Posts: 53
Threads: 25
Joined: Sep 2009
Reputation:
0
[attachment=2507]
ABSTRACT
In an ever-developing world, where electronic devices are duplicating every other sense of perception, the sense of smell is lagging behind. Yet, recently, there has been an urgent increase in the need for detecting odours, to replace the human job of sensing and quantification. Some of the most important applications fall in the category where human beings cannot afford to risk smelling the substance. Other important applications are continuous monitoring, medical applications, etc. These applications allow man to perform tasks that were once considered impossible. The fast paced technology has helped develop sophisticated devices that have brought the electronic nose to miniature sizes and advanced capabilities. The trend is such that there will be accurate, qualitative and quantitative measurements of odour in the near future.
THE E-NOSE
Mimicking the nose is a challenging task. The human nose can smell 10,000 different odour molecules mixed in air. Odour in a substance is due to certain volatile organic compounds (VOCs), which easily evaporate and get carried by an air stream. An e-nose can smell and estimate odours quickly though it has little or no resemblance to the human nose. A human nose has receptors, which serve as binding sites for VOCs. A receptor is just a molecular structure on the surface of the nerve cell to which an odorous molecule with the right shape binds. The receptor and the binding molecule fit exactly as in a key and lock arrangement. These odour-sensing nerve cells line the upper part of the cavity in the human nose. Once an odour molecule binds to a receptor, a chain reaction follows which ultimately transmits an electrical signal to the brain. A specific odour of coffee or wine is usually caused not by one, but a mixture of hundreds of organic compounds. So, the brain has a mammoth task of processing signals received from the nerve cells originating from the nose, to identify the nature of smell. The exact working of the brain in processing these signals is yet to be fully understood.
An electronic nose can be defined as an instrument which is comprised of an array of electronic chemical sensors with partial specificity and an appropriate pattern recognition system, capable of recognizing simple or complex odours (and other gaseous mixtures). The ability of an electronic nose to rapidly discriminate between slight variations in complex mixtures makes the techniques ideal for on-line process diagnostics and screening across a wide range of application areas. An electronic nose is a machine that is designed to detect and discriminate among complex odours using a sensor array. The sensor array of consists of broadly tuned (non-specific) sensors that are treated with a variety of odour-sensitive biological or chemical materials. An odour stimulus generates a characteristic fingerprint (or smell-print) from the sensor array. Patterns or fingerprints from known odours are used to construct a database and train a pattern recognition system so that unknown odours can subsequently be classified and identified. Thus, electronic nose instruments are comprised of hardware components to collect and transport odours to the sensor array as well as electronic circuitry to digitise and stored the sensor responses for signal processing. The two main components of an electronic nose are the sensing system and the automated pattern recognition system. The sensing system can be an array of several different sensing elements (e.g., chemical sensors), where each element measures a different property of the sensed chemical, or it can be a single sensing device (e.g., spectrometer) that produces an array of measurements for each chemical, or it can be a combination. Each chemical vapour presented to the sensor array produces a signature or pattern characteristic of the vapour. By presenting many different chemicals to the sensor array, a database of signatures is built up. This database of labelled signatures is used to train the pattern recognition system. The goal of this training process is to configure the recognition system to produce unique classifications of each chemical so that an automated identification can be implemented. The quantity and complexity of the data collected by sensors array can make conventional chemical analysis of data in an automated fashion difficult. One approach to chemical vapour identification is to build an array of sensors, where each sensor in the array is designed to respond to a specific chemical. With this approach, the number of unique sensors must be at least as great as the number of chemicals being monitored. It is both expensive and difficult to build highly selective chemical sensors.
Artificial neural networks (ANNs), which have been used to analyse complex data and to recognize patterns, are showing promising results in chemical vapour recognition. When an ANN is combined with a sensor array, the number of detectable chemicals is generally greater than the number of sensors. Also, less selective sensors, which are generally less expensive, can be used with this approach. Once the ANN is trained for chemical vapour recognition, operation consists of propagating the sensor data through the network. Since this is simply a series of vector-matrix multiplications, unknown chemicals can be rapidly identified in the field. Electronic noses that incorporate ANNs have been demonstrated in various applications. Some of these applications will be discussed later in the paper. Many ANN configurations and training algorithms have been used to build electronic noses including back propagationtrained, feed-forward networks; fuzzy ART maps; Cohune s self-organizing maps (SOMs); learning vector quantizers (LVQs); Hamming networks; Boltzmann machines; and Hopfield networks. Figure 1 illustrates the basic schematic of an electronic nose. 6 One of our prototype electronic noses, shown in Figure is composed of an array of nine tinoxide vapor sensors, a humidity sensor, and a temperature sensor coupled with an ANN. Two types of ANNs were constructed for this prototype:the standard multilayer feedforward network trained with the backpropagation algorithm and the fuzzy ARTmap algorithm [2]. During operation a chemical vapor is blown across the array, the sensor signals are digitized and fed into the computer, and the ANN (implemented in software) then identifies the chemical. This identification time is limited only by the response time of the chemical sensors, which is on the order of seconds. This prototype nose has been used to identify common household chemicals by their odor.
Although each sensor is designed for a specific chemical, each responds to a wide variety of chemicals. Collectively, these sensors respond with unique signatures (patterns) to different chemicals. During the training process, various chemicals with known mixtures are presented to the system. By training on samples of various chemicals, the ANN learns to recognize the different chemicals. This prototype nose has been tested on a variety of household and office supply chemicals including acetone, ammonia, ethanol, glass cleaner, contact cement, correction fluid, iso-propanol,lighter fluid, methanol, rubber cement and vinegar.For the results shown in the paper, five of these chemicals were used: acetone, ammonia,isopropanol, lighter fluid, and vinegar. Another category, none was used to denote the absence of all chemicals except those normally found in the air which resulted in six output categories from the ANN.
Both networks were trained using randomly selected sample sensor inputs. The ANNs used here were not trained to quantify the concentration level of the identified analytes, but were trained with samples with different concentrations of the analytes. This allowed the ANN to generalize well on the test data set.Performance levels of the two networks were basically equivalent ranging from 89.7% to 98.2% correct identification on the test set depending on the random selection of training patterns. Figures 4 and 5 illustrate the responses of the sensors and the ANN classification for a variety of test chemicals presented to the ANNs. The ANN was able to correctly classify the test samples with only small residual errors. While the ANN used here was not trained to quantify the concentration level of the identified analytes, it was trained with samples with different concentrations of the analytes. This allowed the ANN to generalize well on the test data set. From the responses of the sensors to the analytes, one can easily see that the individual sensors in the array are not selective . In addition, when a mixture of two or more chemicals is presented to the sensor array, the resultant pattern (sensor values) may be even harder to analyze (see Figure 5: c, d, and e). Thus, analyzing the sensor responses separately may not be adequate to yield the classification accuracy achieved by analyzing the data in parallel.
