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Odour discrimination with an electric nose
Abstract
Smell is probably the least understood and exploited of the principal human senses, yet it is clearly important to both product and process control in many industries, such as foodstuffs, beverages, tobacco and perfumery. Advances in the field of integrated microelectronic devices have led to new instruments, robots, capable of vision and complex touch or taction, but not yet of smell. This paper reviews the research effort that has been carried out at Warwick University over recent years into the development of an electronic instrument that can mimic the human sense of smell. The approach that we have adopted is to construct a microprocessor-controlled system comprising an array of solid-state chemical gas sensors (with overlapping partial sensitivities to odorants) and associated signal processing and pattern recognition. This electronic system is based upon our present knowledge of the biological system. Our earliest electronic nose consisted of an array of only three to twelve tin dioxide thick-film sensors, yet it can discriminate between alcohols, beverages, tobacco blends and coffees. Current efforts are reported towards the fabrication of an integrated microsensor metal oxide array, the development of other electronic devices using polymeric materials, and the implementation of various pattern-recognition techniques, including correlation, principal-component analysis, cluster analysis and artificial neural networks. Finally, the application areas most likely to arouse widespread interest in the next decade are discussed.
... Depending on the application of the system, different methods are used to construct the patterns and determine the degree of compatibility of both sets. However, an e-nose always consists of a set of sensors, consisting of several or several dozen elements, i.e., a multi-sensor matrix, an information processing unit, such as an artificial neural network (ANN), software with digital pattern recognition algorithms, and databases [53,54]. It is worth mentioning that these elements in commercial devices are mounted in easily replaceable modules, allowing the device to be adapted to the task performed. ...
... Table 1 below summarises the main advantages and disadvantages with a brief explanation. [19,21,43,47,53,56,65]. ...
E-nose and e-tongue are advanced technologies that allow for the fast and precise analysis of smells and flavours using special sensors. Both technologies are widely used, especially in the food industry, where they are implemented, e.g., for identifying ingredients and product quality, detecting contamination, and assessing their stability and shelf life. Therefore, the aim of this article is to provide a comprehensive review of the application of e-nose and e-tongue in various industries, focusing in particular on the use of these technologies in the fruit and vegetable juice industry. For this purpose, an analysis of research carried out worldwide over the last five years, concerning the possibility of using the considered multisensory systems to test the quality and taste and aroma profiles of juices is included. In addition, the review contains a brief characterization of these innovative devices through information such as their origin, mode of operation, types, advantages and disadvantages, challenges and perspectives, as well as the possibility of their applications in other industries besides the juice industry.
... Mass spectrometry (MS) also achieves high selectivity and, when combined with gas chromatography, is able to separate and data on its own. For this task, support vector machines or neural networks, similar to biological systems, are used [7]. An SVM attempts to find a hyperplane that best separates the data [16]. ...
... While PCA is useful for reducing the dimensionality of the data, it cannot be used to classify data on its own. For this task, support vector machines or neural networks, similar to biological systems, are used [7]. An SVM attempts to find a hyperplane that best separates the data [16]. ...
Volatile organic compounds (VOCs) are chemicals emitted by various groups, such as foods, bacteria, and plants. While there are specific pathways and biological features significantly related to such VOCs, detection of these is achieved mostly by human odor testing or high-end methods such as gas chromatography–mass spectrometry that can analyze the gaseous component. However, odor characterization can be quite helpful in the rapid classification of some samples in sufficient concentrations. Lower-cost metal-oxide gas sensors have the potential to allow the same type of detection with less training required. Here, we report a portable, battery-powered electronic nose system that utilizes multiple metal-oxide gas sensors and machine learning algorithms to detect and classify VOCs. An in-house circuit was designed with ten metal-oxide sensors and voltage dividers; an STM32 microcontroller was used for data acquisition with 12-bit analog-to-digital conversion. For classification of target samples, a supervised machine learning algorithm such as support vector machine (SVM) was applied to classify the VOCs based on the measurement results. The coefficient of variation (standard deviation divided by mean) of 8 of the 10 sensors stayed below 10%, indicating the excellent repeatability of these sensors. As a proof of concept, four different types of wine samples and three different oil samples were classified, and the training model reported 100% and 98% accuracy based on the confusion matrix analysis, respectively. When the trained model was challenged against new sets of data, sensitivity and specificity of 98.5% and 98.6% were achieved for the wine test and 96.3% and 93.3% for the oil test, respectively, when the SVM classifier was used. These results suggest that the metal-oxide sensors are suitable for usage in food authentication applications.
... As the sample enters the sensor array, it induces a reversible physical and/or chemical change in the sensing material, which causes an associated change in electrical properties, such as conductivity (Harsanyi, 2000) [13] . Each "cell" in the array can behave like a receptor by responding to different odors to varying degrees (Shurmer and Gardner, 1992) [32] . The electronic nose consists of three major parts which are detecting system, computing system and sample delivery system. ...
... As the sample enters the sensor array, it induces a reversible physical and/or chemical change in the sensing material, which causes an associated change in electrical properties, such as conductivity (Harsanyi, 2000) [13] . Each "cell" in the array can behave like a receptor by responding to different odors to varying degrees (Shurmer and Gardner, 1992) [32] . The electronic nose consists of three major parts which are detecting system, computing system and sample delivery system. ...
Earlier, for food testing, the sample was first digested and then subjected to analysis. These analytical methods are expensive, slow and often required the use of chemical reagents which are ultimately drained. To overcome these drawbacks, many emerging technologies of non-destructive techniques are applicable for analyzing the food products. The potential use of these technologies for measuring and monitoring the quality of dairy products has been evaluated by researchers. The techniques like near
infrared radiations, medium infrared radiations, electronic tongue, electronic nose, ultrasound and magnetic resonance may be used to envisage not only the chemical composition but also the quality of milk and the dairy foods. Some of these techniques can be used for on line monitoring and also for determining the structure. These techniques along with their applications in dairy industry have been presented in this paper.
... As the sample enters the sensor array, it induces a reversible physical and/or chemical change in the sensing material, which causes an associated change in electrical properties, such as conductivity (Harsanyi, 2000)[13]. Each " cell " in the array can behave like a receptor by responding to different odors to varying degrees (Shurmer and Gardner, 1992)[32]. The electronic nose consists of three major parts which are detecting system, computing system and sample delivery system. ...
... As the sample enters the sensor array, it induces a reversible physical and/or chemical change in the sensing material, which causes an associated change in electrical properties, such as conductivity (Harsanyi, 2000)[13]. Each " cell " in the array can behave like a receptor by responding to different odors to varying degrees (Shurmer and Gardner, 1992)[32]. The electronic nose consists of three major parts which are detecting system, computing system and sample delivery system. ...
Earlier, for food testing, the sample was first digested and then subjected to analysis. These analytical
methods are expensive, slow and often required the use of chemical reagents which are ultimately
drained. To overcome these drawbacks, many emerging technologies of non-destructive techniques are
applicable for analyzing the food products. The potential use of these technologies for measuring and
monitoring the quality of dairy products has been evaluated by researchers. The techniques like near
infrared radiations, medium infrared radiations, electronic tongue, electronic nose, ultrasound and
magnetic resonance may be used to envisage not only the chemical composition but also the quality of
milk and the dairy foods. Some of these techniques can be used for on line monitoring and also for
determining the structure. These techniques along with their applications in dairy industry have been
presented in this paper
... As the sample enters the sensor array, it induces a reversible physical and/or chemical change in the sensing material, which causes an associated change in electrical properties, such as conductivity (Harsanyi, 2000) [13] . Each "cell" in the array can behave like a receptor by responding to different odors to varying degrees (Shurmer and Gardner, 1992) [32] . The electronic nose consists of three major parts which are detecting system, computing system and sample delivery system. ...
