Florian Bousquet, Department of Electronics and Telecommunication, NTNU 1 TFE 06 - ASICS FOR MEMS...

Florian Bousquet, Department of Electronics and Telecommunication,

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TFE 06 - ASICS FOR MEMSTFE 06 - ASICS FOR MEMS

CMOS MEMS - Present & Future

Integrated Smart Sensor Calibration

Florian Bousquet, Department of Electronics and Telecommunication September 2006

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OutlineOutline

o MEMS – Present & Future

o 0) Introductiono 1) Present & Technology overview

o 1.1) Pre-CMOS approacho 1.2) Intra-CMOS approacho 1.3) Post-CMOS approacho 1.4) Mass Sensitive Chemical Sensoro 1.5) Force Sensor Array

o 2) Futureo 2.1) CMOS MEMS based products o 2.2) CMOS NEMSo 2.3) Biotronicso 2.4) Siliconless CMOS MEMS


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OutlineOutline

o Integrated Sensor Calibration

o 0) Introductiono 1) 1-Dimentional calibration

o 1.1) Calibration principleo 1.2) Mathematicso 1.3) Implementation

o 2) 2-Dimentional Calibrationo 2.1) Calibration principleo 2.2) Mathematicso 2.3) Implementation

o Conclusion


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0) Introduction0) Introduction

o All the IC nowadays and since 15 years :

CMOS technologyCMOS technology

o High process yield, high reliability

o Well established fabrications technologies

≠o MEMS processes : only drive for a while by universities

and defense labso Due to “unstandardized” processes and low volumes ordered


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o In the mid-1990’s, development of: o Accelerometers for airbag deploymento DMD (Digital Micro mirror Devices) for image projection

o Why?

Integration of the MEMS structure into a basic CMOS process

o Not only lowers manufacturing costs but also allows tighter integration of MEMS with ICs


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o Result:Reduced chip size

Improvement device performance

o Furthermore, high volume applications (inertial and pressure sensors) and applications requiring sensor arrays (DMDs) need both CMOS-MEMS processes.

o Thus, CMOS-based MEMS is more and more used within CMOS processes to release devices.

o An increasing number of Microsystem can be formed within the regular CMOS process sequence: Above all magnetic, optical and temperatures sensors.


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1) Technology overview1) Technology overview

o Process: o Based on depositing thin films of metal or crystalline

material on a substrateo Then , applying patterned masks by photolithographic imagingo Finally, etching the films to the mask.

o Wet etching : a liquid solution will dissolve the material o Dry etching : reactive ion etching (Released of beams and cantilever),

sputter, and vapor phase etching

o In the other hand, several devices (new ones) must be produced with additional micromachining and thin film deposition steps:

o 1) Pre-CMOS approacho 2) Intermediate-CMOS Approacho 3) Post-CMOS Approach


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1.1)1.1)Pre-CMOSPre-CMOS Approach Approach

o Structures of the MEMS are formed before the regular CMOS process sequence.

o Avoid thermal budget constraints during the MEMS fabrication : typically, structures are buried and sealed.

o And pre-processed wafer are used as starting materials for the subsequent CMOS process.


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1.2) 1.2) Intra-CMOSIntra-CMOS approachapproach

o Additional fabrication steps are performed in-between the regular CMOS steps.

o More highly integrated process Better performances Why? Because the micro structures and electronics part are “closer together”.

o And because inserting before the back end interconnect metallization ensures process compatibility with polysilicon.

o Ex: Pressure sensors from Infineon Technologies and Freescale.


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1.3) 1.3) Post-CMOSPost-CMOS approach approach

o Two possibilities:o MEMS structures are built from the

CMOS layers (pressure, inertial, flow, chemical sensors).

o Or built by additional layers deposited on top of the CMOS wafer (DMD by TI or Honeywell’s thermal imagers).

o These two approaches are interesting because they can be entirely outsourced and so processed at any CMOS foundry.

o Main Drawback: Stringent thermal budget, limiting temperatures to about 400°C


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1.4) Mass sensitive Microsensor1.4) Mass sensitive Microsensor

o CMOS based sensor for detection of volatile organic compounds in air :o Based on cantilever beam vibrations and electro-thermal

excitation detected by 4 Piezoresistors in Wheastone bridge and heating resistors.

o Cantilever coated with chemical sensitive layer: upon absorption of analyte molecules, cantilever mass increases and its fundamental resonance frequency decrease.

o This is recorded by an on-chip amplifying feedback circuit

o Realized using a 0.8 µm CMOS technology of AMS


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1.5) Force sensor array1.5) Force sensor array

o Sensor used for recording force images and force distance curves in Atomic Force Microscopy (AFM):o Consisting in 10 cantilevers with integrated thermal actuators, piezoresistive

sensors and driving and signal conditioning circuitry

o External controller applies heating power to the thermal actuators : Maintain constant cantilever defections

o Piezoresistive output signal is amplified on-chip and applied to the external controller.

o Operation time per cantilever: 100µso Images area: 1.1 x 110 µmo Vertical resolution: 3 nm


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2) Future2) Future

o 1) CMOS MEMS based products :o New products beyond the currently dominating pressure

sensor and accelerometers

o Based on the trends: o Systematic process development of laboratory CMOS MEMS for industrial

mass production

o Co-integration of digital interfaces and µcontrollers with microstructures

less expensive and more powerful

o Development of packaging to protect the vulnerable CMOS chip from environmental impact