2.2. Sensing an Odorant
In a typical e-nose, an air sample is pulled by a vacuum pump through a tube into a small chamber housing the electronic sensor array. The tube may be of plastic or stainless steel. A sample-handling unit exposes the sensors to the odorant, producing a transient response as the VOCs interact with the active material. The sensor response is recorded and delivered to the signal-processing unit. Then a washing gas such as alcohol is applied to the array for a few seconds or a minute, so as to remove the odorant mixture from the active material.
Finally, the reference gas is again applied to the array, to prepare it for a new measurement cycle. The odorant is applied for a period equal to the response time of the input output Array of gas sensors Sample Handler Signal Processing System sensor array. The washing and reference gases are applied for the sensor array to recover and come to a reference point. This duration is termed the recovery time. The main steps of odor recognition can be briefly explained as follows:
- Heating the sample for a certain time generates the smell.
- The gas phase is sampled and transferred to a detection device which reacts to the
presence of various molecules.
- The difference in the sensor reactions is revealed using different statistical pattern recognition techniques to classify the odors. From this pattern and from previous human input (human training from sensory panels), the system predicts the mostly likely human response to the new pattern.
The electronic nose gives either a simple answer like recognized, good, or bad or a more sophisticated response such as an odor intensity or a molecule concentration The terminology can be simple and qualitative or more specific and quantitative.
2.3. Gas Sensors
The main advantages of the gas sensors are as follows.
1. High Speed
2. Reliable
3. Continuous real time monitoring of sites, etc.
The problems associated with human panels are individual variation, adaptation, fatigue, infectious mental state, subjectivity and exposure to hazardous compounds. So, the enose can create an odour profile that extends beyond the capabilities of the human panel or GC/MS measurement techniques. The output of the e-nose can be the identity of the odorant, an estimate concentration of the odorant, or the characteristic properties of the odour as might be perceived by a human.
Fundamental to the artificial nose is the idea that each sensor in the array has different sensitivity. Also, the pattern of responses across all sensors in the array is used to identify and/or characterize the odour.
INTRODUCTION TO SENSORS
A sensor is a device which can respond to some properties of the environment and transform the response into an electric signal. The general working mechanism of a sensor is illustrated by the following scheme :
In the field of sensors, the correct definition of parameters is of paramount importance because these parameters:
allow the diffusion of more reliable information among researchers or sensor operators, allow a better comprehension of the intrinsic behaviour of the sensors help to propose new standards, give fundamental criteria for a sound evaluation of different sensor performances. Response curves and sensitivity
Output signal :
The output signal is the response of the sensor when the sensitive material undergoes modifications, in the following pattern :
SENSITIVE MATERIAL (M) TRANSDUCER SENSOR (Vout)
Different types of response curves exist. The linear response is the easiest one; it is characterized by the following equation Vout = aM + b. The other response is a non linear one; its equation is Vout = f(M).
Output noise :
Noise measurement must be done if one wants to have an accurate definition of the sensor. The noise is the output signal when the sensor does not measure any variations of the sensitive material. The noise depends on the frequency (cf. graph). If we consider two sensors with the same output noise but a different sensitivity (cf. graph), we can underline two statements :
statement 1 : the sensor which has the greatest sensitivity allows the detection of a lower M
level.
statement 2 : the sensor which has the greatest sensitivity allows a better resolution with
respect to the other.
Resolution
The resolution is the measurement level which gives, at the output, a signal to noise ratio S/N)
equal to 1.
In practice, (S/N) = 3 or (S/N) = 9.
We must distinguish between the resolution at the minimun M value and the resolution elsewhere on the response curve. Moreover, it is essential to consider that the resolution value follows the working point along the response curve and the boundary conditions. Selectivity / Contents The selectivity is the capacity of a sensor to be sensitive to a specific compound. The artificial sensing techniques are often based on sensor arrays (electronic tongue and electronic nose, for instance). In those cases, using less selective sensors is more interesting because one can detect a larger field of compounds. Reversibility / Contents The reversibility is the aptitude of the sensing mechanism to follow (of course with a given delay) the variation of the environment. It means that initial conditions must be obtained when the input reaches initial values.
In pratice, reversibility is a requirement for continuous monitoring applications (e.g. in environmental applications). However reversibility, as it requires week interactions between sensors and analytes, can not be compatible with high selectivity which needs strong interactions. When the sensors are non reversible,we can distinguish between : Regenerable sensors : the initial conditions can be ripristinated through an additional chemical process Disposable sensors which can be used only one time (e.g. medical sensors)
TYPES OF SENSORS
E-nose is classified based on the type of sensors used.
1. Conductivity Sensors
2. Piezoelectric Sensors
3. FET gas Sensors
4. Optical Sensors
5. Spectrometry based sensing methods
3.1. Conductivity Sensors
There are two types of conductivity sensors: 1) metal oxide 2) polymer, both of whichexhibit a change in resistance when exposed to volatile organic compounds.
3.1.1. Metal Oxide Type
Working principle
These sensors are made of a ceramic former heated by a heating wire and coated by a semiconducting film. These semiconductor sensors can sense gases by monitoring changes in the conductance during the interaction of a chemically sensitive material with molecules that need to be detected in the gas phase.
Metal
Active Electrodes
Material
Resistive
Heating
They are used to detect toxic and flammable gases in domestic and environmental applications and for food aromas.
How to increase selectivity
The metal oxides are generally less selective than many other sensor technologies. Selectivity may be obtained using several methods:
- use of filters
- deposition of a suitable catalyst layer
- pulsing of sensor temperature in working conditions
- use of other semiconducting metal oxides
- control of the grain size Preparation techniques for gas sensors Metal oxide gas sensors can be subdivised into:
- Thick film devices (depositing a paste of material between two electrodes)
Advantages Disadvantages
easier to produce
poor selectivity
depend on ambient
temperatures and relative
humidities
long stabilizing times after
energization
large power consumption
-Thin film devices: they use vapor deposition technologies in order to obtain a very thin film of metal oxide between two electrodes.