... As the sample enters the sensor array, it induces a reversible physical and/or chemical change in the sensing material, which causes an associated change in electrical properties, such as conductivity (Harsanyi, 2000) [13] . Each "cell" in the array can behave like a receptor by responding to different odors to varying degrees (Shurmer and Gardner, 1992) [32] . The electronic nose consists of three major parts which are detecting system, computing system and sample delivery system. ...
Earlier, for food testing, the sample was first digested and then subjected to analysis. These analytical
methods are expensive, slow and often required the use of chemical reagents which are ultimately
drained. To overcome these drawbacks, many emerging technologies of non-destructive techniques are
applicable for analyzing the food products. The potential use of these technologies for measuring and
monitoring the quality of dairy products has been evaluated by researchers. The techniques like near
infrared radiations, medium infrared radiations, electronic tongue, electronic nose, ultrasound and
magnetic resonance may be used to envisage not only the chemical composition but also the quality of
milk and the dairy foods. Some of these techniques can be used for on line monitoring and also for
determining the structure. These techniques along with their applications in dairy industry have been
presented in this paper
... Another method for point-of-need analysis of VOCs is the electronic nose (E-Nose), which emerged in the late 1980s and rapidly flourished by capitalizing on the development and applications of artificial intelligence, digital micro-circuitry, electronic sensor design, software enhancements and computer systems integration [139]. The prototypical E-Nose is comprised of an array of sensors that are arranged within an electrical circuit and that differentially respond to individual VOCs. ...
Staphylococci are broadly adaptable and their ability to grow in unique environments has been widely established, but the most common and clinically relevant staphylococcal niche is the skin and mucous membranes of mammals and birds. S. aureus causes severe infections in mammalian tissues and organs, with high morbidities, mortalities, and treatment costs. S. epidermidis is an important human commensal but is also capable of deadly infections. Gold-standard diagnostic methods for staph infections currently rely upon retrieval and characterization of the infectious agent through various culture-based methods. Yet, obtaining a viable bacterial sample for in vitro identification of infection etiology remains a significant barrier in clinical diagnostics. The development of volatile organic compound (VOC) profiles for the detection and identification of pathogens is an area of intensive research, with significant efforts toward establishing breath tests for infections. This review describes the limitations of existing infection diagnostics, reviews the principles and advantages of VOC-based diagnostics, summarizes the analytical tools for VOC discovery and clinical detection, and highlights examples of how VOC biomarkers have been applied to diagnosing human and animal staph infections.
... Approximately a decade later, the first commercial E-nose has emerged (Gardner et al., 1994). The basic working principle of E-nose is based on the human olfactory system that consists of three main parts; (I) sample delivery part, (II) detection system and (III) computing system that can be learned, recognized and distinguished odors (Shurmer et al., 1990;Shurmer et al., 1992;Wongchoosuk et al., 2009). For the sample delivery part, the sample is injected into a clean air carrier to the instrument. ...
Agricultural cycle is the annual cycle of activities for planting and harvesting. The global warming and climate change currently cause serious impacts on the agricultural cycle leading to reduced crop quantity and quality. In the past decade, the gas sensors and electronic nose (E-nose) technologies have shown great promise and utility in monitoring and prediction of important parameters related to the growth and harvest of a crop. This review summarizes overall the evolution of utilizing gas sensors and E-nose technologies for guideline of agricultural best management practices including applications on cultivation preparation, crop production, harvesting and storage of crops. Advantages and limitations of these technologies in agricultural applications are reviewed to highlight potential research directions.
... Persaud and Dodd (1982) gave the idea of e-nose system for aroma discrimination using chemical sensors. According to Gardner 1991 andGardner andShurmer 1992, an e-nose typically consists of a mechanism for chemical detection such as an electronic multisensor array system, an information-processing unit, a digital pattern-recognition algorithm system that is capable of recognising odours, and a reference-library database. Since twentieth century, e-nose technique has undergone a great deal of development and it is preferred to routine laboratory analysis. ...
The food products may attract unscrupulous vendors to dilute it with inexpensive alternative food sources to achieve more profit. The risk of high value food adulteration with cheaper substitutes has reached an alarming stage in recent years. Commonly available detection methods for food adulteration are costly, time consuming and requires high degree of technical expertise. However, a rapid and suitable detection method for possible adulterant is being evolved to tackle the aforesaid issues. In recent years, electronic nose (e-nose) system is being evolved for falsification detection of food products with reliable and rapid way. E-nose has the ability to artificially perceive aroma and distinguish them. The use of chemometric analysis together with gas sensor arrays have shown to be a significant procedure for quality monitoring in food. E-nose techniques with numerous provisions are reliable and favourable for food industry in food fraud detection. In the present review, the contributions of gas sensor based e-nose system are discussed extensively with a view to ascertain the adulteration of food products.
... For E-nose systems, odorant molecules induce changes in the physical/chemical properties of the sensor arrays [130]. With appropriate interface circuits (voltage divider, Wheatstone bridge, Anderson loop circuitry), these changes are represented as analogue signals [131], then buffered, amplified, filtered, offset, linearized, and (temperature) compensated. ...
Instantly sensing the food quality attributes is a prerequisite to regulate the drying process for final product quality improvement. Novel sensing technologies have been “pushed” to food drying engineering from other research disciplines. Electronic nose, computer vision, hyperspectral imaging, near-infrared, nuclear magnetic resonance, and dielectric properties have been “transplanted” for this purpose. Various physicochemical attributes of food quality, including flavors, moisture contents, colors, shapes, texture, and chemical contents, have been sensed during the food drying process. Sun and solar drying, hot air convective drying, freeze drying, and microwave drying have been involved in these attempts. Numerous data processing and analysis techniques have been employed to make clear the meaning of multivariate variables for the above technologies. With the assistance of these technologies, a great diversity of drying processes have been modulated and food product quality had been improved. To promote their industrial application, more research is required to be conducted and more practical sensing method development is suggested along this direction.
... Stirring samples in headspace analysis represent the so-called Dynamic Headspace (DHS) method, which is observed in sample preparation techniques for electronic noses devices analysis [21,24,25], even presenting better performance for samples discrimination when compared to other techniques such as Static Headspace extraction [21]. Static Headspace (SHS) corresponds to the most common technique among electronic noses systems [21,26,27,28], mainly due to its simplicity [21], and provides favorable control when associated to vapor-flow injection [29,30]. ...
Wood barrel aging distilled beverages corresponds to a process capable of aggregate flavor compounds that may change sensory profiles and improve distillates quality. The analysis of the flavor compounds to determine degree of maturation of distillate relies most on costly techniques such as chromatography, so that more affordable and less laborious technologies may be suitable for wood-derived flavor determination in beverages, such as digital olfactometry. An electronic nose system reliability may take into consideration appropriate sample preparation method in order to obtain optimal performance over detection of odor compounds. An optimized pre-injection method was established for cachaça analysis in an electronic nose system after an experimental Rotational Central Composite Design, considering the sample preparation factors: incubation temperature, samples ethanol content, stirring period and equilibrium period. Raw data underwent the chemometric technique Multiple Co-inertia Analysis for feature extraction in prior to optimization design. The chemometric approach for data pre-treatment and analysis demonstrated favorable performance for electronic nose application. The optimal sample preparation included dilution of the aged distillate to lower ethanol content (10% v/v), sample incubation at 49 °C and excluded stirring and equilibrium stages, leading to a simpler and less time-consuming protocol.
... It relies on each sensor in the array being different and therefore its response to an odour being unique within the array. The pattern recognition software then learns the sensor responses associated with a specific odour source [11]. This operating principle attempts to mimic the function of biological olfactory receptors by detecting a complex pattern, instead of measuring the individual constituents of a mixture. ...
