MICRO STRUCTURE WORKSHOP 2004
SCALING PROPERTIES AND MEMS IMPLEMENTATION OF ACOUSTIC GAS SENSORS Bertil Hök1, Anders Blückert1, Vegar Dalsrud2, Per Gerhard Gløersen2, Geir Uri Jensen3, Daniel Lapadatu2, Andreas Vogl3, Dag T. Wang3, Trond Inge Westgaard2, Per Åkerlund1, Niels Peter Østbø3 1 Hök Instrument AB, Flottiljgatan 49, SE-721 31 Västerås, Sweden Phone: +46 21 80 00 99, Fax: +46 21 80 07 22 E-mail:
[email protected] 2 SensoNor AS, Box 196, N-3192 Horten, Norway 3 SINTEF Electronics and Cybernetics, Department of Microsystems, Box 124 Blindern, N-0314 Oslo, Norway
Abstract The scaling properties of acoustic gas sensors indicate a design window from tens of micrometers to several millimeters in critical feature size, thus favouring a bulk micromachining approach. The first MEMS implementation using a triple-stack glass-silicon-glass process is reported, with highlighted experimental results from prototype design and processing runs. This technology platform is believed to generate new application opportunities within the fields of indoor air quality monitoring and control, respiratory diagnostics and monitoring, and automotive climate control.
Introduction Acoustic gas sensors are useful devices [1] for industrial monitoring and control. The dependence on a physical property, the velocity of sound, provides important advantages compared to devices depending on catalytic or other chemical properties. These sensors thus belong to a class of gas sensing devices, shared by thermal conductivity sensors, and devices based on infrared spectroscopy. The acoustic dimension offers several important opportunities, such as modest demands on mechanical precision, and high reliability even in severe environments. Successful industrial applications are ranging from humidity monitoring and control of drying processes [2] to indoor air quality (IAQ) control [3]. The potential applicability is, however, much wider [4]. The possibility of combining small size, fast response, and low production cost in a prospective MEMS (micro electro-mechanical systems) approach, would provide new opportunities in medical applications, e g respiratory diagnostics and monitoring. Automotive air conditioning systems is another possible application area of growing interest, in which low cost, environmental durability, and high reliability are important issues. This paper represents the first public report of a cooperative effort by SensoNor AS, SINTEF,
and Hök Instrument AB in exploring MEMS implementation of acoustic gas sensors. The project with acronym MASCOT (Micro Acoustic Sensor Systems for CO2 Tracking) is particularly focussing on CO2 sensing in air, although the application range could be extended to other gases as well. In this paper, we will present the physical scaling properties of acoustic gas sensors in a general context. The analysis is based on fundamental physical relations, which may also act as design guidelines. One approach to MEMS implementation of acoustic gas sensors will be presented, and its possible future implications will be briefly discussed.
Scaling Properties The basic relation of gas sensors directly follows from the solution of the wave equation in an ideal gas, resulting in the following classical relation:
c=
kTγ m
(1)
where c is the velocity of sound, k=1.38*10-23 J/K is Boltzmann’s constant, γ is the ratio of specific heat at constant pressure and volume,
SCALING PROPERTIES AND MEMS IMPLEMENTATION OF ACOUSTIC GAS SENSORS
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YSTADS SALTSJÖBAD
respectively, and m is the molecular mass. Eq. (1) clearly indicates the usefulness of acoustic sensors in binary gas mixtures. By measuring the velocity of sound, the constitution of a binary mixture with known constituents can be determined. With certain restrictions, CO2 in air could be considered a binary mixture, and their differing and known molecular masses form the basis of the determination of CO2 concentration. The velocity of sound can e g be measured by pulse-echo techniques, but in this paper we will focus on devices using an acoustic resonator, the resonance frequency of which is related to the velocity of sound. There are two basically different types of such resonators. The first type can be described by a lumped parameter model, incorporating inertial and compliant elements. The classical Helmholtz resonator is a prominent member of this family, including a compliant gas volume V, and a neck with cross section area A and length ℓ as combined inertial and dissipative element. The resonance frequency fr and Q factor of a Helmholtz resonator is given by [5, 6]:
fr =
c 2π
Q=a
A l ⋅V
π ⋅ fr µ
(2)
(3)
The expression for Q involves only viscous loss, µ being the kinematic viscosity of the gas (µ=1.56*10-5 m2/s in air at 0°C and 1 bar). The metric parameter a is identical to the neck radius in the ideal Helmholtz resonator with a circular cross section, but may include other dependencies in more complex geometries. The second type of resonator is based on standing waves in the gas, reflected from walls of the sensor enclosure. The classical Kundt’s tube with closed ends represents the simplest one-dimensional geometry, and exhibits numerous resonance modes given by the following relation:
f rN =
Nc , N = 1,2,3,... 2L
(4)
L is the tube length, and N is the mode number. The general expression for Q (eq. (3)) due to viscous loss also holds for this type of resonator, but in addition, other effects may
HÖK ET AL.