Advantages Disadvantages
significantly higher
sensitivity
lower power consuption
per device
more expensive
more difficult to produce
instable
Different deposition methods like PVD ( sputtering, thermal evaporation .. ), spray and solgel
techniques can be used for the preparation of thin film gas sensors.
A new method called RGTO enables to prepare mixed oxide thin films with high surface area and nanosized crystallites.
These sensors are manufactured by, among others, the Japonese company FIGARO.
Advantages and disadvantages of metal oxide semiconductor
Advantages
- they are available because they are commercially produced
- they have high sensitivities to a range of organic vapors
- a variety of different types are available with broadly different sensitivities so that an array can be constructed
- they are characterized by a relatively fast response, typically less than 10 seconds
Disadvantages
- their size
- they operate at elevated temperatures
- they are highly sensitive to compounds such as ethanol, CO2 or humidity Typical offerings include oxides of tin, zinc, titanium, tungsten and iridium, doped with a noble metal catalyst such as platinum or palladium, which operates at 200 C to 400 C.
As a VOC passes over the doped oxide material, the resistance between the two metal contacts changes in proportion to the concentration of the VOC.
Advantages: Wide availability and low cost.
Disadvantages: These are prone to drift over periods of hours to days. So, signal-processing algorithm should be employed to counteract this property. These sensors are also susceptible to irreversible binding by sulphur compounds.
Applications: The sensitivity ranges from 5 to 500 ppm. Used for sensing CO, NH3, or H2O.
3.1.2. Polymer Sensors
Here the active material is a conducting polymer from such families as the polypyroles, thiophenes, indoles or furans. Changes in the conductivity of these materials occur as they are exposed to various types of chemicals, which bond with the polymer backbone. A given compound s affinity for a polymer and its effect on the polymer s conductivity are strongly influenced by the counter ions and functional group attached to the polymer backbone. Here the response time is inversely proportional to the polymer s thickness, which is usually in the range of 10 to 20 m.
Advantages: The sensitivity varies from 0.1 ppm to 100 ppm. No need of heaters, as they will operate in the ambient temperatures. High portability.
Disadvantages: They are difficult to make. Their responses also drift over time. More susceptible to humidity.
3.2. Piezoelectric Sensors
These are of two types QCM (Quartz Crystal Microbalance) and SAW (Surface Acoustic Wave devices). Here they are configured as mass change sensing devices.
3.2.1. QCM Type
It consists of resonating disc with metal electrodes on each side connected to read wire. The device resonates at a characteristic frequency (10 to 30 MHz), when excited with an oscillating signal. During manufacturing, a polymer coating is applied to the disc to serve as the active sensing material. In operation, a gas sample is adsorbed at the surface of the polymer, increasing the mass of the disk polymer device and thereby reducing the resonance
frequency. The reduction is inversely proportional to the odorant mass adsorbed by the polymer when the sensor is exposed to a reference gas. The resonance frequency returns to the baseline value.
Advantages: High sensitivity. Remarkably, linear over a wide dynamic range. Sensitivity does not change with temperature. Humidity response will depend upon the type of adsorbent material used. Batch to batch variability is not a problem as a differential change measurement of frequency change will remove the common mode noise. Disadvantages: When dimensions are scaled down to micrometer level the surface to volume ration will increase and so the noise to signal ratio also will increase.
3.2.2. SAW Type
Here a surface wave travels over the surface of the device. So sensors operate at much higher frequency and so can generate a large change in frequency. A typical SAW device operates in hundreds of Megahertz, while 10 MHz is more typical for a QCM. But SAW devices can measure changes in mass to the same order of magnitude as QCMs.
3.3. FET gas Sensors
The FET is a " metal "/ insulator / semiconductor structure in which the gate (the " metal ") can be any conducting layer or medium. The FET is a semiconducting device which acts as an amplifier (like a transistor). There are different FET configurations:
-the MOSFET: metal oxide semiconductor FET
-the SGFET: fabrication of a Suspended Gate on a metal-oxide-semiconductor
-the ISFET: ion sensitive FET
Advantages and disadvantages of the MOSFET
Advantages:
-high sensitivity
-small size
-low cost
Disadvantages
The reproducibility and the sensibility of the sensor are not sufficient enough to use it in a real measuring system, particularly for a multiple-component gas mixture. These are based on the principle that VOCs in contact with a catalytic metal can produce a reaction in the metal. The reaction products can diffuse through the gate of a MOSFET to change the electrical properties of the device. The sensitivity and selectivity of the device can be optimised by ranging the type and thickness of the metal catalyst and operating them at different temperatures.
Advantages: They can be made by IC fabrication processes. So the batch variations can be minimised.
Disadvantages: There should be a window in the IC chip to permit the flow of odorants to cause the catalytic product above the gate structure. So there is a necessity for sealing off all other areas. These sensors are also susceptible to baseline drift.
3.4. Optical Fibre Sensors
These utilise glass fibres with a thin chemically active material coating on their sides or ends. A light source at a single frequency is used to interrogate the active materials, which responds with the change in colour to the presence of VOCs. The active material contains chemically active fluorescent dyes immobilized in an organic polymer matrix. As VOCs interact with it, the polarity of the fluorescent emission spectrum.
Advantages: Cheap and easy to fabricate. Arrays of fibre sensors have wide range of sensitivities. Differential measurement is possible to avoid common mode noise. Disadvantages: Complexity of the measuring system. Limited lifetime to photo bleaching.
3.5. Spectrometry Based Sensors
Here a vapour trap is used to concentrate the VOCs and then it being injected into a spectrometer that generates a spectral response characteristic of the vapour. Then the efficient signal processing technique can be used for finding out the odorant. Here the disadvantage is that is the use of highly complex electronic measuring device.
Potentiometric Chemical Sensors Potentiometric Chemical Sensors are based on the measurement of a potential under no current flow. The measured potential may then be used to determine the analytical concentration of some components of the analyte solution. For useful definitions please go to Electrochemical terms and concepts. There exist different types of potentiometric chemical sensors. A classification shows the binding between them. This web-page will only develop the ion selective sensors (ISE) and the biosensors.
Ion selective sensors (ISE)
An ISE produces a potential which is proportional to the concentration of an analyte. Making measurements with an ISE is therefore a form of potentiometry. The most common ISE is the pH electrode, which contains a thin glass membrane that responds to the H+ concentration in a solution. Ion selective sensors are susceptible to several interferences. Samples and standards are therefore diluted 1:1 with total ionic strength adjuster and buffer (TISAB). The instrumentation of an ISE consists of the ion-selective membrane, an internal reference electrode, an external reference electrode, and a voltmeter. Different sorts of ion selective membranes exist : the glass, the chalcogenide and the crystal membrane. Research currently focuses on chalcogenide membranes.