In this paper, we report on an in-house developed electronic nose (E-nose) for use with breath analysis. The unit consists of an array of 10 micro-electro-mechanical systems (MEMS) metal oxide (MOX) gas sensors produced by seven manufacturers. Breath sampling of end-tidal breath is achieved using a heated sample tube, capable of monitoring sampling-related parameters, such as carbon dioxide (CO2), humidity, and temperature. A simple mobile app was developed to receive real-time data from the device, using Wi-Fi communication. The system has been tested using chemical standards and exhaled breath samples from healthy volunteers, before and after taking a peppermint capsule. Results from chemical testing indicate that we can separate chemical standards (acetone, isopropanol and 1-propanol) and different concentrations of isobutylene. The analysis of exhaled breath samples demonstrate that we can distinguish between pre- and post-consumption of peppermint capsules; area under the curve (AUC): 0.81, sensitivity: 0.83 (0.59–0.96), specificity: 0.72 (0.47–0.90), p-value: <0.001. The functionality of the developed device has been demonstrated with the testing of chemical standards and a simplified breath study using peppermint capsules. It is our intention to deploy this system in a UK hospital in an upcoming breath research study.
... Each "cell" in the array can behave like a receptor which responds to different odors to varying degrees [8]. Figure 1 shows the sensing method of an e-nose. ...
The frequent usage of sensory modalities for Advanced Driver Assistance System (ADAS) and in some In-Vehicles Information System (IVIS) are only for visuals and hearing applications. Yet, the air quality inside the car is not usually monitored. Not to mention, the existing breath analyzers are used only by road traffic police enforcer randomly in examining the alcohol content in motorist's breath to avoid drunk driving related accidents. In this study, we proposed the development and utilization of an e-nose sensory module as an added feature for Controller Area Network (CAN) technology application. An electronic nose is characterized by its capability to intelligently sensed the gases present in the surrounding using an array of gas sensors with a pattern reorganization component. This e-nose comprises of a sensor array of five commercially available sensors (TG 2602, TG 822, TG 825, TG 813 and TG 880), a data acquisition interface, and a microprocessor. A software from the CAN module verified the system functionality. Experimental results indicate that the proposed system is able to identify the five different types of gases namely methane, ethanol, propone, isobutane, and hydrogen with high efficiency. Thus, it can be used as an added safety feature for vehicles.
... Each "cell" in the array can behave like a receptor which responds to different odors to varying degrees [8]. Figure 1 shows the sensing method of an e-nose. ...
The frequent usage of sensory modalities for Advanced Driver Assistance System (ADAS) and in some In-Vehicles Information System (IVIS) are only for visuals and hearing applications. Yet, the air quality inside the car is not usually monitored. Not to mention, the existing breath analyzers are used only by road traffic police enforcer randomly in examining the alcohol content in motorist's breath to avoid drunk driving related accidents. In this study, we proposed the development and utilization of an e-nose sensory module as an added feature for Controller Area Network (CAN) technology application. An electronic nose is characterized by its capability to intelligently sensed the gases present in the surrounding using an array of gas sensors with a pattern reorganization component. This e-nose comprises of a sensor array of five commercially available sensors (TG 2602, TG 822, TG 825, TG 813 and TG 880), a data acquisition interface, and a microprocessor. A software from the CAN module verified the system functionality. Experimental results indicate that the proposed system is able to identify the five different types of gases namely methane, ethanol, propone, isobutane, and hydrogen with high efficiency. Thus, it can be used as an added safety feature for vehicles.
... The recent work on the design of the breathalyzers has mostly focused on the design of an array of similar sensors and complex signal processing algorithms [7][8][9]. This approach stems from the E-nose technology that had been mostly focused on the classification of odors [10][11][12]. The major drawback of this approach is that most types of gas sensors, including the metal-oxide sensor, suffer from drift in the response and with an array of sensors along with the complex supervised signal processing the calibration of these devices over the longer period of time becomes cumbersome. ...
A single exhale breathalyzer comprises a gas sensor that satisfies the following stringent conditions: high sensitivity to the target gas, high selectivity, stable response over extended period of time and fast response. Breathalyzer implementation includes a front-end circuit matching the sensitivity of the sensor that provides the readout of the sensor signal. We present here the characterization study of the response stability and response time of a selective Nitric Oxide (NO) sensor using designed data acquisition system that also serves as a foundation for the design of wireless handheld prototype. The experimental results with the described sensor and data acquisition system demonstrate stable response to NO concentration of 200 ppb over the period of two weeks. The experiments with different injection and retraction times of the sensor exposure to constant NO concentration show a fast response time of the sensor (on the order of 15 s) and the adequate recovery time (on the order of 3 min) demonstrating suitability for the single exhale breathalyzer.
... Electronic noses (EN) are intelligent chemical sensor array systems, typically consisting of two major components: (a) a single chemical gas sensor or an array of chemical sensing systems and (b) a pattern recognition system. 4 The functional principles of EN are relatively simple. 6 During operation, every single chemical odorous component presented to the EN sensor system produces a response (e.g., a change in electrical properties) which can be identified as the characteristic odor signature for the examined scent. ...
Border control for homeland security faces major challenges worldwide due to chemical threats from national and/or international terrorism as well as organized crime. A wide range of technologies and systems with threat detection and monitoring capabilities has emerged to identify the chemical footprint associated with these illegal activities. This review paper investigates artificial sniffing technologies used as chemical sensors for point-of-use chemical analysis, especially during border security applications. This article presents an overview of (a) the existing available technologies reported in the scientific literature for threat screening, (b) commercially available, portable (hand-held and stand-off) chemical detection systems, and (c) their underlying functional and operational principles. Emphasis is given to technologies that have been developed for in-field security operations, but laboratory developed techniques are also summarized as emerging technologies. The chemical analytes of interest in this review are (a) volatile organic compounds (VOCs) associated with security applications (e.g., illegal, hazardous, and terrorist events), (b) chemical "signatures" associated with human presence, and
... The swelling action is caused by adsorption producing forces and/or mechanical displacements and changes in resistivity. Polymer swelling phenomena has been studied extensively for chemoresistance based electronic noses [6][7] and ultra-sensitive vapor sensing [4][5] with ppb and ppt detection limits of explosives and organic vapors. However the deflection for ppb and ppt level detection is as small as few nanometers. ...
... Electronic noses are imitated living creatures' olfactory systems to differentiate among odors and volatile compounds by use of different sensor series and pattern recognition techniques. Electronic nose studies have been started at Warwick University at England [1]. In the last few decades, there have been various researches done to improve the hardware and software of electronic noses'. ...
Identification of more than three perfumes is very difficult for the human nose. It is also a problem to recognize patterns of perfume odor with an electronic nose that has multiple sensors. For this reason, a new hybrid classifier has been presented to identify type of perfume from a closely similar data set of 20 different odors of perfumes. The structure of this hybrid technique is the combination of unsupervised fuzzy clustering c-mean (FCM) and supervised support vector machine (SVM). On the other hand this proposed soft computing technique was compared with the other well-known learning algorithms. The results show that the proposed hybrid algorithm’s accuracy is 97.5% better than the others.
... Because Liquor is formed from many single gases, so liquor more complex than a single gas. H. V. Shurmer and J. W. Gardner [1][2][3][4] used 12 kinds of metal sensors on five kinds of liquor were classified, and achieved better results. In this paper, multisensor array and information fusion technology are combined. ...
Electronic nose (EN) is a equipment with ability of identification of simple or complex odors. Because of its low cost and accurate identification rate, the researches of it attract more attention and it develops quickly. Firstly, through Gas Sensor Array, we get large amount sample data and all data which is preprocessed. Secondly, modified Bp algorithm and RBF algorithm combining nearest neighbor - clustering algorithm and K-means clustering algorithm is proposed to realize the identification. Principal component analysis (PCA) method wipes off redundant sensor from the sensor array. Principle components and brief sensor signals are tested by above two algorithms. The test result indicated that the rapid and exact identification measure of ANN combining PCA is provided to the pattern identification with sensor information fusion.
