Microsensors often do not have the selectivity to chemical species available in large laboratory instruments. A new type of pattern recognition algorithm is used to classify mixtures of H{sub 2} with NO{sub 2} and O{sub 2}. The microsensors used are thin film catalytic metal field effect transistors and chemiresistors on the Sandia Robust Sensor platform. For this study pure Pd thin films and Pd/Ni alloys are shown to provide good classification of mixtures containing NO{sub 2} from those containing O{sub 2} or no oxidant

Bartholomew, J.W.

Hughes, R.C.

Osbourn, G.C.

Rodriguez, J.L.

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O S i l  THE DETECTION OF MIXTURES OF NOx'S WITH HYDROGEN USING CATALYTIC METAL FILMS ON THE SANDIA ROBUST SENSOR WITH PATTERN RECOGNITION. R. C. Hughes, G. C. Osbourn, J. W. Bartholomew, and J. L. Rodriguez Sandia National Laboratories, Microsensor Dept. MS 1425, Albuquerilue, NM, 871 85, USA. I I SUMMARY Microsensors often do not have the selectivity to chemical species available in large laboratory instruments. A new type of pattern recognition algorithm is used to classify mixtures of H, with NO, and 0,. The microsensors used are thin film catalytic metal field effect transistors and chemiresistors on the Sandia Robust Sensor platform. For this study pure Pd thin films and Pd@i alloys are shown to provide good classification of mixtures containing NO, from those containing 0, or no oxidant. INTRODUCTION Since the discovery 20 years ago of the hydrogen sensitivity of palladium gated field effect structures by Lundstrijm, et a1 [I], many variations on the basic thin film catalytic metal have appeared in the literature. It was found that various kinds of thin film structures produce sensitivity to hydrogen containing molecules and mixtures of oxidants with those reductants. Sensitivity to ammonia is achieved with several combinations of very thin metals (Pt) with thicker contact layers [2].  Ethanol and methanol have been done with pattern recognition of large area field effect structures with metal and temperature gradients and light response images [3]. CO can be selected by modified gate structures of Pd and Pt [4]. Suspended gate structures can detect vapors that enter the gap between the suspended gate material (which can  be a conducting polymer or other metals) and the FET , insulating surface [5].  In this paper we describe results , obtained with combinations of catalytic alloys and the use of a new pattern recognition algorithm which had not previously been used with data from catalytic metal gas sensors. EXPERIMENT The Sandia Robust Hydrogen Sensor (SRH) provides a manufacturable electronic platform for a wide variety of catalytic alloys. The fabrication steps have been given previously [GI, and the response to IH2-02 mixtures has also been detailed r71 The field effect transistor (FET) on the chip gives good information about low partial pressures of H, (pH,), but its logarithmic response limits the accuracy at higher pH2 values. The resistors made of the same catalytic alloy are hot accurate at low values, but give a response that is rohghly linear in the square root of pH, at higher pressures. However, the signal from a given pH, may change if an oxidizing agent is present, like 0, or NO, concentration of these reactants is high enough, flammable mixtures occur. Lower concentrations of NOx are of interest for pollution control. We have found that mixtures of oxidizing and reducing agents do not always give the same sensor response on sensors with different catalytic alloys, for example pure Pd vs. alloys of Pd with Ni. We have used a five sensor array with the Sandia pattern recognition algorithm [8] to classify. H, mixtures with NO, vs. 0,. The five sensors include a pure Pd field effect transistor(FET) and resistor, a separate SRH Pd/Ni(9%) FET and resistor and a Nyad electrochemical oxygen sensor (commercial product). We have found that the Nyad sensor only responds to PO, and gives the correct value, even with the highest pH, and the pN0, values studied here (up to 200 ppm). One of the tasks of the pattern recognition algorithm is to treat sensor array