Biosensors
The principle : coupling enzymes and electrode reactions. The enzyme is used as a bioelectrocatalyst of the oxydation or reduction of a substrate. There are 2 different ways of coupling enzymes and electrode reactions : with mediator or mediatorless
Example : measurement of the concentration of glucose
The electrochemical kinetic of enzymatic catalysis
Xi + ni e- Xi n- K(j) = K0 exp (-a ni F j /RT) avec a =0.5
Xj + n2 e- Xj n2-
equilibrium step
Xj n- / Xj = K0 exp (-n2 F j /RT) =K(j)
In the first step, the substrate is absorbed. Then there is an equilibrium of the e- into the reacting site. The last step is the biochemical reaction. The e- tunneling in the bioelectrocatalysis is the process which transfers the e- from the electronic matrix to the enzyme site.
Two steps : E E* E + P
w® Kcat
w® = exp (-r /A)
a = w® / (Kcat + w®)
Each step can be the limiting one.
The importance of the deposition of the enzymes on the surface.
The effectivity to electrons transfer depends on the distance between the enzymes and the electrode. Therefore the deposition on the enzymes of the surface must be made with care. Advantages and disadvantages of potentiometric chemical sensors Advantages
- A wide range of available sensing materials and sensors.
- Wide variations of sensor properties, some unique features
- A wide knowledge about composition / properties relationship
- Simple installation. Easy, direct measurements.
- Different configurations (static, flow, bulk, micro).
- Easy applicability for automatic and / or industrial analysis.
- Low cost.
Disadvantages
- Insufficient selectivity of many sensors.
- The number of available sensors is still smaller than the number of analytes.
Posts: 53
Threads: 20
Joined: Sep 2009
Reputation:
0
[attachment=8340]
Submitted by,
K.MANO & K.KAVITHA
PSY Engineering College.
SYNOPSIS
Introduction
Human nose vs. Electronic nose
Advantages over human sniffers
Sensors in E-nose
E-nose Instrumentation
Portable E-nose
Food quality analysis
Health monitoring
Human body odour analysis
Humidity control
Applications
Future development
Conclusion
EMBEDDED ELECTRONIC NOSE
INTRODUCTION
An electronic nose is an instrument which comprises an array of electronic chemical sensors with partial specificity and an appropriate pattern recognition system capable of recognizing simple or complex odours . The "electronic nose" is a relatively new tool that may be used for safety, quality, or process monitoring, accomplishing in a few minutes procedures that may presently require days to complete. Therefore the main advantage of this instrument is that in a matter of seconds, it delivers objective, reproducible aroma discrimination with sensitivity comparable to the human nose for most applications.
HUMAN NOSE vs. ELECTRONIC NOSE
Each and every part of the electronic nose is similar to human nose. The function of inhaling is done by the pump which leads the gas to the sensors. The gas inhaled by the pump is filtered which in the human is the mucus membrane. Next comes the sensing of the filtered gas, which will be done by the sensors i.e., olfactory epithelium in human nose. Now in electronic nose the chemical retain occurs which in human body is enzymal reaction. After this the cell membrane gets depolarised which is similar to the electric signals in the electronic nose. This gets transferred as nerve impulse through neurons i.e., neural network and electronic circuitries.
ADVANTAGES OVER HUMAN SNIFFERS
The human sniffers are costly when compared to electronic nose. It is because these people have to be trained. This is a time consuming that a construction of an electronic nose. Now for the confirmation of the values obtained from a sniffer the result obtained from the sniffer has to be compared with some other sniffer s value. And here there are great chances of difference in the values got by each individual. Detection of hazardous or poisonous gas is not possible with a human sniffer. Thus taking into consideration all these cases we can say that electronic nose is highly efficient than human sniffer.
DIFFERENT TYPES OF SENSORS
There are different types of electronic noses which can be selected according to requirements. Some of the sensors available are calorimetric, conducting, piezoelectric etc. Conducting type sensors can again be sub divided into metal oxide and polymers. In this type of sensors the functioning is according to the change in resistance. The sensor absorbs the gas emitted from the test element and this results in the change of resistance correspondingly. According to the Resistance-Voltage relation V=I*R. Here V is the voltage drop, R is the resistance of the sensor and I is the current through it. By this relation as resistance changes the voltage drop across the sensor also change. This voltage is measured and is given to the circuit for further processes. The voltage range for using metal oxide sensor in from 200 C to 400 C. The working principle of polymer sensor is same as that of metal oxide sensor .Calorimetric sensors are preferable only for combustible species of test materials. Here the sensors measure the concentration of combustibles species by detecting the temperature rise resulting from the oxidation procession a catalytic element.
ELECTRONIC NOSE INSTRUMENTATION
A data-processing system (NST Senstool) as we have our brain.
A MOSFET sensor rely on a change of electrostatic potential. They respond exclusively to molecules that dissociate hydrogen on the catalytic metal surface (such as amines, aldeids, esthers, chetons, aromatics ed alcohols) and they work at the temperature of 140-170 C. When polar compounds interact with this metal gate, the electric field, and thus the current flowing through the sensor, are modified. The recorded response corresponds to the change of voltage necessary to keep a constant present drain current.
A MOS sensor rely on change of conductivity induced by the adsorption of gases. Due to the high operating temperature (300-400 C) the organic volatiles (such as satured hydrocarbons, NO, CO etc.) transferred to the sensors are totally combusted to carbon dioxide and water on the surface of the metal oxide, leading to a change in the resistance.
NST Senstool software offers three methods for analyzing sensors input:
PCA: Principal Component Analysis
PLS: Partial Least Square Regression
ANN: Artificial Neural Network
IPNOSE: A PORTABLE ELECTRONIC NOSE BASED ON EMBEDDED
TECHNOLOGY FOR INTENSIVE COMPUTATION AND TIME DEPENDENT
SIGNAL PROCESSING
Here we suggest the integration of a small form factor computer for an electronic nose
system. This concept allows us to seamlessly implement arbitrary temperature modulation for tin-oxide sensors, remote connectivity, large Data storage, and complex signal processing.Gas sensors used in electronic noses are based on broad selectivity profiles, mimicking the responses of olfactory receptors in the biological olfactory system. The basic building blocks of a generic electronic-nose systems include sample delivery, sensor chamber, signal transduction and acquisition, data preprocessing, feature extraction and feature classification. In conventional systems, the processing module is a personal computer separated from the remaining parts of the system. This module is responsible for data preprocessing, feature extraction and classification. Significant efforts are required to improve the overall performance of the instrument, and every component must be given careful consideration.