Based on their construction or working principles, biosensors, biomimetic sensors, and bioapplicable sensors may have been understood differently, but everyone acknowledges their commonality of sensing in fields that require knowledge of biochemical science and engineering. In the era of big data and industry 4.0, the amalgamation of artificial intelligence (AI) technology and the Internet of Things (IoT) with the applied science of sensing is seen as a way forward to achieve unprecedented growth in the design and development of novel and robust biochemistry-related sensors. The integration of AI with sensing technology makes it possible to produce sensors that can rapidly detect targets while maintaining high sensitivity, accuracy, and precision, all at a cost-effective price point. This work reviews recent literature on the applications of AI tools to accelerate the advancement of intelligent biosensors. Also, it projects how novel AI tools such as digital twins, machine vision, robotics, natural language processing, and text mining will transform the design and broaden the applicability of biosensors, bio-inspired sensors, and bioapplicable sensors.
Son yıllarda gıdaların kalite özelliklerinin belirlenmesinde hızlı ve ekonomik teknikler geliştirilmesine yönelik çalışmalara artan ilgi nedeniyle, elektronik burun sistemlerine olan talep artmış ve bu sistemler hızlı teknikler arasında yerini almıştır. İnsan koku alma mekanizmasını taklit eden elektronik burun sistemlerinde farklı teknolojiler için farklı tiplerde tasarlanmış gaz sensörleri bulunmaktadır. Bu sensörlerden iletkenlik ölçümüne dayalı metal oksit yarı iletken gaz sensörleri (MOS) hızlı tepki vermesi, ucuz, sağlam ve portatif olmaları nedeniyle tıp, kimya, ziraat ile gıda sektöründe geniş kullanım alanı bulmuştur. Gıdaların kalitesi, raf ömrü, depolanması, mikrobiyal kontaminasyonu, bozulması, tağşişi ve sınıflandırılması elektronik burun teknolojisi yoluyla yürütülen çalışmalar arasındadır. Elektronik burun metal oksit yarı iletken gaz sensörleri, mevcut gıda analizlerine bir alternatif oluşturmuş ve sonuçları doğrulama olanağı sağlamıştır. Bu derlemede elektronik burun metal oksit yarı iletken sensörleri ve özellikle gıda analizlerinde bu sensörlerin yardımıyla gerçekleştirilen bilimsel çalışmaların özetlenmesi amaçlanmıştır.
This chapter contains sections titled: Methods for Validation Medical Applications Fire Detectors Pipeline Inspection Sensing Arrays with Colloidal Particles Nanodisk Sensor Arrays Food Testing Soil Volatile Fingerprints Methods for Validation Medical Applications Fire Detectors Pipeline Inspection Sensing Arrays with Colloidal Particles Nanodisk Sensor Arrays Food Testing Soil Volatile Fingerprints
Volatile organic compounds (VOCs) are pervasive in the environment and their real-time continuous monitoring can facilitate better understanding of their effects on human health by combining environmental factors with physiological conditions. The scope of wearable sensors for detection of VOCs is evident as the accuracy of the sensor prediction depends on its proximity to the VOC source along with the sensitivity and selectivity of the sensor itself. In this paper, we present a low-power wearable e-nose system based on a capacitive micromachined ultrasonic transducer (CMUT) array. CMUTs offer inherent benefits of excellent mass resolution, easy array fabrication, and integration with electronics, which make them an appropriate choice as a transducer element for gravimetric e-nose systems. A 5-channel CMUT sensor array was chemically functionalized and used for the detection of four volatiles, ethanol, toluene, p-xylene, and styrene. All the channels of the sensor array achieved a resolution below 10 ppm within 0.2–3% of OSHA-PEL time-weighted average (TWA) for each volatile. For each test cycle, the maximum frequency shift, the rate of adsorption, and the rate of desorption were extracted as features. Linear discriminant analysis (LDA) was applied to visualize the discrimination performance of the sensor array. The system performance was characterized using an automated testing system. The presented sensor system can be used for identification of volatiles with suitable pattern-recognition techniques.
Towards implementing a portable and low power hand‐held gas sensing system, this chapter targets the design of integrated electronic signal conditioning circuits also known as integrated electronic readout circuits. It first reports a study of the available gas sensing technologies focusing on the advantages and limitations of each, then metal oxide (MOX)‐based gas sensors are introduced as a sensing technology for portable handheld gas detection used for environmental monitoring. Next, the principle of operation of such sensors is addressed. The chapter provides the characterization to define the specifications of the electronic integrated readout circuit. It discusses the requirements of each block at transistor level design. Thereafter, a state‐of‐the‐art study is provided to introduce the MOX gas sensor electronic interface circuits available in literature. The chapter also addresses the efforts done in terms of power consumption reduction for portable mobile applications.
Gas sensor array & pattern recognition is the most promising method to improve the anti-interference performance of metal oxide gas sensor. How to choose the initial gas sensor array is very important in gas sensor array optimization. In this paper, an initial array optimization method based on combinatorial and high-throughput (CHT) method is proposed. In
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-based gas sensing film with Ho, Ir, Ru, Mn, V and Mo surface modification were screened out with good cross-selectivity to different VOCs. All the results in this work form a comprehensive and detailed database, providing a reference for choosing the initial gas sensor array.
Gas sensor arrays, also called electronic noses, use many chemically diverse materials to adsorb and subsequently identify gas species in complex mixture environments. Ideally these materials should have maximally complementary adsorption profiles to achieve the best sensing performance, but in practice they are selected by trial-and-error and thus current electronic noses do not achieve optimal detection. In this work, we employ metal-organic frameworks (MOFs) as sensing materials and leverage a genetic algorithm to identify optimal combinations of them for detecting methane leaks in air. We build on our previously reported computational design methodology, which ranked MOF arrays by their Kullback-Liebler divergence (KLD) values for probabilistically describing the concentrations of each gas species in an unknown mixture. We ran the genetic algorithm to find optimal MOF arrays of various sizes when selecting from a library of fifty different MOF materials. The genetic algorithm was able to accurately predict the best arrays of any desired size when compared to brute-force screening. Thus, this search optimization can be integrated into the efficient design of MOF-based electronic noses.
Electronic noses mimic smell and taste senses by using sensor arrays to assess complex samples and to simultaneously detect multiple analytes. In most cases, the sensors forming such arrays are not highly selective. Selectivity is attained by pattern recognition/chemometric data treatment of the response pattern. However, especially when aiming at quantifying analytes rather than qualitatively detecting them, it makes sense to implement chemical recognition via receptor layers, leading to increased selectivity of individual sensors. This review focuses on existing sensor arrays developed based on biomimetic approaches to maximize chemical selectivity. Such sensor arrays for instance use molecularly imprint polymers (MIPs) in both e-noses and e-tongues, for example, to characterize headspace gas compositions or to detect protein profiles. Other array types employ entire cells, proteins, and peptides, as well as aptamers, respectively, in multisensor systems. There are two main reasons for combining chemoselectivity and chemometrics: First, this combined approach increases the analytical quality of quantitative data. Second, the approach helps in gaining a deeper understanding of the olfactory processes in nature.
Gas sensing techniques are often required to not only be sensitive and portable, but also to be able to identify gases. In this paper, we describe and demonstrate a new gases identification approach based on noise spectroscopy. By using the model of the gas sensor noise developed in our previous work, we calculate the exact theoretical expression of the first derivative of the power spectral density (PSD) of the gas sensor noise, and we show that there is a correlation between this expression and the nature of the detected gas. This theoretical result is argued by some experimental results performed on metal oxide (MOX) gas sensor exposed to various gases. The new principle holds prospects for finding powerful method for identification of gases.
