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IEEE Instrumentation and MeasurementTechnology ConferenceBudapest, Hungary, Ma y 21-23,2001.

Tin Oxide Gas Sensing: Comparison Among Different Measurement Techniques forGas Mixture ClassificationA.Fort,N.Machetti, S.Rocchi, B.Serrano#, L.Tondi, N.Ulivieri, V.Vignoli and G.Sberveglieri*

Dept. of Information EngineeringSiena 53100, ITALYPhone: +39 0577 233608, Fax: +39 0577 233602Email: ad a@ing.unisi.it, URL: http://www.dii.unisi.it# Dept. of Earth SciencesSiena 53100, ITALYPhone: +39 0577 233831, Fax: +39 0577 233938Email: serrano@u nisi.it,URL: http://www.dst.unisi.it* INFM and University of BresciaBrescia 25 133, ITALYPhone: +39 030 3715708, Fax: +39 030 2091271Email: sberveglieri@bsing.ing.unibs.it,URL: http://www.unibs.it

Abstract - n this paper a study is presented aiming at the se-lection of the most appropriate measurement technique fo r wineclasszjkation. In particular the problem of detecting typicalwine aroma components in mktu res where ethanol is present istaken into account. Literature proposes different solutions inorder to enhance metal-oxide sensor selectivity. An interestingapproach concerns the application of different measurementtechniques. In this work three methods based on chemical tran-sient, AC m easurements and temperature modulation have beeninvestigated.Kevwords - Electronic nose, semiconductor gas sensor, tem-perature m odulation, chemical transients.

I. INTRODUCTIONElectronic noses are comp lex systems for odo r classifica-tion whose structure is som ewhat inspired to the m amm al-ian olfactory system. The basic concept, to which they arebased is to use a sensor array made up of many sensingelements. The selectivity of each element is low, never-theless the com bination of the respon ses of many differentelements with different sensitivities has a characteristicpattern that can be seen as a signature of each differentchemical mixture responsible for a given aroma. The elec-tronic nose structure comprises the sensor array, a condi-tioning and signal processing electronic system aiming atenhancing the array sensitivity (analogue and digital pro c-essing) and finally a classifier that performs a comparisonwith a reference data-base. Obviously, the database cannotbe exhaustive (due to noise, sensor response drifts etc.)hence the comparison is performed by complex algorithmsable to generalize (e.g. neural networks, fuzzy system s).Conductive sensors change their conductivity when react-ing with oxidizing or reducing gases. Amo ng variable con-ductivity transducers, Metal Ox ide Sensors (MOX) are oneof the most popular technological choice. These sensorsvary their conductivity in presence of oxidizing and re-0-7803-6646-8/011$10.002001 EEE

ducing gases, because the ab sorption and desorption of 0-,Oy, 02- t the sensor surface changes the electron densityat the semiconductor surface; adsorbed oxygen gives riseto potential barriers at grain boundaries and thus increasesthe resistance of the sensor surface, on the other hand re-ducing gases decrease the oxygen surface concentrationand hence the sensor resistance. The magn itude of the re-sponse depends on the nature and concentration of thevolatile molecules, and on the type of metal oxide. Mainadvantages of metal oxide sensors are a high sensitivity, along term stability and the possibility of integration. Themain disadvantage is the high operating temperature (200 -500C)equired to allow chem ical reactions.Even if some instances of electronic noses are commer-cially available, there is still much interest in the researchfield. Man y research groups work on sensor technolog y, onthe development of measurement techniques and of dataprocessing algorithms. An interesting topic concerns theenhancement of sensor selectivity. Here many solutionscan be envisaged. An interesting approach concerns ex-ploiting different measurement techniques. It is well estab-lished that good results can be achieved by m easuring thetransducer conductivity variations during chemical tran-sient obtained with abrupt changes in odor concentration.In fact in this case the reaction kinetics can be exp loited todifferentiate among different compounds. An alternativemethod was presented in many works in the last yearsshowing that changing the operating temperature of theSn 02 sensors allows to modify their response to a givenchemical species or mixture [ l]. Since the optimum oxida-tion temperatures are different from gas to gas, operatingthe transducer at two different temperatures is equivalent touse two different transducers. A further technique concernsAC measurements. By measuring the complex impedanceof the sensor it is possible to highlight different physicaland chemical effects [2] which can differentiate among