MONITORINGOPEN ACCESS
FOOD ANALYSIS
The electronic nose finds wide applications in the food industry. It is used to detect the bacterial growth on foods such as meat and fresh vegetables. It can be used to test the freshness of fish. It is used in the process control of cheese, sausage, beer, and bread manufacture. Other applications include Identification of spilled chemicals in commerce (for U.S. Coast Guard), Quality classification of stored grain, Diagnosis of ulcers by breath tests, Detection and diagnosis of pulmonary infections (e.g., TB or pneumonia), Identification of source and quality of coffee, Monitoring of roasting process, and so on.
The use of ENs for food quality analysis tasks is twofold. ENs is normally used to discriminate different classes of similar odour-emitting products. In particular ENs already served to distinguish between different coffee blends and between different coffee roasting levels and beverages. This is because the separation achieved by the gas chromatographic technique is complemented by the high sensitivity of mass spectroscopy and its ability to identify the molecules eluting from the column on the basis of their fragmentation patterns. Detection limits as low as 1 ppb (parts per billion) are frequently reached. Commercial coffees are blends, which, for economic reasons, contain (monovarietal) coffees of various origins.
HEALTHCARE MONITORING
Many new applications await in such area as healthcare monitoring, biometrics and cosmetics. In principles, the human body dynamically generates unique patterns of volatile organic compounds (VOCs) under diverse living conditions such as eating, drinking, sexual activities, health or hormonal status. These VOCs released from the human body can give some information about diseases, behavior, emotional state and health status of a person. The human odor is released from various parts of body and exists in various forms such as exhalation, armpits, urine, stools, farts or feet. E-nose can diagnose the urine odor of the patients with kidney disorders.
HUMAN BODY ODOUR ANALYSIS
An electronic nose (E-nose) has been designed and equipped with software that can detect and classify human armpit body odor. An array of metal oxide sensors was used for detecting volatile organic compounds. The measurement circuit employs a voltage divider resistor to measure the sensitivity of each sensor. This E-nose was controlled by in-house developed software through a portable USB data acquisition card with a principle component analysis (PCA) algorithm implemented for pattern recognition and classification. The E-nose is still able to recognize people, even after application of deodorant. In conclusion, this is the first report of the application of an E-nose for armpit odor recognition.
HUMIDITY CONTROL
Most chemical gas sensors are sensitive to humidity. Therefore, if two identical samples with a different humidity are measured, the results can be different. In our work, we propose two methods as solutions to this problem. The first is a hardware-based method, where the sample was handled so as to have almost the same humidity as the background. Under such condition, the humidity signals will be equivalent for the sample and the reference, thereby only signals from the odors of interest result. To produce a constant humidity background, the carrier gas was directed to flow through a liquid water container that is immersed in a temperature-controlled heat bath. The temperature of the heat bath can be adjusted until the generated humidity reaches the desired value. humidity.
APPLICATIONS OF ELECTRONIC NOSES
There are various applications in which an electronic nose may be used.
Environmental monitoring
Monitoring of air, water and land.
Medical Diagnostics and Health Monitoring
Breath Monitoring
Eye Infection
Medical Environmental Monitoring
Leg Ulcers
Cultured Bacteria
Food and Beverage Applications
Quality and process monitoring of fruits, vegetables, meat, fish, brewery, tea, coffee and so on.
Automotive and Aerospace Applications
Detection of hazardous gas within automobiles, spacecrafts.
Narcotic Detection.
Application in Cosmetics and Fragrance Industry
Detection of Explosives
FUTURE DEVELOPMENTS
Future developments in the use of hybrid micro sensor arrays and the development of adaptive artificial neural networking techniques will lead to superior electronic noses.
The major areas of research being carried out in this field are:
1. Improved sensitivity for use with water quality and sensitive microorganism detection applications.
2. Identification of microorganisms to the strain level in a number of matrices, including food.
3. Improvement in sensitivity of the E-Nose for lower levels of organisms or smaller samples.
4. Identification of infections such as tuberculosis in noninvasive specimens (sputum, breath).
5. Development of sensors suitable for electronic nose use, and evaluation of unexploited sensors.
CONCLUSIONS
Researches are still going on to make electronic nose much more compact than the present one to make it more compact and to make electronic nose I.C.s. In future we might be able to manufacture olfactory nerves.
Advantages of the electronic nose can be attributed to its rapidity, objectivity, versatility, non requirement for the sample to be pretreatment, easy to use etc.
Posts: 60
Threads: 29
Joined: Jul 2009
Reputation:
0
[attachment=1651]
ELECTRONIC NOSE
ABSTRACT
The perception of volatile compounds by the human nose is of great importance in evaluating the quality of foods. Therefore, it is not surprising that repeated efforts have been made over the years to introduce instruments operating on a similar principle as the human nose: the electronic nose is an instrument that encloses the human sensitivity to the objectivity of the instrumental response and supplies results similar to the human nose and in short time.
An electronic nose is an instrument which comprises an array of electronic chemical sensors with partial specificity and an appropriate pattern recognition system capable of recognising simple or complex odours. It can be regarded as a modular system comprising a set of active materials which detect the odour, associated sensors which transduce the chemical quantity into electrical signals, followed by appropriate signal conditioning and processing to classify known odours or identify unknown odours.
Research has been carried out into the use of thin and thick film semiconducting (inorganic and organic) materials for odour sensing. Research effort is now centered upon the use of arrays of metal oxide and conducting polymer odour sensors. The latter are particularly exciting because their molecular structure can be engineered for a particular odour-sensing application. The electronic nose finds wide applications in the food industry. Future developments in the use of hybrid micro sensor arrays and the development of adaptive artificial neural networking techniques will lead to superior electronic noses.
By,
Deena Davies,
IV year, Biomedical Engineering Department
Sahrdaya College of Engineering And Technology,
Kodakara, Thrissur, Kerala.