The global confectionary market was valued at $184 billion in 2015, and is projected to reach $232 billion by 2022. The industry directly employs 55,000 people domestically, and more than 400,000 jobs in agriculture, retail, transportation and other industries rely in part on the sale and manufacture of confections. However, many available analytical methods for measuring the quality of confections are relatively expensive, time consuming, and difficult to operate or maintain, therefore, it is unrealistic for small/medium confection manufacturers to use those methods. The objective of this study was to develop fast-measuring and affordable analytical methods for some important quality related properties. In addition, the developed methods were used to study the properties of confections and compare them with traditional methods, seeking their potential applications in confection quality assurance for small/medium confection manufacturers and other researchers. Two capacitance-based thermal analysis (CTA) methods were developed to study the glass transition and melting properties of different boiled candies and chocolates respectively. Three particle size measurement methods were tested for characterizing cocoa particle size distribution in the refining/conching process. The microstructure of cocoa particles was also studied by scanning electron microscopy (SEM). Flavor development and volatile compounds profiles of cocoa during roasting and refining/conching processes were studied by electronic nose. The results provide better understandings about quality related properties, such as glass transition, melting, and particle size, of confection by using non-traditional methods. The potential applications of fast-measuring and affordable analytical methods were tested and several of the methods were proved to be useful for small/medium confection manufacturers.
Les systèmes multicapteurs de gaz intelligents connaissent actuellement un développement accru pour de nombreux domaines d'application. Inscrite dans le large domaine de la lutte contre la pollution atmosphérique, notre étude a pour but principal la détection de deux gaz polluants antagonistes le sulfure d'hydrogène H2S, réducteur, et le dioxyde d'azote, NO2, oxydant. Après avoir situé ce sujet dans le cadre de la pollution atmosphérique, puis présenté le principe des nez électroniques, nous justifions notre choix d'une matrice de capteurs à base d'oxyde métallique, et mettons en évidence les avantages et inconvénients de ces capteurs. L'inconvénient majeur est leur sensibilité croisée, qui peut devenir un avantage par l'utilisation de méthodes de reconnaissance de formes. Les deux gaz sont étudiés seuls ou en mélange, successivement dans trois atmosphères, de plus en plus complexes. Les concentrations étudiées correspondent à une pollution industrielle près d'une source émissive. De chaque réponse des capteurs obtenue lors de la procédure systématique de caractérisation, nous avons extrait trois variables représentatives communes à toutes les mesures et une quatrième correspondant à un "pic" négatif spécifique de la réponse de tous les capteurs à H2S, non utilisé dans l'analyse de données, car il n'apparaît pas toujours dans les mélanges. Nous avons construit une base de données d'apprentissage de notre système (environ 1000 mesures) étudiée à l'aide de l'analyse factorielle discriminante, méthode multidimensionnelle supervisée. Nous obtenons identification et quantification des atmosphères gazeuses, en procédant par étapes qui tiennent compte notamment des atmosphères de références. Une identification rapide est obtenue avec deux variables représentatives, valable pour la détection d'un seuil. Grâce aux règles de décision fiables obtenues, nous proposons une méthode d'identification d'atmosphères inconnues directement exploitable par des utilisateurs
This chapter describes and updates the development, design, and potential of conductive polymer nanocomposites (CPCs) for the design of smart materials. CPCs are obtained by structuring a network of conductive nanofillers (carbon or metallic) into an insulating polymer matrix. These hybrid materials offer original properties such as chemo-, piezo-, or thermo-sensitivity that allow implementation of smart functionalities into materials allowing to target promising applications such as structural health monitoring or anticipated diagnosis of diseases. Nevertheless, to synthesize CPC with reliable, durable, and reproducible characteristics, it is necessary to pay attention to the construction steps of the 3D conducting architectures, to their formulation, and to their characterization at different scales of observation from the nano- to the microscale.
The main objective of our proposed system is to safe guard people's life and government property. This paper will focus on the system that will detect and control the fire accidents on running train. In-house parameters such as temperature and humidity in the each coach can be monitored in real time. From the information collected by the sensor system, decisions for firefighting, alarming, and automatic water sprinkler system can be made more quickly by the relevant system or engine driver. After receiving the signal, the engine driver will stop the train and take necessary action.
Odour sensor arrays produce multidimensional patterns of data that may be used as ‘fingerprints’ to differentiate between different volatile chemicals or mixtures of chemicals. A problem that arises for the human observer, is how to visualise multidimensional data in order to determine whether a certain pattern is similar or different from known patterns. A requirement is to reduce multidimensional data to two or three dimensions, and project unknown patterns on to the resulting map in real time, allowing the observer to make judgements on the incoming data. The SAMMAN network was adopted, but modified by the use of a previously trained neural network encoding principal component analysis to provide weights used to initialise the SAMMAN network. This provided a robust system that was invariant to changes in the order of the data set, and allowed rapid projection of unknown data on to a Sammon map.
The need to selectively recognize and complex ions and molecules is common in many areas of science and industry. Nature’s ability to selectively detect or sense specific compounds in a variety of ways and under many different conditions has long been the source of inspiration in the application and development of recognition-based chemistry. Biofunctional membranes present one such example where polymeric membranes can be designed with a desired function by using or mimicking natural chemical recognition systems. The components found in living organisms that have selective recognition features (i.e., proteins, enzymes, membrane systems, sensory neurons, etc.) have been the subject of much intense study. The rapid, selective, and sensitive response of natural sensory systems that employ recognition chemistry can serve as a model in the development of biosensors. This includes mimicking natural receptors,1 antibiotics,2,3 and even olfactory membranes4 to accomplish desired tasks. One group has successfully immobilized double-helical DNA directly onto an electrode surface and obtained a biosensor that responded selectively to DNA-binding substances (via intercalation) as well as to magnesium ion.5 The applications which await the development of novel biosensors cover a wide range of disciplines, including environmental, medical, industrial, and other venues of research.
The development of chemically diverse arrays has gained the attention of researchers due to their anticipated capacity to mimic the function of olfactory receptors in the mammalian olfactory system. A major hurdle facing the field is the limited ability to generate large numbers of different sensing elements out of the relatively limited number of conducting polymers. In this work, chemically distinct electrocopolymerized sensors were created with pyrrole by using different substituted vinyl groups (e.g., styrene, m-styrene, 4-chlorostyrene, 4-chloromethylstyrene, 4-t-butylstyrene, 4-t-butoxystyrene, divinyl benzene and vinyl pyridine) as monomers. Copolymer films were grown at different potentials that created an additional level of sensor diversity by altering the relative amount of each of the components. By controlling the deposition conditions in this way, as well as setting different redox potentials to the films after growth changes the copolymer's composition and the amount of dopant anion that is incorporated into the sensing films respectively. The composition of the sensing films was also altered by changing the dopant-type during copolymer growth, thereby providing another mechanism for varying the chemical nature of the sensing materials. The chemical diversity among the 27 different sensing polymers used in this work is demonstrated with differential partitioning of 12 analytes, ranging from alcohols and solvents to fuels. This process of generating significant numbers of chemically distinct sensors represents a significant advancement in the efforts to approach the number of olfactory receptors in mammals. The fact that the sensing polymers can be electropolymerized onto very small conducting contacting electrodes shows that this approach is compatible with integrated circuit technology.
The biological components of vertebrate and invertebrate chemical sensing systems are now becoming well understood in terms of their structure and function. As a result, it is now possible to consider biomimetic models of olfaction and how they may be translated into functional engineering devices. This chapter outlines some of the development in sensor array technology that can enable functional devices. The responses of individual odor sensors com bined into an array, where each sensor possesses slightly different response selectivity and sensitivity toward the sample odors, when combined by suit able mathematical methods, can provide information to discriminate between many sample odors. Arrays of gas and odor sensors, made using different technologies, have become known as electronic noses and consist of three elements: A sensor array that is exposed to the volatiles, conversion of the sensor signals to a readable format, and software analysis of the data to produce characteristic outputs related to the odor encountered. The output from the sensor array may be interpreted via a variety of methods-such as pattern recognition algorithms, principal component analysis, discriminant function analysis, cluster analysis, and artificial neural networks-to discriminate between samples. This chapter introduces some of the more biologically oriented algorithms that may transform traditional multivariate data analysis, feature extraction, and pattern recognition.