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chemical species. In this paper the application of thesethree measurement techniques to the recognition of mix-ture containing ethanol is presented. The purpose is theselection of the m ost appropriate technique for w ine classi-fication.11. MEASUREMENT SYSTEM

The results presented in this paper are obtained by meansof a laboratory electronic nose, based on a SnOz sensor ar-ray which comprises a headspace and an electronic system.The latter was designed to allow for a versatile use withdifferent metal oxide sensors and measuring techniques.The system is fully software controllable and reconfigu-rable, it allows to perform measurements with an array ofup to 16 elements, it permits measurements during chemi-cal transient, it can operate as a vectorial impedance meterin a frequency range spanning from DC to 1 5 MHz and fi-nally it can measure the gas sensor sensitivity when thetemperature follows an arbitrary-defined profile. The basicidea is to exploit the flexible structure of the developedlaboratory system to explore the potentials of the aboveproposed measurement techniques in conjunction with theusage of different kinds of SnOz sensors. This system wasdesigned to be the experimental base for the developmentof special purpose electronic noses. The gas-sampling unitis a digitally controlled system providing the possibility toinject the desired odor into the headspace and to control thegas flow. Odors in both liquid and gas phase can be ana-lyzed. Liquids to be tested are volatilized by a Drechselbottle in a carrier gas. A known flow (50-200 dmin) freference gas (synthetic air) continuously invests the sen-sors. During measurements, the system controls three-fluxcontrollers to choose between the reference gas and thesmell to be tested, and it also controls the smell concentra-tion. The sensors are arranged in a cylindrical symmetryconfiguration orthogonal to the gas flux, so that each ofthem receives the same controlled flux of the aroma-carrying gas. In this way, problems with the decay ofVOCs or with the appearance of com bustion products ob-served for serial sensor arrangements can be excluded.

111. RESULTSFor this study an array of 8 gas sensors was used: 4 Tagu-chi sensors (TGS2600, TGS20601, TGS2610, TGS2620)and 4 Sn 02 sensors produced by the Thin Film L ab of theUniversity of Brescia (2 sensors doped with gold andplatinum and 2 undoped sensors). The S n 0 2 sensors aresensitive to the presence of ethanol, and a high concentra-tion of ethanol in a chemical mixture tends in general tosaturate their responses. A possible solution to this prob-lem is the use of wine pervaporation; this procedure canreduce the ethanol content of wine of roughly an order ofmagnitude. A pervaporated wine can therefore contain lessthan 1%of ethanol [3]. For this reason, in this work we in-

vestigate the possibility of detecting odors in water solu-tions wei-e the ethanol con centration is lower than 1%.The ability to discriminate among six different solutions isinvestigated: (#1: solution of water with 1% of ethanol, #2:solution of water with 1% of ethanol and 0.05% of ethylacetate, #3: solution of water with 1% of ethanol and 8g/lof Glycerol, #4: solution of water with 0.2% of ethanol, #5:solution of water with 0.2% of ethanol and 0.05% of ethylacetate, #6: solution of water with 0.2% of ethanol and 8gflof Glycerol).A . Chemical transientsSensor resistance is measured during chemical transients.The m easurement protocol is the following: 1 min. of syn-the ti c a ir (200 d m i n ) , 1 min . of smell (30 d m i n ) insynthetic air (170 d m i n ) and 12 min. of synthetic air (200d m i n ) . In general the steady state is not reached duringthe phase of odor injection.The sensor dynamic behavior (see Fig. 1) was modeledwith two expone ntial functions of the following type:

R ( t )=a+b . e x p [ c . t o - t ) ] . (1)In this way six parameters (a,b,c for the falling transientand for the rising transient) are extracted for classification.In Fig. 2.a the parameter c is plotted versus parameter a fo rthe falling transient, due to odor injection, for theTGS2611 sensor: it can be seen that discrimination is ob-tained essentially by parameter a , while parameter c varia-tions are very close to the noise level. A discrimination isobtained also by analyzing the recovery transient due toinjection of synthetic air in the headspace after odor pulse.Actually the measurements depend both on the sensorsbehavior and the chamber kinetics. In Fig. 2.b. the pa-rameter c is plotted versus parameter b for the rising tran-sient for the Sn386G(Pt) sensor.It can be observed that the odor presence and the ethanolconcentration modifies the final resistance values and af-fects slightly the dynamic behavior. Moreover each sensoris sensitive only to the presence of ethylacetate.B . AC measurementsAs already said, the system operates as a vectorial imped-ance-meter in a frequency range spanning from DC to 15MHz. T he impedance measurement is obtained in chemicalsteady state conditions: smell (30 d m i n ) in synthet ic ai r (170 i n ) . In this case, this measurement techniquedoesnt give any further information with respect to themeasurement technique described in the above section. Infact the sensors show a low resistance values. Hence theeffect of the parallel capacitances cannot be seen in the in-vestigated frequency band.