INTRODUCTION
The perception of volatile compounds by the human nose is of great importance in evaluating the quality of foods. Therefore, it is not surprising that repeated efforts have been made over the years to introduce instruments operating on a similar principle as the human nose: the electronic nose or simply the E-nose is an instrument that encloses the human sensitivity to the objectivity of the instrumental response and supplies results similar to the human nose and in short time.
An electronic nose is an instrument which comprises an array of electronic chemical sensors with partial specificity and an appropriate pattern recognition system capable of recognising simple or complex odours . It can be regarded as a modular system comprising a set of active materials which detect the odour, associated sensors which transduce the chemical quantity into electrical signals, followed by appropriate signal conditioning and processing to classify known odours or identify unknown odours.
The "electronic nose" is a relatively new tool that may be used for safety, quality, or process monitoring, accomplishing in a few minutes procedures that may presently require days to complete. Therefore the main advantage of this instrument is that in a matter of seconds, it delivers objective, reproducible aroma discrimination with sensitivity comparable to the human nose for most applications. The term "electronic nose" was first used in a jocular sense with sensor arrays in the 1980's. As the technology developed, it became apparent that the animal and human olfactory systems operate on the same principle: A relatively small number of nonselective receptors allow the discrimination of thousands of different odours.
Research has been carried out into the use of thin and thick film semiconducting (inorganic and organic) materials for odour sensing. Research effort is now centered upon the use of arrays of metal oxide and conducting polymer odour sensors.
HUMAN NOSE vs. ELECTRONIC NOSE
ELECTRONIC NOSE INSTRUMENTATION
An electronic nose like human sensory systems, it incorporates:
Chemical sensors (10 MOSFET and 5 MOS) as we have human olfactory receptors in our olfactory region.
A data-processing system (NST Senstool) as we have our brain.
A MOSFET sensor rely on a change of electrostatic potential. They respond exclusively to molecules that dissociate hydrogen on the catalytic metal surface (such as amines, aldeids, esthers, chetons, aromatics ed alchols) and they work at the temperature of 140-170 C. When polar compounds interact with this metal gate, the electric field, and thus the current flowing through the sensor, are modified. The recorded response corresponds to the change of voltage necessary to keep a costant present drain current.
A MOS sensor rely on change of conductivity induced by the adsorption of gases. Due to the high operating temperature (300-400 C) the organic volatiles (such as satured hydrocarbons, NO, CO etc.) trasferred to the sensors are totally combusted to carbon dioxide and water on the surface of the metal oxide, leading to a change in the resistance.
NST Senstool software offers three methods for analyzing sensors input:
PCA: Principal Component Analysis
PLS: Partial Least Square Regression
ANN: Artificial Neural Network
They enable to:
Get an overview of the data (PCA and PLS)
Predict properties of the samples (PLS e ANN
PCA is a rotation-projection method that helps visualizing the information contained in a large data set. It is a transformation in which many original dimensions are transformed into another coordinate system with fewer dimensions.
PLS is a regression model which use Principal Components and in which we must give a property of the samples such as class or quantitative value.
Artificial neural networks are the most powerful type of data processing technique being employed in Electronic Nose instruments. ANNs are self-learning; the more data presented, the more discriminating the instrument becomes. By running many standard samples and storing results in computer memory, the application of ANN enables the Electronic Nose to "understand" the significance of the sensor array outputs better and to use this information for future analysis.
ANNs allow the Electronic Nose to function in the way a brain functions when it interprets responses from olfactory sensors in the human nose. The ANN's processing elements (or nodes) can be compared to the neurons in the brain. "Learning" is achieved by varying the emphasis, or weight, that is placed on the output of one sensor versus another. ANNs also can be trained to compensate for small response changes that occur when sensors degrade over time. Ideally, a sensor array would respond to a specific sample with the same precision over a long period of time. However, sensors can degrade with prolonged use and the output can vary. ANNs can correct for this problem.
As the organic vapors pass over the sensor array each sensor responds with a certain selectivity. These patterns need to be further processed. Electronic Nose Technology (ENT) is the combination of sensor arrays linked with advanced statistical and neural network software that provides a visual image of an odour, or how an odour relates to other odours. This relationship could represent good bad, pass fail, new old, or the system can be trained to recognize attributes such as green, fruity, floral or spoiled. ENT correlates exceedingly well with both sensory and tradition analytical techniques and ENT can combine both elements in a single analysis.
A number of prototype electronic noses have been developed by the electronic nose research group. There are several laboratory-based instruments, one employing an array of metal oxide sensors, and another employing an array of conducting polymer sensors. This research has led to the production of two desk-top sized electronic nose instruments. Several portable instruments have also been designed and built. These include a 4-element tin oxide electronic nose, a 6-element tin oxide electronic nose, and four 12-element polymer electronic noses.
The E-Nose is best suited for matching complex samples with subjective endpoints such as odor or flavor. For example, when has milk turned sour? Or, when is a batch of coffee beans optimally roasted? The E-Nose can match a set of sensor responses to a calibration set produced by the human taste panel or olfactory panel routinely used in food science. The E-Nose is especially useful where consistent product quality has to be maintained over long periods of time, or where repeated exposure to a sample poses a health risk to the human olfactory panel. Although the E- Nose is also effective for pure chemicals, conventional methods are often more practical.
APPLICATIONS
The electronic nose finds wide applications in the food industry. It is used to detect the bacterial growth on foods such as meat and fresh vegetables. It can be used to test the freshness of fish. It is used in the process control of cheese, sausage, beer, and bread manufacture. Other applications include Identification of spilled chemicals in commerce (for U.S. Coast Guard), Quality classification of stored grain, Diagnosis of ulcers by breath tests, Detection and diagnosis of pulmonary infections (e.g., TB or pneumonia), Identification of source and quality of coffee, Monitoring of roasting process, and so on.
FUTURE DEVELOPMENTS
There are numerous potential applications of electronic noses from the product and process control to the environmental monitoring of pollutants and diagnosis of medical complaints. However, this requires the developments of application-specific electronic nose technology, that is electronic noses that have been designed for a particular application. This usually involves the selection of the appropriate active material, sensor type and pattern recognition scheme. The work has led to several commercial instruments, one employing commercial tin oxide sensors (Fox 2000, Alpha MOS, France) and another employing conducting polymer sensors (NOSE, Neotronics Ltd, UK). Future developments in the use of hybrid microsensor arrays and the development of adaptive artificial neural networking techniques will lead to superior electronic noses.