Taking advantage of the analogy with olfaction sensation analyser in human brain, principle of operation of the growing group of devices called "electronic noses" is presented. Types of sensors most often applied are discussed. Various methods of processing information derived from the sensor array response to complex chemical stimulus are presented using the knowledge about principle of brainwork.
The origin of salting, originally used to preserve meat products in general, is lost in ancient time. However, Catón, in “De Re Agricola,” described several salted-meat recipes that today are still being used in several Mediterranean areas (Pineda, 1989). With today’s widespread availability and use of refrigeration, salting of meat for preservation has become of less importance. Today, salting has been modified and improved to dry-curing wherein additives and adjuncts such as nitrates and ascorbic acid are added to the salt; furthermore, processing time is for a long periods to permit optimal maturation and flavor development (Flores and Toldrá, 1993).
Twelve moist foods for cats were characterised using different analytical methods (sensory analysis, gas chromatography (GC) coupled with a mass spectrometer, texture and gas sensor measurements) and the links between the different data sets and cat preferences were analysed. Gas sensor measurements were reliable, discriminating and non-correlated with the water activity of the products. Multiple Factor Analysis described the relations between the different data sets while GC and sensory data helped to give a better understanding of the reasons for preferences. Although gas sensor data gave a representation of the products quite similar to that obtained with palatability results, these data gave less rich information on product sensory characteristics than the other types of data. Partial Least Squares regression produced predictive models and revealed quantitative links between data sets. The various data sets give complementary information which facilitate the prediction of palatability. In particular, some palatability parameters were predicted through the responses of certain gas sensors and texture measurements. Even if sensory data give better predictions, gas sensor and texture measurements have the advantage of being rapid.
We have developed the system called an odor recorder for reproducing the smell recorded using the odor sensing system. The recipe of the odor, where the sensor-array output pattern of a target odor matches that of an internally blended odor using multi-input multi-output (MIMO) feedback control, is recorded. It can be reproduced using an odor blender. The odor recorder has the capability of dynamic change in the odor in addition to the ability of recording the static recipe of the odor. Here, several techniques such as a neural network with feedback error learning, the real-time reference method and its modified technique for speeding up are described. The experiments revealed that the real-time reference method had the robustness against the environmental change. Moreover, the recording of the dynamic change of the odor over a few seconds was successfully performed using that method.
We developed a fragrance and flavor analyzer system that overcomes the drawback of electronic noses using metal-oxide semiconductors, i.e., the nonlinearity of their outputs with respect to the concentration of samples. This was realized by installing a dilution and mixing apparatus and a concentrating system before fragrance and flavor analyses as pretreatment systems, applying feedback to the sensor outputs for each measurement, and adjusting the lengths of vectors comprising the multiple sensor outputs to a certain value in the range where the sensor outputs are relatively linear. When the lengths of the vectors comprising the multiple sensor outputs are adjusted to a certain value for each measurement, the type of odor can be evaluated using the vector direction. The intensity of the odor is calculated from the dilution or concentration rate required to adjust the vector length to a certain value. By modifying this method, we also developed a technique of odor deviation mapping to quantitatively display changes in the type of odor. In odor deviation mapping, a reference odor and one or two odor deviations, which indicate the deviations from the reference odor, are selected while their vector lengths are being adjusted. Deviation axes are prepared on a map using vectors comprising sensor outputs obtained by adding each odor deviation to the reference odor, and the deviations of odors from the reference odor are quantitatively visualized on the map. As examples, applications of the map to the determination of expiration dates of foods and the identification of substances causing unusual odors are also discussed in this paper.
Conducting polymer nanowires of poly(3, 4-ethylene dioxythiophene) (PEDOT) was firstly prepared by an simple wetting anodic aluminium oxide template (AAO) method. The AAO template was wetted by PEDOT polymer solution and the conducting polymer nanowires was formed into the hole of template. The formed PEDOT nanowires was characterized by UV-vis-near IR (UV-vis-NIR) absorption spectrum, and the result showed that the nanowires was in a doped state. The size of obtained nanowires was larger than the size of AAO template pore, which resulted from a swelling effect of polymer after removing AAO template. Conductivity investigation showed that nanowires had higher conductivity than conventional bulk PEDOT materials and exhibited excellent doping/dedoping characteristic. For the sensitive characteristics study, the PEDOT nanowires showed faster response to different analyte gas, such as methanol and ethanol, and especially showed excellent gas sensitivity to methanol gas. It has been found that at 5ppm methanol concentration, the nanowires exhibits short response time about 10-20 s and the reproducible gas sensitivity can be achieved more than 20 times at same testing condition. This excellent gas sensitivity of PEDOT nanowires was ascribe to the higher surface area ratio of nanowires and ordered PEDOT conductive channel in nanowires, which supply well condition for analyte gas to diffuse into and out from the nanowires.
The human sense of smell is the faculty upon which many industries rely to monitor items such as beverages, food and perfumes. Previous work has been carried out to construct an instrument that mimics the remarkable capabilities of the human olfactory system. The instrument or electronic nose consists of a computer-controlled multi-sensor array which exhibits a differential response to a range of vapours and odours. The authors report on a novel application of artificial neural networks (ANNS) to the processing of data gathered from the integrated sensor array or electronic nose. This technique offers several advantages, such as adaptability, fault tolerance, and potential for hardware implementation over conventional data processing techniques. Results of the classification of the signal spectra measured from several alcohols are reported and they show considerable promise for the future application of ANNS within the field of sensor array processing.
Phospholipid accounted for 81% (by weight) of the total lipid of rat olfactory mucosa. Phosphatidylcholine (46% of total phospholipids) and phosphatidylethanolamine (26%) were the predominant phospholipids. Phosphatidylinositol (8%), sphingomyelin (6%), and phosphatidylserine (7%) were the next most abundant phospholipids, with cardiolipin (4%) and phosphatidic acid (1%) present in lesser amounts. Only trace amounts of the polyphosphoinositides, phosphatidylinositol monophosphate, and phosphatidylinositol bisphosphate were detected. Sterol was the major neutral lipid present (83% of the total neutral lipid mass) with lesser amounts of triacylglycerols (7%), steryl esters (6%), free fatty acids (4%), and diacylglycerols (1%). Monoacylglycerols were detected only in trace amounts. The sterol to phospholipid ratio was 0.39:1. Most of the phospholipids of the olfactory mucosa showed a high polyunsaturated fatty acid content, with the arachidonic acid (20:4) and docosahexaenoic acid (22:6) residues predominating. The fatty acids in sphingomyelin, however, were almost totally saturated and included the 24:0 and 24:1 residues, which were not detected in other phospholipids. Polyunsaturated fatty acids accounted for less than 25% of the total fatty acid of any individual neutral lipid and comprised largely linoleic and arachidonic acids. The results are discussed in relation to the putative role of lipids in olfactory signal transduction.
Sensors utilizing the conductivity change of oxide semiconductor elements are classified into surface-sensitive type and bulk-sensitive type. The surface-sensitive type, represented by the SnO//2 sensors widely used as detectors for combustible gas leakage, is characterized by low operating temperature and pronounced effects of temperature and sensitizer. Taking the detection of H//2 by an SnO//2 sensor as an example, the adsorption and interactions of O//2 , H//2 O and H//2 on SnO//2 surface are described. The results are consistent with a gas sensing model in which combustible gases consume absorbed oxygen, O-. Sensitization effects are also described and two mechanisms, chemical and electronic, are proposed.
The temperature dependence of resistivities of gas sensors made of SnO2, Pd-doped SnO2, and ThO2-doped SnO2 with Pd has been investigated in air containing reducing gases such as CO, H2, and C3H8. The curves for ThO2-doped sensors were significantly influenced by the reducing gases as compared to the sensors without ThO2. From these results, it is found that in Pd-doped SnO2 sensors the dopant plays an important role in oxidizing the surface of SnO2 above 170°C, and that the addition of ThO2 to Pd-doped SnO2 enhances the effects of Pd by removing the adsorbed hydroxyl on SnO2. It is also apparent that the interactions between reducing gases in air and SnO2-based sensors depend upon the oxidizing rates of the surface of SnO2, as well as the amounts of the adsorbed hydroxyl on SnO2.
