy and atomic force microscope and tested with various VOC vapors. Density functional theory (DFT) calculations were performed to investigate the electronic properties and interaction energies between ZnTPP and analyte molecules. It can be clearly seen that this hybrid optical-electrochemical electronic nose system can classify the vapor of different volatile organic compounds.     

A Method of Feature Extraction on Recovery Curves for Fast Recognition Application With Metal Oxide Gas Sensor Array

In the fast recognition applications of electronic nose, not only the recognition time is important, another parameter response-recovery time also needs to be considered. The response-recovery time could be defined as the time from the beginning of measuring one sample to the state of being ready for new sample measurement. An electronic nose with nine metal oxide (MOX) gas sensors and a method of feature extraction on sensor recovery curves were presented in this paper. The electronic nose was designed to reduce the recognition time and the response-recovery time synchronously. In the sampling module of the electronic nose, there were two pumps, which could let the sensor quickly recovered. The feature extraction method could rapidly extract features from sensor recovery curves with robust information. Nine volatile organic compounds (VOCs) gas samples were measured with the electronic nose. The correct recognition ratios under 10 and 15 s recognition time are 91.0% and 95.8%, respectively. The mean response-recovery time of these sensors in the measurements was 33.5 s, which was about 42.7% of the response-recovery time in typical traditional gas sample measurements. The results show that the proposed feature extraction method could extract robust information with short recognition time and response-recovery time.     

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.     

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.     

A gradient microarray electronic nose based on percolating SnO(2) nanowire sensing elements

Fabrication, characterization, and tests of the practical gradient microarray electronic nose with SnO(2) nanowire gas-sensing elements are reported. This novel device has demonstrated an excellent performance as a gas sensor and e-nose system capable of promptly detecting and reliably discriminating between several reducing gases in air at a ppb level of concentration. It has been found that, in addition to the temperature gradient across the nanowire layer, the density and morphological inhomogeneities of nanowire mats define the discriminating power of the electronic nose.     

A conductive polymer based electronic nose for early detection of Penicillium digitatum in post-harvest oranges

We describe the construction of an electronic nose, comprising four chemiresistive sensors formed by the deposition of thin conductive polymer films onto interdigitated electrodes, attached to a personal computer via a data acquisition board. This e-nose was used to detect biodeterioration of oranges colonized by Penicillium digitatum. Significant responses were obtained after only 24 h of incubation i.e. at an early stage of biodeterioration, enabling remedial measures to be taken in storage facilities and efficiently distinguishing between good and poor quality fruits.The instrument has a very low analysis time of 40 s.     

SnO/sub 2/ gas sensing array for combustible and explosive gas leakage recognition

A gas-sensing array with ten different SnO/sub 2/ sensors was fabricated on a substrate for the purpose of recognizing various kinds and quantities of indoor combustible gas leakages, such as methane, propane, butane, LPG, and carbon monoxide, within their respective threshold limit value (TLV) and lower explosion limit (LEL) range. Nano-sized sensing materials with high surface areas were prepared by coprecipitating SnCl/sub 4/ with Ca and Pt, while the sensing patterns of the SnO/sub 2/-based sensors were differentiated by utilizing different additives. The sensors in the sensor array were designed to produce a uniform thermal distribution along with a high and differentiated sensitivity and reproducibility for low concentrations below 100 ppm. Using the sensing signals of the array, an electronic nose system was then applied to classify and identify simple/mixed explosive gas leakages. A gas pattern recognizer was implemented using a neuro-fuzzy network and multi-layer neural network, including an error-back-propagation learning algorithm. Simulation and experimental results confirmed that the proposed gas recognition system was effective in identifying explosive and hazardous gas leakages. The electronic nose in conjunction with a neuro-fuzzy network was also implemented using a digital signal processor (DSP).     