The major areas of research being carried out in this field are:
1. Improved sensitivity for use with water quality and sensitive microorganism detection applications.
2. Identification of microorganisms to the strain level in a number of matrices, including food.
3. Improvement in sensitivity of the E-Nose for lower levels of organisms or smaller samples.
4. Identification of infections such as tuberculosis in noninvasive specimens (sputum, breath).
5. Development of sensors suitable for electronic nose use, and evaluation of unexploited sensors.
CONCLUSION
Advantages of the electronic nose can be attributed to its rapidity, objectivity, versatility, non requirement for the sample to be pretreatment, easy to use etc. And now scientists at the University of Rome have developed a sensor, which, they claim, can detect those chemicals flowing out of a cancerous lung. Their tests, on a group of 60 people - half with lung cancer - pinpointed every single cancer patient. They suggested that an 'e-nose' could one day form the basis of a screening test for smokers and others at risk of lung disease. The only way of doing this reliably at the moment is to use a bronchoscope to look directly at the insides of the lungs for signs of cancer.
Posts: 53
Threads: 21
Joined: Jul 2009
Reputation:
0
[attachment=15038]
1. INTRODUCTION
ELECTRONIC Noses (EN), in the broadest meaning, are instruments that analyze gaseous mixtures for discriminating between different (but similar) mixtures and, in the case of simple mixtures, quantify the concentration of the constituents. ENs consists of a sampling system (for a reproducible collection of the mixture), an array of chemical sensors, Electronic circuitry and data analysis software. Chemical sensors, which are the heart of the system, can be divided into three categories according to the type of sensitive material used: inorganic crystalline materials (e.g. semiconductors, as in MOSFET structures, and metal oxides); organic materials and polymers; biologically derived materials.
The use of ENs for food quality analysis tasks is twofold. ENs is normally used to discriminate different classes of similar odour-emitting products. In particular ENs already served to distinguish between different coffee blends and between different coffee roasting levels. On the other hand, ENs can also be used to predict sensorial descriptors of food quality as determined by a panel (often one generically speaks of correlating EN and sensory data). ENs can therefore represent a valid help for routine food analysis.
The combination of gas chromatography and mass spectroscopy (GC-MS) is by far the most popular technique for the identification of volatile compounds in foods and beverages. This is because the separation achieved by the gas chromatographic technique is complemented by the high sensitivity of mass spectroscopy and its ability to identify the molecules eluting from the column on the basis of their fragmentation patterns. Detection limits as low as 1 ppb (parts per billion) are frequently reached. The main drawbacks of the approach are, however, the cost and complexity of the instrumentation and the time required to fully analyze each sample (around one hour for a complete chromatogram). Comparatively, ENs are simpler, cheaper devices. They recognize a fingerprint, that is global information, of the samples to be classified. For food products, the sensory characteristics determined by a panel are important for quality assessment. While man still is the most efficient instrument for sensorial evaluation, the formation of a panel of trained judges involves considerable expenses.
Commercial coffees are blends, which, for economic reasons, contain (monovarietal) coffees of various origins. For the producers the availability of analysis and control techniques is of great importance. There exists a rich literature on the characterization of coffee using the chemical profile of one of its fractions, such as the headspace of green or roasted beans or the phenolic fraction. In the literature up to 700 diverse molecules have been identified in the headspace. Their relative abundance depends on the type, provenance and manufacturing of the coffee. It is to be noticed that none of these molecules can alone be identified as a marker. On the contrary one has to consider the whole spectrum, as for instance the gas chromatographic profile.
2. COMPARISION OF ELECTRONIC NOSE WITH BIOLOGICAL NOSE
Each and every part of the electronic nose is similar to human nose. The function of inhaling is done by the pump which leads the gas to the sensors. The gas inhaled by the pump is filtered which in the human is the mucus membrane. Next comes the sensing of the filtered gas, which will be done by the sensors i.e., olfactory epithelium in human nose. Now in electronic nose the chemical retain occurs which in human body is enzymal reaction. After this the cell membrane gets depolarised which is similar to the electric signals in the electronic nose. This gets transferred as nerve impulse through neurons i.e., neural network and electronic circuitries.
3.DIFFERENT TYPES OF SENSORS
There are different types of electronic noses which can be selected according to requirements. Some of the sensors available are calorimetric, conducting, piezoelectric etc. Conducting type sensors can again be sub divided into metal oxide and polymers. In this type of sensors the functioning is according to the change in resistance. The sensor absorbs the gas emitted from the test element and this results in the change of resistance correspondingly. According to the Resistance-Voltage relation V=I*R. Here V is the voltage drop, R is the resistance of the sensor and I is the current through it. By this relation as resistance changes the voltage drop across the sensor also change. This voltage is measured and is given to the circuit for further processes. The voltage range for using metal oxide sensor in from 200 C to 400 C. The working principle of polymer sensor is same as that of metal oxide sensor The only change is in the temperature range i.e., the room temperature.
Piezoelectric sensors are sub-divided into quartz crystal microbalances and surface acoustic wave. In quartz crystal the surface absorbs the gas molecules. This results in the change of mass, which causes a change in the resonant frequency of the quartz crystal. This change in frequency is proportional to the concentration of the test material. The change in frequency also results a change in the phase. In surface acoustic wave we measure the change in phase of the resonant frequency.
Calorimetric sensors are preferable only for combustible species of test materials. Here the sensors measure the concentration of combustibles species by detecting the temperature rise resulting from the oxidation process on a catalytic element.
Posts: 60
Threads: 26
Joined: Aug 2009
Reputation:
0
[attachment=14549]
INTRODUCTION
The electronics field is developing at a fast rate. Each
day the industry is coming with new technology and
products. The electronic components play a major role in
all fields of life. The scientists had started to mimic the
biological world. The development of artificial neural
network (ANN), in which the nervous system is
electronically implemented is one among them.
The scientists realized the importance of the
detection and identification of odor in many fields. In
human body it is achieved with the help of one of the
sense organ, the nose. So scientists realized the need of
imitating the human nose. The concept of the electronic
nose appeared for the first time in a nature paper by
Persuade and Dodd (1982). The authors suggested and
demonstrated with a few examples that gas sensor array
responses could be analyzed with artificial neural
networks thereby increasing sensitivity and precision in
analysis significantly. This first publication was followed
by several methodological papers evaluating different
sensor types and combinations.
