MEMS based sensors for indoor environment applications

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MEMS based sensors for indoor environment applications Ralph W. Bernstein, Niels-Peter Østbø SINTEF ICT Bertil Høk Høk Instruments Per G. Gløersen SensoNor ASA 1

The SINTEF Group SINTEF s Council SINTEF s Board President Senior Executive Vice President Executive Vice President of Finance SINTEF Health Research SINTEF ICT SINTEF Marine SINTEF Materials and Chemistry SINTEF Petroleum and Energy SINTEF Technology and Society 2

MiNaLab (Micro Nano Lab) Clean room area: SINTEF: 800 m 2 University of Oslo: 600 m 2 Micro environments, class 10 A full silicon processing line for MEMS and radiation detectors Capacity of 10.000 6 wafers/year 35 employees at SINTEF Located at the campus of University of Oslo 240 MNOK invested in scientific equipment and laboratory infrastructure Funded by Norwegian Research Council and SINTEF 3

MiNaLab offer One of two silicon processing lines in Norway. The only independent one. Offers the complete range from design, process and device development through flexible prototyping and production. Production: Contract production of MEMS using processes not commercial available in industrial foundries. Contract and foundry production of radiation detectors. MEMS design center: SensoNor process = MULTIMEMS Other available foundry processes In-house MEMS processes 4

Key parameters for IAQ control Temperature CO 2 Humidity Other gases (e.g. CO) There is a strong demand for (networks of) low cost multi sensors 5

Infrared (IR) gas sensing Advantages: Selective Sensitive Non contact Reliable Disadvantages: Inherently expensive (at least two components) Large size Requires drift compensation Complex packaging 6

MEMS devices for infrared gas sensing 7

Micro ElectroMechanical Systems (MEMS) Miniaturized systems that carry out several operations. Typically: sensing, singnal conditioning and actuation Micro sensor and/or actuator ASIC Packaging 8

Microsystem technology Utilizes the production technology developed for microelectronics to make sensors (MEMS) Miniaturization High volume, low cost production Integration with electronics Special processes Micromachining Functional thin films Wafer stacking Piezo resistors Pressure sensor 9

Why silicon technology Batch processing => low cost, high volume Well established production technology Advanced infrastructure, materials and design tools available Wide range of sensor principles available Silicon has attractive mechanical properties Integration is possible 10

IR sources Thermal sources Conventional light bulbs MEMS based IR sources IR LEDs IR LASERS 11

The infrared emitter Produced by silicon micromachining Grey body spectrum Electronically controlled modulation Modulation depth: 20 % @ 50 Hz Power consumption: 1 Watt Application example: SIMRAD Optronics Gas Detector for methane (CH4) More than 15 years of continuous operation in the North Sea 12

Filters Single gas selectivity Compensation Multi gas detection (CO, humidity) 13

The Carbocap technology from VAISALA 14

A CO and methane sensor based on a thermally tuned Fabry-Perot filter Rogne, Bernstein, Avset, Ferber, and Johansen MOEMS 99, Heidelberg Micromachined in silicon Based on the thermo-opto effect T ~ 25 o C Designed to synthesize a characteristic gas spectrum Electrically modulated 10 nm Wavelengths from 1.2 µm -> Modulation frequency: 1 Hz Simple design, low cost 15

Transmission through 1000 ppm CO 1 0.8 0.6 0.4 0.2 0 4.5 4.55 4.6 4.65 4.7 4.75 4.8 4.85 4.9 4.95 5 Wavelength in micrometers CO absorption pattern + Transmission through 350 micrometer silicon 1 0.8 0.6 0.4 0.2 0 4.5 4.6 4.7 4.8 4.9 5 Wavelength in micrometers Absorption pattern synthesized by multi-line filter 1 0.8 Transmission 0.6 0.4 0.2 0 4.5 4.55 4.6 4.65 4.7 4.75 4.8 4.85 4.9 4.95 5 Wavelength in micrometers 16

CO measurments with the slab sensor Relative modulation amplitude (%) 3 2 1 0 1 1 2 3 4 10 20 30 40 50 60 70 80 90 100 time (seconds) 17

Diffractive optics for gas sensors 18

MEMS based IR detectors Thermopile detector Wolfgang Schmidt and Jörg Schieferdecker 19