have to be considered, especially at high frequencies. Also, the interpretation of the metric parameter a becomes less obvious. From the perspective of scaling properties, eqs. (2)-(4) provide a basis for optimum performance. The formal similarities of eq. (2) and (4) should be noted. They are both essentially based on the velocity of sound divided by a metric entity. In the lumped parameter case, this metric entity should be considerably less than the acoustic wavelength at the frequency of operation (otherwise it will turn into the second type of resonator, involving standing waves). Decreasing the metric dimension by miniaturisation leads to improved performance due to increasing resonance frequency. The reduced dead volume of the device also leads to improved response time. On the other hand, Q is adversely affected by miniaturisation as indicated by the parameter a. More detailed quantitative analysis shows that there is a design window extending from a few tens of micrometers to several millimetres, in which acoustic sensors may have favourable characteristics. Outside this range, Q factors will be too low. In addition to a resonating element, an acoustic gas sensor also requires an activating element (‘loudspeaker’), and a readout element (‘microphone’) in order to determine the resonance frequency. From a fundamental point of view, these elements could be considered invariant to scaling. Decreasing the diameter of a diaphragm can, in principle, always be matched by decreasing its thickness in order to retain its properties. Of course, technological limitations may have to be taken into account, but that is another issue. From this analysis, it is clear that MEMS implementation of acoustic gas sensors is favourably performed in a bulk rather than surface micromachining context. Very little, if anything, is gained by feature sizes in the nanometer range.
MICRO STRUCTURE WORKSHOP 2004 MEMS Implementation
The detailed design was based on finite element modelling in the mechanical, thermal and acoustic domains. The devices were also modelled with respect to parasitic signal coupling. Two design runs have been consecutively performed so far, followed by experimental characterisation of the device properties. A few highlights from these concurrent activities will be presented below.
Utsigna l (10=50 uV)
The MEMS implementation reported in this paper is based on one of SensoNor’s triplestack glass-silicon-glass bulk micromachining processes. Before designing prototypes, various basic schemes were analysed, resulting in a limited number of device versions that were actually implemented. Cavities to define resonating elements were designed either in glass or silicon, or both. In glass, the cavity geometry was defined by isotropic etching, whereas anisotropic etching incorporating a pn junction etch-stop technique in silicon was used for defining diaphragm structures for activation and detection. Aligned anodic bonding was performed, following SensoNor’s standard process. Resistive elements were used both for activation and detection, the latter using the piezoresistive effect in silicon.
LP-A; FG -inst: 8Vp-pAC sinus 0Voffset; 20-120kHz(10-60); 500H z (250H z) m ellan sampel; 7,8VD C; 1s m ellan sampel; flat ingångsfilter; 100m s slutfilter; vektorrepresentation; mätning 3; r um stemperatur, 21,4°C; 2003-11-04 10
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Figure 2. Frequency characteristics of prototype sensor element in air at room temperature, exhibiting an acoustic resonance at 40 kHz. Fig. 2 shows the experimental frequency characteristics of a prototype sensor element, such as that shown in Fig. 1. The recording was made in air at room temperature, and clearly displays two resonance peaks, one at 40 kHz, and one at 108 kHz. The first one, exhibiting a Q factor of 6.5 has acoustic origin, whereas the second one represents the mechanical eigenfrequency of the detection diaphragm. It was designed to avoid the acoustic resonance, or any of its harmonics. The peak amplitude is approximately 30 µV when driving the sensor with an 8 volt sinusoidal waveform. LP-A; sn01; FG-inst: 8Vp-pAC sinus 0Voffset; 25-45kHz(12,5-22,5); 200Hz (100Hz) mellan sampel; 7,8VDC; 1s mellan sampel; flat ingångsfilter; 100ms slutfilter; vektorrepresentation; mätning 7; rumstemperatur, 21,5°C; 31% RH; CO2; 2003-11-06 8
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Figure 1. Prototype acoustic gas sensor in a ceramic package. The die area is 3 x 3 mm2. Fig. 1 shows a prototype sensor die mounted in an open ceramic package, with attached bonding wires. The die includes bonding pads connected to the resistive activating element, and a Wheatstone piezoresistive bridge for signal detection. The die area of 3 x 3 mm2 is not minimised but conformed to a multiproject wafer (MPW) environment.