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2) Future2) Future

o 2) CMOS NEMS as platform for Nano:o High sensitivity to differents effectso They have to deliver more than a basic device function &

some challenges have to be faced:o Interconnect challenge :Human is capable to handle mm sized objects and

only few electrons generate signals

o The « 300K » question : Problem of influence of the external conditions and thus find the right optimization

o Everything nano? : Miniaturization is not a value by itself: it has a cost, and we have to focus on the crucial nano part and do the rest with µtechnology

o But IC technology can bring the vast fabrication experience gained over the last decades, and it is to be noticed that gates thicknesses’ve reached the nano-level


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2) Future2) Future

o 3) Micro Biotronics :

Biophysical and Biomedical microdevices

MEMS for surgical sewing, Neuro MEMS, Biochemical sensors, Bio-mimetic devices…

o Miniaturized Hardware:o Micro electronicso Mechatronics

o Biologyo Biochemistryo Biomedical science…

TRONICSBIO


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2) Future2) Future

o 3) Micro Biotronicso Challenges are:

o Requires operations in water abhorred by microelectronics

o Living cells have to be kept alive by a mirofluidic supply system

o Stability between biological and electronic materials

o Limited lifetime of enzymes and antibodies


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2) Future2) Future

o 4) Siliconless CMOS MEMS

o Silicon might be expensive for MEMS requiring small parts of it.

o Maybe make a whole µsystem out of polymer (plastic, glass) would be cost-effective.

o Recent thin film transistors and organic circuits on flexible polymeric substrate have been demonstrate that was feasible.


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o Why calibration?o Sensor should provide correct transfert

from the φ signal to the electrical output signalo Increase performance & reliability and so boost the

MEMS market

o BUT increase MEMS production costs :o It takes time and attention per individual sensoro Need several reference measurements and correction

o Solution :Include at the sensor a programmable calibration facility (implemented as a digitally circuit integrated)

o It does NOT eliminate the need to do calibration!!


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1) 1-Dimentional calibration1) 1-Dimentional calibration

o Calibration principle:o Normally : collecting a set of measurements

data and then compute (complicated one!) correction formula

o Here : Each measurement is directly used to compute one programmable coefficient in a correction function

o And the next measurement makes use of this to compute another coefficient… but without affecting the previous calibration

o By instance :o 1): Offset

o 2): Gain

o 3): Linearity

o 4): …


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1) 1-Dimentional calibration1) 1-Dimentional calibrationo Mathematics:

o Yref: reference signal (a1 is a dimensionless number)

f 1 x f x a 1 . y ref f 2 x f 1 x a 2 . f 1 x y 1 f 3 x f 2 x a 3 . f 1 x y 1

. f 2 x y 2 y ref


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o Implementation:o Analog Signal Processor for Polynomial

Sensor Calibration

o Flow Diagram:


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o Implementation:

o Easy to implement on µcontroller (repetitive character)

Or

With Harware digital as well as analog

o Following example: analog implementation with current signals o They can easily be added, substracted or multiplied (Kirschoff)

o All the currents are represented by differential current and carried by common bias current


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1) 1-Dimentional calibration1) 1-Dimentional calibrationo Implementation (block diagram):

Caption: Sensor Signal Calibration points Addition Substraction Correction coef


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2) 2-Dimensional Polynomial2) 2-Dimensional Polynomial

o Why 2 dimensions?o By instance, a pressure sensor: not only

affected by pressure but also by temperature

o Calibration principle:o Same method as before with a dimension more:

o Select the error you want to correct (1° offset, 2° gain…)

o Instead of correcting it once and pass through to the next error, make a set of corrections for a predefined number of temperatures values

o So that the calibration function is equal to the desired function in all temperature calibration points

o The results are better with that method (speed and error reduction)


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o Mathematics :


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Transfer & error surface before calibration


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Transfer & error surface after calibration


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o To prevent escalation of the polynomial factors in the formulas:o Make first a correction of the cross sensitivity

(T°C in our case) before linearizing sensitivity of the input variable (pressure)

o But complicated in our case: temperature is swept through the whole temperature range several times

o And pressure cycles require less time for measurement than T°C

o So the solution is:

o Keep the order of corrected output values computation

o But change the order of corrections coefficients computation by:o At T° t1, applying pressure p1 to calculate a11 and apply t2 to calculate a21…

o Why can we make that? Because at the given T°, all the calibrations functions are equals!!

It’s the definition of this method!


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o Implementation:o Microcontroller-based pressure sensor system with

digital Calibration


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2) 2-Dimensional Polynomial2) 2-Dimensional Polynomialo Implementation:

o Multiplexer makes possible to read out the T° sensor and the pressure sensor with only one ΔΣ AD converter

o Calibration program and coefficients are stored in the µcontroller memory

o Software is written in C language and is composed of 2 parts:o Calibration part : Compute calibration coefficients & measure outputo Measurement part : Compute corrected values of pressure with equations

o Functioning:o User have to enter reference datas for the whole calibration processo Once the number of cal. Points & reference signals are in the µcontroller, the

system is totally autonomous and compute his own calibration coefficients and then compute the real measure of pressure.


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ConclusionConclusion

o MEMS in the future will be more and more used since they are needed in a huge range of applications and since the IC processes can be used to produce some at a lower cost and with a best reliability

o Calibration is a very important part but costly of the MEMS process o If the cost of such a process can be decreased and calibration made

easier for the use, it would improve significantly the MEMS marketo We’ve seen a method which is going in that sense


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Florian Bousquet, Department of Electronics and Telecommunication, NTNU 1 TFE 06 - ASICS FOR MEMS...

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