An artificial nose based on M-porphyrin (M = Mg, Zn) thin film and optical spectroscopy

Artificial nose has recently become an emerging instrument for quality assurance in the food industry. These paper present the optical gas sensors based on Magnesium-5, 10, 15, 20-tetra phenyl-porphyrin (MgTPP) and Zinc-5, 10, 15, 20-tetra phenyl-porphyrin (ZnTPP) thin films and their application as an artificial nose. Based on the measurement of optical absorbance response using a general UV-Vis spectroscopy, this artificial nose was tested to discriminate various volatile organic compounds (VOCs) and Thai beverages. Atomic force microscopy (AFM) and X-rays diffraction (XRD) were used to confirm the polycrystalline structure of the sensing materials. Density functional theory (DFT) calculations reveal that MgTPP interacts more strongly with the VOCs than ZnTPP, especially with methanol. The classification results of VOCs and Thai beverage vapors using the principal component analysis indicate that both MgTPP and ZnTPP-based artificial noses can be an efficient tool for quality assurance of alcoholic beverages.     

Individual and gender fingerprints in human body odour

Individuals are thought to have their own distinctive scent, analogous to a signature or fingerprint. To test this idea, we collected axillary sweat, urine and saliva from 197 adults from a village in the Austrian Alps, taking five sweat samples per subject over 10 weeks using a novel skin sampling device. We analysed samples using stir bar sorptive extraction in connection with thermal desorption gas chromatograph-mass spectrometry (GC-MS), and then we statistically analysed the chromatographic profiles using pattern recognition techniques. We found more volatile compounds in axillary sweat than in urine or saliva, and among these we found 373 peaks that were consistent over time (detected in four out of five samples per individual). Among these candidate compounds, we found individually distinct and reproducible GC-MS fingerprints, a reproducible difference between the sexes, and we identified the chemical structures of 44 individual and 12 gender-specific volatile compounds. These individual compounds provide candidates for major histocompatibility complex and other genetically determined odours. This is the first study on human axillary odour to sample a large number of subjects, and our findings are relevant to understanding the chemical nature of human odour, and efforts to design electronic sensors (e-nose) for biometric fingerprinting and disease diagnoses.     

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%.     

Development of electronic nose method for evaluation of residual solvents in low‐density polyethylene films

Flexible packaging films containing high levels of residual volatile organic compounds (VOCs) can alter the flavour and odour of packaged foods. Currently, a range of gas chromatographic techniques and sensory evaluations are used for assessing the residual VOCs in packaging films. An objective method for assessing the residual solvents from low‐density polyethylene (LDPE) was developed using an Alpha MOS Fox 3000 electronic nose (e‐nose) equipped with 12 metal oxide semiconductor sensors. Three VOCs, ethyl acetate, ethyl alcohol and toluene, were chosen as models for solvents of interest in flexible food packaging analysis. LDPE film samples were spiked with single and binary mixtures of solvents and analysed using the e‐nose and by GC–FID (HP 6890; Hewlett‐Packard Co., Wilmington, DE). The responses obtained from the e‐nose were processed using principal component analysis (PCA) and discriminate factorial analysis (DFA) in order to identify the residual solvents. Partial least squares analysis (PLS) was also used to quantify the amount of residual solvent and to correlate the e‐nose results with gas chromatography, which is currently the standard method for determining residual VOCs in packaging films. There was good agreement between the e‐nose responses and gas chromatography results for single solvents (r = 0.90–0.98). The technique also worked for binary solvent mixtures (r = 0.84–0.99). The electronic nose can be a viable alternative to traditional techniques while providing simplicity and objectivity, which would be extremely advantageous in routine quality control of residual solvents. Copyright © 2006 John Wiley & Sons, Ltd.     