Filter and detector in one chip: The SINTEF photoacoustic gas sensor IR window Absorption path Modulated IR source Pressure sensor Sealed absorption chamber 20

The photoacoustic detector chip Pyrex Silicon pressure sensor Wafer level gas filling High precision piezoresisive pressure sensor Transferred to the SensoNor MPW foundry process IR radiation Silicon 21

The photoacoustic signal 800 600 400 200 0-200 -400-600 -800 0 0.01 0.02 0.03 0.04 Time (sec) Photoacoustic signal IR source modualtion 22

CO 2 Measurement with the PA sensor: 16 8000 14 7000 PA-Signal [PA] 12 10 8 6 4 PA-Signal (Pa) rel. Humitdity (%*100) CO2 (ppm) 6000 5000 4000 3000 2000 Gasconcentration [ppm] 2 1000 0 0 0 500 1000 1500 2000 2500 3000 3500 4000 4500 Time [s] 200-100 ppm resolution 23

Characteristics High selectivity without additional filters High sensitivity => small size No pumps and valves Easily implemented in MEMS technology => low cost High volume production an packaging technology required Long term drift compensation has to be implemented 24

MASCOT: Micro-Acoustic Sensors for CO 2 Tracking Per Gerhard Gløersen, SensoNor AS Bertil Hök, Hök Instrument AB Niels Peter Østbø, SINTEF The MASCOT project was cofinanced by the IST programme of the European Commission under grant number IST-2001-32411 25

Electro-acoustic IAQ sensor Qair 26

Device modelling basics Relationship between velocity of sound c and molecular mass M of a gas: c = RTγ M R: universal gas constant (=8.314 J/mol K), T: absolute temperature (K) γ: Ratio of specific heat at constant pressure and volume Resonant frequency and Q of a Helmholtz resonator: Neck effective length l and area A (radius a) f r = c 2π A l V Compliant gas volume V µ: kinematic viscosity of gas Q a ω r 2µ 27

Schematic drawing of sensor chip Activating resistors on diaphragm Compliance Entrance hole Glass Silicon Inertance and resistance Detecting resistors on diaphragm Glass 28

Sensor output signal in air and CO 2 40 35 CO2 Air 30 Output signal (µv) 25 20 15 10 5 0 25 27 29 31 33 35 37 39 41 43 45 Frequency (khz) The resonance frequency shifts from 40 to 32 khz and the Q factor increases from 6.5 to 8.1 29

Sensor characteristics f r Q Typical value 40250 Hz 6.60 CO 2-11 Hz/1000ppm +0.009/1000ppm RH Temp Pressure Resolution +4 Hz/%RH 63 Hz/ C 0 ±2 Hz (±200 ppm CO 2 or ±0.5% RH) -0.001/%RH -0.015/ C +0.04/kPa ±0.01 30

MEMS based humidity sensors 31

Some aspects of multi sensors The challenge is often NOT to be sensitive to humidity and temperature Temperature sensors are easily implemented as an integral part of standard electronics. Multi sensors are often based on MCM integration. MEMS devices is potential easy to integrate since the are small and often based on the same principles (piezoresistive, capacitive and optical) MEMS also opens for a higher degree monolithic integration Temperature sensors as part of the gas sensor chip 32

Conclusion IR technology offers highly sensitive, selective and reliable gas sensors. MEMS based IR sources, IR detectors, tuneable optical filters, and complete gas and humidity sensors are available. IR gas sensors are, however, still expensive due to large size, expensive components, packaging, and drift compensation. Higher level of integration is required. A DOE based CO 2 under industrialization by Optosene AS A MEMS based photo-acoustic gas sensor for CO 2 is demonstrated offering high selectivity, sensitivity, and is compatible with MEMS technology. A new class of electro-acoustic MEMS-implemented CO 2 sensors has been demonstrated: Simple and uncritical geometry Strong potential for mass-production at low cost A CO sensor based on a thermally tuned F-P filter is demonstrated. The detection limit for CO was 20 ppm m, and 50 ppm m for methane. MEMS based sensors are by their small size and fabrication and packaging technology potentially suitable for multi-sensor integration 33