Langmuir-Blodgett (LB) multilayer films of ω-tricosenoic acid (ωTA) have been deposited onto freshly-etched silicon to prevent the formation of the natural passivating oxide layer. Pd-gate devices formed on this structure have been investigated by C-V and G-V methods, and it has been shown that the number of impurity states at the silicon surface is increased by this treatment. Furthermore, the sensitivity to hydrogen gas of these states is greatly improved.
This paper describes a gas sensor system that delivers a set of signals for each gas applied. This signal spectrum can be evaluated by means of pattern recognition in order to identify the gas and measure its concentration.This sensor principles is demonstrated by means of a set of four MOS gas sensors with layers of different types of zeolite filters. The experimental results demonstrate the feasibility of this concept. Advantages and disadvantages are discussed.
An experimental multisensor system has been used to provide an early unambiguous indication of a fire or heating in a mine by monitoring the gaseous products evolved. The system could distinguish between the gases evolved from a fire and those evolved from diesel engines or from explosives. The methane and total flammable gas content were also measured. Six sensors of three different types in combination with oxidizing layers and absorbent traps were used. Sensors based on electrical conductivity changes in lead phthalocyanine were used to provide a measure of NO2 and NOx. Sensors based on conductivity changes in single crystals of ZnO were used to indicate CO and total products of combustion/heating, and catalytic sensors were used to measure the CH4 and the total flammable gas levels. The system has been used on a sampling system at the surface of a mine.The potential of multisensor systems for unambiguous indications of a hazardous situation has been demonstrated. The problems associated with setting up a more complex system that would automatically indicate the presence of a hazard on the basis of a combination of sensor responses are briefly discussed.
A simpler integrated hydrogen leak detector has been fabricated, which consists of a Pd-Si tunnel MIS diode for the hydrogen sensor, a diffused resistor layer for the inside heater and a p-n junction diode for temperature control. Measurements were carried out on the response characteristics to hydrogen at different device temperatures and hydrogen concentrations. The results show that the newly fabricated detector can be used as a practical detector for small leakage of hydrogen at a device temperature between 100 and 120 °C. It is also demonstrated that the tunnel MIS diode with a hole-structure Pd layer drastically improves the hydrogen sensitivity.
The design characteristics of lower-power platinum gas sensors are studied. These sensors work by the detection of the positive ions produced during the catalytic oxidation of organic vapours on hot platinum wires and ribbons. These sensors are selective to long-chain hydrocarbons. A prototype sensor design is presented, which uses a small piece of platinum ribbon welded to a ceramic header with a wire mesh cathode to collect the positive ions. The ionic current is measured with a battery-run picoammeter circuit biased to float at −120 V. The ribbon is heated resistively with a standad power supply. At the operating temperature of 800 °C, the power consumption is about 2 W. The prototype is capable of detecting iso-octane vapour down to a concentration of 2 ppm. Platinum ribbon was used rather than wire as the wire had a greater tendency to melt due to thermal runaway in the resistive heating process. It was observed that the number of positive ions produced by the catalytic process decreased during long-term measurements. Scanning electron micrographs showed this to be due to facetting of the platinum surface. A few seconds' exposure at 1300 °C restored the surface and the ionic response. Thus periodic thermal cycling is necessary for the prototype sensor.
An approach to an integrated semiconductor gas sensor is presented. The major reasons considered for developing a semiconductor oxide gas sensor on silicon are the accurate local temperature control of the sensing area and the low level of the heating power required, together with an appropriate integrated structure. Thermal loss measurements show that the integrated gas sensor can operate up to 400 °C with less than 200 mW heating power. Depending on the deposition conditions, catalyst addition or surface conditioning, the SnOx thin films are known to have an optimal sensitivity to CO between 250 °C and 400 °C. The sensitivity for CO gas and the response time of the device are presented for sputtered thin films of SnOx, deposited on top of an isolated resistive heater, separated from silicon by a thin thermally-isolating membrane.
A multisensor system has been developed that is capable of discriminating between complex vapours or gaseous mixtures. The system is based on an array of 12 discrete tin oxide semi-conductor sensing elements, each possessing different characteristics whilst being sensitive to a broad spectrum of gases. A weighted fault-tolerant least-squares method is used to analyse the multisensor data. Results show the multisensor system successfully discriminates (100%) between methanol, ethanol, propan-2-ol and butan-1-ol. Its overall ability to distinguish between beverages and spirits or mixtures is somewhat lower (83%) underpinning a need in this case for complementary sensing materials.
This paper relates to a system comprising an array of highly discriminating gas sensors linked to a microcomputer for information processing and display, mimicking a mammalian olfactory system and hence meriting the description electronic nose. By providing a unitary response to a complex gas mixture, it offers a particularly attractive way of identifying or finger-printing odours, and it can alternatively provide a means for gas analysis. We consider here various constraints on what is achievable in relation to present technologies, especially in the field of sensing devices and in information processing.
This paper describes the design and fabrication of an integrated array of tin oxide odour sensors using planar micro-electronic silicon technology. Some fundamental properties of the device structure are discussed, including power consumption, along with its response to several odours. In addition, the sensing element is modelled as a pair of finite coplanar electrodes lying upon a thin oxide layer, and an analytical conductance equation obtained that relates its conductance to electrode geometry in a diffusion-limited model. The physical conditions that require the use of a diffusion or reaction model are discussed.
After a brief introduction to the mechanisms involved in semiconductor gas sensors, questions of linearity and superposition are considered for mixtures of gases. It is established that Taguchi gas sensors (TGS) can provide a good approximation to a linear model and that superposition principles apply under certain conditions. This greatly facilitates the analysis of data and the identification of constituent components in a mixture of gases. Innovative techniques have been applied to alcohols and tobaccos with conspicuous success. These relate to pattern recognition and cluster separation, using simple mathematical procedures to enhance the identification of closely similar batches of test samples. It is confidently expected that many other applications for these methods will arise.
Pd-MOS structures with holes in the gate metal have been prepared for detecting arsine, and investigated in a flow system. The samples show a reversible decrease of threshold voltage on admixtures of arsine to an air stream (temperature range 350 K to 470 K). A change of threshold voltage of 34 mV is found for 0.1 ppm arsine in air (T = 433 K). For arsine concentrations of 2.5 ppm, a response time of 40 s and a recovery time of 300 s are observed at 450 K. The response of the same structures to small concentrations of H2 has also been investigated. Sensitivity and response are comparable to the results found for arsine. This similarity points to a decomposition of arsine at the Pd surface, with subsequent diffusion of hydrogen to the metal-oxide interface.
Although the identification of various kinds of odors in our daily life is important, few artificial odor sensing systems have been reported. From the biomimetic point of view, the use of plural sensors to recognize the output pattern of a sensor array for such identification is very promising. An odor sensor using a quartz-resonator array and neural-network pattern recognition has been previously reported. In the present study, optimization of the sensor-array components has been made and the recognition probability has been improved.
The sensitivity, response speed and selectivity of a p-channel Pd-gate MOS transistor to H2S present in the atmosphere are investigated at different temperatures. The response of this device to H2S can be improved by increasing the temperature. The experimental results show that the optimal operation temperature is 150 °C. Under specific conditions, complete reversibility of the device is obtained.
Barrier properties of a promising conjugated polymer, poly(N-methylpyrrole) (PMPY) with high- and low-work-function metals, gold and indium respectively, have been investigated. The electrical conductivity of PMPY films was varied from insulating to metallic levels by electrochemical oxidation I-V characteristics were used to investigate the function properties. Heavily doped PMPY+ films were found to form an Ohmic contact with gold ( phi Au=5.1 eV) and a Schottky barrier with indium ( phi In=4.1 eV), this difference corresponding to the difference in work functions. Results indicate a leaky Schottky barrier with high fields producing InJ varies as V1/2 and are interpreted in terms of metal-semiconductor band theory.