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Fig. 1.Transient sensors' responses normalized with respect to the impedance value in air 20.

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Fig. 2. a) TGS 2611 sensor response during odor injection represented by mean s of two of the parameters defined in (1).b) Sn386G University of Brescia Ptdoped sensor response du ring recover represented by means of tw o of the parameters defined in (1).

C . Variable sensor Temperature.It was already proved that sensor temperature modulationsimprove selectivity, in fact the single sensor operated atdifferent temperatures behaves as different sensors withdifferent doping. Moreover the dynam ic response of a sin-gle sensor to the operating temperature variation can givefurther selectivity enhanceme nt [11. Different factors suchas the rate of surface decom position of reducing gases andthe charge carrier concen tration contribute to the dynam icresponse. From a macroscopic point of view the mecha-nisms which contribute to changes in the sen sor resistanceas a function of the temperature can be divided into twoclasses: fast phenomena, essentially related to the change

of free electron number (NTC or PT C behavior) and slowphenomena, e.g. absorption and desorption of oxygen atthe sensor surface. The two mechanisms can be observedby measuring the sensor response when exciting the sen-sors heater with voltage pulses with different amplitudesand d urations, while chemical conditions are maintained ina steady state (in our case the odor is present with a 30d m i n lux in the carrier syn thetic air 170d m i n ) . I n Fig .3 the response of TGS2600 and TGS2611 in presence of1% of ethanol are shown: it can be seen that the NTC oef-ficient for the second sensor is considerably smaller thanthe NTC oefficient of the first one, and that, for this sen-sor, the slow phenomena are more im portant. The respo nseto pulsed temperature can be used to select the most suit-able temperature excitation waveforms.

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TGS26W

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20 40 60 80 1001600 Time (s)

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Fig. 3 . a) Transient response of TGS2600 andb) TGS2611 to l%EtOH during temperature puls es. c ) Heater voltage.

IV. CONCLUSIONSParticularly interesting results can be obtained by usingsinusoidal waves. In this case the difference in the dy namicbehavior of the sensors in presence of the considered threesolutions becomes relevant. The experimental results ob-tained with two sine waves with the same amplitude butdifferent periods are represented in Fig. 4. t can be seenthat when thermal excitation is much faster than chem icalreactions, the sensor response is determined essentially bythe NTC S n 0 2behavior. On the o ther hand, a larger distor-tion, with a pattern characteristic for a given odor is pres-ent when the therm al variation dynamic is slower.

In terms of discrimination power, experimental resultspoint out that measurements performed by exciting thesensor heater with sine waves give better results thanmeasurements in chemical transients. Moreover, only thelatter type of measurements allow a significant glycerolrecognition. Obtained results also show that the tempera-ture sine wave period must be chosen in agreemen t to thechemical reaction rate of e very sensor.

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Fig. 4. a) Sensor resistance versus time when the temperature is a sinusoidal input with duration 40 s (left) and 180 s (right). b)Temperature profile of theTGS26 11 sensor (40 s and 180 s).REFERENCES

[11 A.P.Lee, .J.Reedy, Temperature modulation in semiconductor gassensing, Sensor and actuato rs,B 60, p.35-42, 1999.[2] W. Gopel, K.D. Schierbaum, Sn02 Sensors:current status and fu-ture prospects, Sensors and Actuators, B 26-27, p.1-12, 1995.[3] C.Pinheiro, T.Schaefer, C.M. Rodrigues, A.Barros, S.Rocha,LDelagadillo, Integrating pervaporation with electronic nose formonitoring the muscatel aroma production, Proc. of the 7*Inter-national Symposium on olfaction and electronic nose, p.145,2000.

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