Figure 3. More detailed frequency plot of the same element as in Fig. 2 in CO2 at room temperature. The acoustic resonant peak moves from 40.3 to 32.6 kHz. Fig 3 shows a recording in CO2 at room temperature of the same element as that in Fig 2. The resonance frequency drops from 40.3 to 32.6 kHz, while Q increases from 6.5 to 8.1. These results are in excellent agreement with theoretical expectations based on eq. (1) and (3). The kinematic viscosity of CO2 is lower than that of air.
SCALING PROPERTIES AND MEMS IMPLEMENTATION OF ACOUSTIC GAS SENSORS
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YSTADS SALTSJÖBAD
LP-A; sn01; FG-inst: 8Vp-pAC sinus 0Voffset; 20-130kHz(10-65); 1000Hz (500Hz) mellan sampel; 7,8VDC; 1s mellan sampel; flat ingångsfilter; 100ms slutfilter; vektorrepresentation; mätning 8; rumstemperatur, 21,5°C; 29% RH; Helium; 2003-11-06 200
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Figure 4. Same element as in Figs. 2 and 3 exposed to helium. The acoustic resonance now coincides with the first mechanical eigenfrequency of the detection diaphragm. Exposure of the same element to helium results in the frequency characteristics shown in Fig 4. Now, the acoustic and mechanical resonances coincide, resulting in a much higher signal amplitude, 120 µV, i e a factor 4 higher than in air.
Discussion It was concluded from the analysis of scaling properties that MEMS implementation using bulk micromachining processes is worth exploring. Expected benefits are improved performance, less variation between individual devices, and reduced production cost. Potential application areas are indoor air quality control, automotive and medical applications, as mentioned above. IAQ Small size High resolution Fast response Tough environment Cross sensitivity Selectivity Long term reliability
No Yes No No Yes No Yes
Automotive Yes Yes Yes Yes Yes No Yes
Medical Yes No Yes Yes Yes Yes No
Table. Industrial requirements on gas sensors in three application areas. In the table above, the general and specific requirements of these application areas are summarised, indicating both common and dissimilar elements. Reliability in general terms is required in all three areas, but the unattended operation over decades of a device for IAQ control is basically different from the reliability required in a disposable sensor for medical use. High resolution is required when measuring CO2 concentration against the fresh air background of 370 ppm, whereas the medical
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applications are concerned with percent concentration levels. On the other hand, breathto-breath analysis requires fast response which is of little significance when controlling air quality in localities of reasonable size. Selectivity is more important in medical diagnostics, e g in the presence of anaesthetic agents than in ventilation control; whatever the foreign gaseous agent may be, it should be ventilated. In conclusion: The first successful MEMS implementation of acoustic gas sensors has been presented. Some highlights of experimental results have been disclosed, indicating a wide range of industrial applications; further work is underway.
References [1] P. Hauptmann Sensoren – Prinzipien und Anwendungen, Carl Hanser Verlag, München, 1990, 136-142. [2] L. Zipser, J. Labude “Akustische Gasanalyse. Teil II: Anwendungen”, Technisches Messen 58 (1991) 463-470. [3] B. Hök, M. Tallfors, G. Sandberg, A. Blückert “A new sensor for indoor air quality control”, Eurosensors XII, Birmingham, U.K., 13-16 September 1998, volume 2, pp1072-1075. [4] F. Granstedt Gas Sensing Using an ElectroAcoustic Principle, Licentiate Thesis, Department of Electronics, Mälardalen University, Västerås, Sweden, May 2002. [5] L.E. Kinsler, A.R. Frey, A.B. Coppens, J.V. Sanders Fundamentals of Acoustics, 4th Edition, Wiley, New York, 2000. [6] L. L. Beranek Acoustics, McGraw-Hill, New York, 1954, 128-142.
Acknowledgements This paper is dedicated to the memory of Fredrik Granstedt, whose contributions to this research field were interrupted by his tragic death in a drowning accident on June 21, 2003. The MASCOT project is co-financed by the European Commission (project number IST 2001-32411). Stimulating technical discussions with the reviewers, Professor Julian Gardner, University of Warwick, U.K., Professor Nico de Rooij, University of Neuchatel, Switzerland, and the Project Officer, Dr Rainer Günzler, are gratefully acknowledged.