The scientists saw the last advances in the electronic
means of seeing and hearing. Witnessing this fast
advances they scent a marker for systems mimicking the
human nose. The harnessing of electronics to measure
odor is greatly desired. Human panels backed by gas
chromatography (GC)/ mass spectroscopy (MS) are helpful
Electronic Nose
in quantifying smells. The human panels are subject to
fatigue and inconsistencies. While classical gas
chromatography (GC)/ mass spectrograph (MS) technique
separate quantify and identify individual volatile
chemicals, they cannot tell us if the components have an
odour. Also they are very slow. So it is important that
faster methods must give way to speedier procedure using
an electronic nose composed of gas sensory. The E-nose
was developed not to replace traditional GC/MS and
sensory techniques. The E-nose was sensitive and as
discriminating as the human nose, and it also correlates
extremely with GC/MS data. The electronic nose allows to
transfer expert know ledged from highly trained sensory
panels and very sophisticated R&D analytical techniques
to the production floor for the control of quality. Although
the human nose is very sensitive, it is highly subjective.
The E nose offers objectivity and reproducibility.
The electronic nose technology goes several steps
ahead of the conventional gas sensors. The electronics
nose system detects and sensing devices with pattern
recognition sub system. The electronic nose won quickly
considerable interest in food analysis for rapid and reliable
quality classification in manufacturing testing. Later, the
electronic noses have also been applied to classification of
micro organisms and bio-reactor monitoring. Even though
the electronic nose resembles its biological counter part
nose too closely the label electronic nose or E-nose has
been widely accepted around the world.
Electronic Nose
THE BIOLOGICAL NOSE
To attempt to mimic the human apparatus,
researchers have identified distinct steps that characterize
the way humans smell. It all begins with sniffing, which
moves air samples that contain molecules of odors past
curved bony structures called turbinate. The turbinate
create turbulent airflow patterns that carry the mixture of
volatile compounds to that thin mucus coating of the
nose s olfactory epithelium, where ends if the nerve cells
that sense odorants.
The volatile organic compounds (VOCs) basic to
odors reach the olfactory epithelium in gaseous form or
else as a coating on the particles that fill the air we
breathe. Particles reach the olfactory epithelium not only
from the nostrils but also from the mouth when food is
chewed.
As VOCs and particles carrying VOCs pass over the
mucus membrane lining the nose, they are trapped by the
mucus and diffuse through to the next layer, namely, the
epithelium, where the sensory cells lie in wait. The cells
are covered in multiple cilia- hair like structures with
receptors located on the cells outer membranes. Olfactory
cells are specialized neurons that are replicated
approximately every 30 days.
Posts: 57
Threads: 29
Joined: Oct 2009
Reputation:
0
[attachment=6191]
Electronic Nose
ABSTRACT
The harnessing of electronics to measure odor is greatly to be desired. Human panels backed up by gas chromatography and mass spectrometry are helpful in quantifying smells, but they time are consuming, expensive and seldom performed in real time in the field. So it is important that these traditional methods give way to a speedier procedure using and electronic nose composed of gas sensors. Electronic nose or E-noses are the systems that detect and identify odours and vapours, typically linking chemical sensing devices with signal processing, pattern recognition and artificial intelligence techniques which enable uses to readily extract relevant and reliable information.
INTRODUCTION
The electronics field is developing at a fast rate. Each day the industry is coming with new technology and products. The electronic components play a major role in all fields of life. The scientists had started to mimic the biological world. The development of artificial neural network (ANN), in which the nervous system is electronically implemented is one among them. The scientists realized the importance of the detection and identification of odor in many fields. In human body it is achieved with the help of one of the sense organ, the nose. So scientists realized the need of imitating the human nose. The concept of the electronic nose appeared for the first time in a nature paper by Persuade and Dodd (1982). The authors suggested and demonstrated with a few examples that gas sensor array responses could be analyzed with artificial neural networks thereby increasing sensitivity and precision in analysis significantly. This first publication was followed by several methodological papers evaluating different sensor types and combinations. The scientists saw the last advances in the electronic means of seeing and hearing. Witnessing this fast advances they scent a marker for systems mimicking the human nose. The harnessing of electronics to measure odor is greatly desired. Human panels backed by gas chromatography (GC)/ mass spectroscopy (MS) are helpfulin quantifying smells. The human panels are subject to fatigue and inconsistencies. While classical gas chromatography (GC)/ mass spectrograph (MS) technique separate quantify and identify individual volatile chemicals, they cannot tell us if the components have an odour. Also they are very slow. So it is important that faster methods must give way to speedier procedure using an electronic nose composed of gas sensory. The E-nose was developed not to replace traditional GC/MS and sensory techniques. The E-nose was sensitive and as discriminating as the human nose, and it also correlates extremely with GC/MS data. The electronic nose allows to transfer expert know ledged from highly trained sensory panels and very sophisticated R&D analytical techniques to the production floor for the control of quality. Although the human nose is very sensitive, it is highly subjective. The E nose offers objectivity and reproducibility. The electronic nose technology goes several steps ahead of the conventional gas sensors. The electronics nose system detects and sensing devices with pattern recognition sub system. The electronic nose won quickly considerable interest in food analysis for rapid and reliable quality classification in manufacturing testing. Later, the electronic noses have also been applied to classification of micro organisms and bio-reactor monitoring. Even though the electronic nose resembles its biological counter part nose too closely the label electronic nose or E-nose has been widely accepted around the world.
Posts: 71
Threads: 29
Joined: Aug 2009
Reputation:
0
[attachment=5010]
Introduction
Electronics nose
Over the last decade, electronic sensing or e-sensing technologies have undergone important developments from a technical and commercial point of view. The expression electronic sensing refers to the capability of reproducing human senses using sensor arrays and pattern recognition systems. Since 1982, research has been conducted to develop technologies, commonly referred to as electronic noses, that could detect and recognize odors and flavors. The stages of the recognition process are similar to human olfaction and are performed for identification, comparison, quantification and other applications. However, hedonic evaluation is a specificity of the human nose given that it is related to subjective opinions. These devices have undergone much development and are now used to fulfill industrial needs.
Posts: 39
Threads: 15
Joined: Oct 2009
Reputation:
0
Posts: 59
Threads: 29
Joined: Aug 2009
Reputation:
0
respected sir/mam
I am student of bachelor of technology from electronics and communication enggineering.i want more description about electronic nose mainly about its sensors like calorimetric sensors,conducting sensors,piezoelectric sensors,chemical sensors.
please mail me description about these things .
thank you.
my email address is [email protected].
thank you.
Posts: 65
Threads: 26
Joined: Jul 2009
Reputation:
0
|