Stimulation According to the “penetration and Puncturing” TheoryOdour Type According to the “penetration and Puncturing” TheorySummaryDiscussionReferences
The application of small all-solid-state galvanic cells for monitoring NO2, CO2 and O2 partial pressures at ambient or slightly increased temperatures is demonstrated. The approach makes use of a gas-sensitive mixed conducting thin layer, which rapidly relates the activity of the gaseous species to the activity of the mobile component according to the Gibbs-Duhem relationship. A reversible change of the potential as a function of the partial gas pressure is observed for the different galvanic cells, which are preferably based on Na+-β/β″-alumina and α-AgI solid electrolytes.
The addition of Ag to Pd in the gate metal of a metal‐insulator‐semiconductor gas sensing diode can improve the performance and change the selectivity of the sensors for a variety of reactions. Data on the response of diodes with 12 different ratios of Ag to Pd in alloys and layers of Pd and Ag to hydrogen and other gases are reported. Diodes with as much as 32% Ag respond very well to H 2 gas and the films are much more durable to high hydrogen exposure than pure Pd films. Improvements in the rate of response and aging behavior are found for certain Ag combinations; others give poorer performance. The presence of Ag on the surface changes the catalytic activity in some cases and examples of H 2 mixed with O 2 and/or NO 2 , propylene oxide, ethylene, and formic acid are given. Such selectivity forms the basis for miniature chemical sensor arrays which could analyze complex gas mixtures.
Chemisorption of oxygen on tin oxide is studied. Correlations between electric conductivity and electron paramagnetic resonance (EPR) measurements are reported.
The response to ammonia of silicon-based Metal Oxide Semiconductor Field Effect Transistor (MOSFET) devices having either evaporated or sputtered Pt gate electrodes has been studied. A substantial difference in ammonia sensitivity was observed between these two types of device, which is thought to be related to differences in morphology between the two types of gate electrode; devices having evaporated Pt gate electrodes, which are non-continuous, are very ammonia sensitive, whereas devices having sputtered Pt gates, which are continuous, are not ammonia sensitive. However, both the evaporated and sputtered gate devices exhibit a similar response to hydrogen (typically, changes in threshold voltage (VT) of approximately -420 mV and -350 mV respectively to 500 ppm hydrogen at 150 °C). The ammonia sensitivity of the evaporated Pt-gate MOSFET is dependent on both temperature and ageing effects; the optimum operating temperature of this device is 175 °C, and a burn-in period of approximately 48 h at 200 °C is necessary before the maximum response to ammonia is observed. The humidity response of both evaporated and sputtered Pt-gate MOSFET devices has been studied at 175 °C; a change from 20 to 95% r.h. does not produce a significant response from either of these devices (ΔVT is typically -35 mV and -5 mV respectively).
Mathematical expressions describing the response of individual sensors and arrays of tin oxide gas sensors are derived from a barrier-limited electron mobility model. From these expressions, the fractional change in conductance is identified as the optimal response parameter with which to characterize sensor array performance instead of the more usual relative conductance. In an experimental study, twelve tin oxide gas sensors are exposed to five alcohols and six beverages, and the responses are studied using pattern-recognition methods. Results of regression and supervised learning analysis show a high degree of colinearity in the data with a subset of only five sensors needed for classification. Principal component analysis and clustering methods are applied to the response of the tin oxide sensors to all the vapours. The results show that the theoretically derived normalization of the data set substantially improves the classification of vapours and beverages. The individual alcohols are separated out into five distinct clusters, whereas the beverages cluster into only three distinct classes, namely, beers, lagers and spirits. It is suggested that the separation may be improved further by employing other sensor types or processing techniques.
Various techniques for selectivity in semiconductor gas sensors, emphasizing powder-based sensors, are reviewed. The use of catalysts and promoters is emphasized, although other techniques such as the use of ‘filters’ are described. Because our understanding of how catalysts and promoters provided selectivity in gas sensors is so poor, a superficial review of the models of catalysis is presented to act as a basis for the discussion of catalysts in sensing. We review the reasons why spillover or Fermi energy control must occur for catalysis to be effective on sensors. We emphasize the different objectives for catalyst behavior in normal heterogeneous catalysis from those in gas sensing. It is concluded from these arguments that a high catalyst dispersion is required in gas sensors, that partial oxidation catalyst may be counter-productive for catalysts designed for gas sensing.
A simple but effective method for the fabrication of reusable dual-microband electrodes for use as gas sensors based on electrochemically polymerized conducting polymers is described. The electrodes are made by sputtering gold onto both sides of thin (12 μm) Mylar films and then encapsulating the resulting gold/Mylar/gold sandwich so that only the edge is exposed. The resulting electrodes are characterized using cyclic voltammetry, a.c. impedance and chronoamperometry.Following the electrochemical deposition of polypyrrole onto the dual-microband electrodes, they can be used as gas-sensitive chemiresistors. Preliminary results for the change of resistance of such a device on exposure to methanol vapour are presented.
General information is presented with respect to the design of gas sensors using surface acoustic waves as the detection principle.Useful configurations use the SAW delay-line oscillator and the SAW resonator oscillator as the detecting element.Some recent experimental results with a SAW NO2 sensor, developed in our laboratories, are presented.
This review covers the fundamental scheme of chemical sensors, fields of major interest in chemical sensors with Langmuir-Blodgett (LB) films, and new and future trends in LB sensor studies. The topics discussed are the relation between sensor characteristics and LB film structure, the biomimetic approach to sensor developments, proposals for transducer improvements, and the possibility of fabricating molecular filters by LB techniques.
The effect of NO2, NO, F2, BCl3, BF3, NH3, H2S, SO2 and HCl at low concentrations (< 1 ppm) in air on the eletrical conductivity of a number of metal phthalocyanines has been investigated. Vacuum sublimed films of Pb, Zn, Cu, Ni, Co and Fe phthalocyanine have been shown to be sensitive to NO2 and F2 but insensitive to more weakly electrophilic and electrophobic gases. Increasing sensitivity to NO2 was observed as phthalocyanines containing progressively heavier metals were used. Magnesium phthalocyanine was affected only by HCl. The potential of these materials as gas sensors is discussed.
The effect of aliphatic alcohols and other small molecules on the resistance of lecithin bilayers has been examined. It is found that short-chain alcohols decrease the bilayer resistance, while above C8 the bilayer resistance is increased. It is proposed that these effects are due to changes in the fluidity of the lipid hydrocarbon chains. In addition to the alcohols, a variety of other molecules induce small conductance changes in the bilayer. The relevance of these findings to the puncturing theory of olfaction and other small molecule-membrane interactions is discussed.
Olfaction exhibits both high sensitivity for odours and high discrimination between them. We suggest that to make fine discriminations between complex odorant mixtures containing varying ratios of odorants without the necessity for highly specialized peripheral receptors, the olfactory systems makes use of feature detection using broadly tuned receptor cells organized in a convergent neurone pathway. As a test of this hypothesis we have constructed an electronic nose using semiconductor transducers and incorporating design features suggested by our proposal. We report here that this device can reproducibly discriminate between a wide variety of odours, and its properties show that discrimination in an olfactory system could be achieved without the use of highly specific receptors.
The temperature characteristics of an H,S sensitive Pd-gate MOS transistor, Sensors and Actuators
- Z Weixin
- Z Yibing
Z. Weixin and Z. Yibing, The temperature characteristics of an H,S sensitive Pd-gate MOS transistor, Sensors and Actuators, I5 (1988) 85-93.
Analysis of discrimination
- K Persaud
- G H Dodd
K. Persaud and G. H. Dodd, Analysis of discrimination