data with an arbitrary number of sensor inputs. Thus each of the five sensors described can be a sensor input, and each of the SRH sensors operating at a different temperature can be a sensor input. The algorithm decides how many sensor inputs are required to give a classification of the gas mixture seen by all the sensors. RESULTS As an example of classification, Fig. 1 shows how mixtures containing NO, can be distinguished from mixtures with 02. or no oxidant at all (only H2). This three dimensional plot only uses three of the sensor inputs, the Pd resistor (SOOC), the pd/Ni FET(80"C) and on the vertical axis, the oxygen sensor. The three Classes chosen are 1) I<, - open circles, 2) H, w/ 02. - shaded circles. and 3 )  13, w/ NO, - solid circles. From the five L O2 Sensor i. f H2 w/ NO, i I  Figure I .  Three dimensional pattern recognition plot showing classification of mixfures. Each dot is for a specific mixture with the highest PO, (20%) and.pH2 (4%) appearing in the upper left hand corner. Note the grouping of all the pH, concentrations with NO2 in the lower right hand corn8w. the greatest class separation was chosen. The - classification algorithm equalizes the maximum responses of each of the three sensors. Since the 0,. sensor ' separates 0,. concentrations exclusively, only the two ' remaining sensor responses are normalized to provide a vector response. The resulting spread of classes lie on a cylindrical surface with the 0,. sensor axis as the axis of rotation. The PdNi FET sensor and Pd Resistor sensor separate the different concentrations of H,. This initial classification does not reveal the concentration of the various gases, but clusters them in a class; the solid circle cluster for H2 /NO2 contains many different H, and NO, concentrations. Once classification (Le. the presence of certain molecules) is performed, a separate algorithm can be used to estimate individual concentrations. In this way, flammable mixtures of H, and Q,. we ! ! from non-flammable mixtures, a very important application of the array technique. The detailed response of the various catalytic metals to the gas mixtures has not been predictable from any theory of catalysis. The temperature dependence of the responses to both 0,. [7]  and NO2 were unexpected (but reproducible). The basic feature of the data that allows the classification is that the presence of small values of NO, blocks the signal from a given pH2 on a pure Pd surface much more than on the Pd/Ni surface. As an example of this kind of data, Fig. 2 shows the response of the two kinds of catalytic resistors to a series of pulses of pH, and pNO,. Each pulse lasts for 5 min. followed by 5 min. of purging with dry air. The upper trace is from the Pd resistor and it can be seen that a mixture of 5000 ppm DISCLAIMER Portions of this document may be illegible in electronic image products. Images are produced from the best available original document. I 2.5 2 1.5 1 0.5 0 1000 2000 3000 4000 5000 6000 Time (sec) . .  Figure 2. Resistor responses to 5 min. pulses starting with air. The top data is for the Pd resistor and bottom is for  the PdNi resistor. The baselines have been oflset for clarity; the first 5 min. establishes the baseline, which is the resistance aJer a 15 minute purge at 140°C in air. 0.2, . . .  : . . . I . . .  ( . . . I .  . , I . .  , 8O'C 0" 0" z z 2 Q 0 0 -0 VI 0" B P z E c 0" z h 0 0 N0.1 0.0 1 2" z" I" I" E L y! y! c - c - 0 0 P a. 2" r" I" I" x % y! v! e c - -0 0 " n  - 0  -0.1 -0.2 -0.3 - P d  FET . P d l N l  FET -0.4 -0.5 . . . .  _ _ . .  . . . .  . . . .  . _ . .  . . . .  . . . .  . . . .  .___.__. . _.._._. ..... .. . . . . . . . . . . . . . . .. .. . . .  . . .. . .. : Time (sec) Figure 3. PdNi and Pd FETs operating at8O"C; the individual data points at 10 second intervals are shown for the Pd FET and a dashed line through the points for the P d N i  FET Five minute pulses of H2 mixiures alternate with S minutes of dty air. The introduction of each new mixture is indicated by the arrow. The data were faken at the same time as those for the resistors in Fig. 2. The zero is defined as the FET threshold voltage afier a I5 minute purge at 140°C in air; all H2 containing mixtures cause the threshold voltage io move in a negative direction. In a rouhe  run for use in the pattern recognition algorithm calibration pulses of H ,  are given before and afier exposures to mixtures wifh NO2 to make sure that ihe calibration of the sensor holds.afies exposure to NOI. - . ~ . . .  . pH, with 100 ppm pN0, gives no response, while the Pd/Ni resistor gives a reduced (from no NO,) but easily measured response. Calibration pulses before and after the run, shown in the Fig. establish that the Pd sensor is still operating, normally when no NO, is present. Fig. 3 shows the response of the two FETs during the same run. The suppression of the signal on the Pd FET when NO, is present is consistant with the signal from the Pd res istor. CONCLUSIONS The training set for the pattern recognition comes from many such pulses for different gas concentrations and sensor temperatures. This means that a considerable experimental data base must be obtained on a wide variety of gases, concentrations, sensor alloy compositions and temperatures. The data base will allow the algorithm to be used effectively in an ever wider number of commercial, industrial and military applic’ations, and may also allow us to model the behavior of the sensor responses to enhance the predictive power to ranges of mixtures not tested. ACKNOWLEDGMENTS We would like to thank Paul McWhorter and Sandia colleagues and support staff in the Sandia Microelectronics Development Lab (MDL) for their work on the design, fabrication and testing of the SRH sensor chip. Special thanks to Mark Jenkins for the construction of the gas sensor test bed and the data acquisition software that makes it possible to supply large amounts of sensor data to the pattern recognition algorithm. This work was perfcirmed at Sandia National Laboratories and was supported by the US. Department of Energy under Contract No. CIE-AC04-94AL85000. ! REFERENCES [I] I. Lundstrom, M. Armgarth, and L.-G. Petersson, CRC Critical Reviews Solid State Materials Science, 15 (1989) 201-278. [2] A. Spetz, M. Armgarth and I. Lundsmrn, Sensors and Materials 1 (#4) 187-207 (1988) [3] I. Lundstrom, H. Sundgren and F. Winquist, Digest of T e c h .  Papers, the 7th Lnt. Conf. Solid State Sensors and Actuators, Transducers ‘93 (Yokohama, Japan, June 7-10, [4] K. Dobos, R. Strotman and G. Zhmer ,  Sensors and Actuators 4 (1983) 593-598. 1993) pp. 416-419. [SI J. Li, D. Petelenz, and J. Janata, Electroanalysis (N 3, 5, (9-lo), (1993) 791-794. [6] J. L. Rodriguez, R. C. Hughes, W. T. Corbett, and P. J. McWhorter, “Robust, Wide Range Hydrogen Sensor”, in IEDM Tech Digest, IEEE cat. # 92CH3211-0, San Francisco, CA, Dec. 13-16, 1992, pp. 521-524. [7] R. C. Hughes, D. J. Moreno, M. W. Jenkins, and J. L. Rodriguez, “The Response of the Sandia Robust Wide Range Hydrogen Sensor to H,-0, Mixtures”, Technical Digest, Solid State Sensor and Actuator Workshop (Hilton Head Island, South Carolina, June 13-16, 1994) pp- 57-60. [8] G,C. Osbourn, J. W. Bartholomew, G. C. Frye, and A. J. Ricco, “Clustering-Based Pattern Recognition Applied to Chemical Recognition Using SAW Array Signals”, Technical Digest, Solid State Sensor and Actuator Workshop (Hilton Head Island, South Carolina, June 13- 16, 1994) pp.193-196. 1 I DLSCLAIMER This report was prepared as an account of work sponsored by an agency of the United States Government. Neither the United States Government nor any agency thcreof, nor any of their employees, makes any warranty, express or implied, or assumes any legal liability or responsi- bility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately owned rights. Refer- ence herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recom- mendation, or favoring by the United States Government or any agency thereof. The views amd opinions of authors expressed herein do not necessarily state or reflect those of the IJnited States Government or any agency thereof. I 

The detection of mixtures of NO{sub x}`s with hydrogen using catalytic metal films on the Sandia Robust Sensor with pattern recognition

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