Evaluation of on-line flue gas measurements by MISiCFET and metal-oxide sensors in boilers

Metal insulator silicon carbide field-effect transistor sensors, metal-oxide sensors, and a linear Lambda sensor in an electronic nose was used to measure on-line in hot flue gases from a boiler. Flue gas from a 100-MW pellets-fuelled boiler has been used to feed the experimental setup. Several reference instruments, which measure the flue gases in parallel to the sensor array, are connected to the electronic nose. Data was collected during six weeks and then evaluated. Using principal component analysis as the data evaluation method, different operating modes for the boiler have been identified in the data set. The different modes could be described in terms of high or low O/sub 2/ and CO concentration. Furthermore, we have shown that it seems possible to use a sensor array to determine the operating mode of the boiler and, by partial least-squares models, measure the CO concentration when the boiler operates in its optimum mode.     

智能家居气味识别装置产品设计研究及实践

目的 探究不同结构的气路和气室设计,对于气味识别装置的性能影响,以及总结归纳关键设计参数,为气味识别产品在居家环境的实际应用提供参考。方法 基于模块化的设计方法,面向电子鼻家居应用设计了6种不同的气路结构,之后开展电子鼻响应测试实验,对比6种结构的性能差异,并在实验结论基础上讨论电子鼻在不同家居应用场景下的部署模式和使用方式,以及实验结论如何应用于实际产品设计过程中。结论 实验表明,不同气室结构对电子鼻的响应性能有着显著的影响,对家居场景中气味采集应用的气路设计具有指导意义,从而帮助提升气味识别能力,赋能家居功能创新和服务创新,提升用户体验。     

Synthesis and integration of tin oxide nanowires into an electronic nose

Single crystal nanostructures of semiconducting tin oxides have been fabricated and characterized as sensing materials for implementation in an electronic nose. The nanowires exhibit exceptional crystalline quality and a very high length-to-width ratio, resulting in enhanced sensing capability as well as long-term material stability for prolonged operation. A sensing device based on SnO₂ nanowires has been fabricated and comparatively tested in an array of chemical sensor with conventional thin film sensing device. Preliminary measurements ethanol/water mixtures demonstrate that nanowire-based sensors can be favourably implemented in the electronic nose and that they perform comparably with the conventional thin film layers.     

纳米氧化锡气敏材料及其传感器阵列的研究进展

对纳米氧化锡气敏材料的理论及应用研究进行了综合性阐述, 重点介绍了运用纳米技术和薄膜技术制备氧化锡气体传感器的研究进展, 并讨论了氧化锡气体传感阵列在电子鼻智能嗅觉系统中的应用现状和前景.     

Analysis of Volatile Bread Aroma for Evaluation of Bread Freshness Using an Electronic Nose (E-Nose)

This paper presents the use of a tin-oxide sensor array and self-organized map (SOM)-based E-nose for analysis of volatile bread aroma and explores its ability to cluster bread odor data according to the freshness of bread. A low cost tin-oxide sensor array based electronic nose system has been used for the classification of state of freshness of bread. The sensor data was acquired for a period of 3 weeks, and an unsupervised self-organizing map (SOM) model was trained using this data to correlate the sensor response to classify the bread as fresh and stale. A comparative evaluation of 3 week' of bread data was carried out using the SOM. The results suggest that the system developed is able to predict the state of bread as fresh and stale up to 98% accuracy if the test bread data sets are of the same week. The classification accuracy reduces to 75-85% if test bread data sets are from different weeks. The model is also applied on three different brands of bread and similar classification results are obtained.     

Semiconductor metal oxide compounds based gas sensors: A literature review

This paper gives a statistical view about important contributions and advances on semiconductor metal oxide (SMO) compounds based gas sensors developed to detect the air pollutants such as liquefied petroleum gas (LPG), H₂S, NH₃, CO₂, acetone, ethanol, other volatile compounds and hazardous gases. Moreover, it is revealed that the alloy/composite made up of SMO gas sensors show better gas response than their counterpart single component gas sensors, i.e., they are found to enhance the 4S characteristics namely speed, sensitivity, selectivity and stability. Improvement of such types of sensors used for detection of various air pollutants, which are reported in last two decades, is highlighted herein.