Microsensors forElectronic Noses and Tongues

Professor Julian Gardner

Microsensors & Bioelectronics LaboratoryWarwick University, Coventry, UK

www.warwick.ac.uk/go/MBL

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• 20 years experience in microsensors

• 450 publications (150 refereed journal)

• 12 books (4 series editor)

• 4 spin-out companies

www.warwick.ac.uk/go/MBL

Microsensors & Biolectronics Laboratory

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Chemical Sensor Today (>$1b)

Resistive OpticalCalorimetricElectrochemicalMass sensitive

• Piezoelectric (QCM, SAW)• Cantilever beam

ABBA Solidanalyte Reaction:

BR

Bmf

BHT ,I

250 mW

500 mW

100 mW

Low Poweri

Low Power

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Electronic Nose

• Device to mimic human olfactory system

• 1-100 million olfactory receptor cells• 350 genes that encode olfactory binding proteins• 1,000s glomeruli nodes• Mitral/tufted cells• 3% genome coding!

• E-nose concept 1980s• First companies

created in 1990s• Emerging market

valued at €10M-1B

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E-Nose: Definition & Architecture“An electronic nose is an instrument which comprises an array of electronic chemical sensors with partial specificity and an appropriate pattern recognition system, capable of recognising simple or complex odours”

Input(Odour)

Output(Predictor)

Olfactory epithelium (Receptor cells)

Mammalian Nose Olfactory bulb

Brain(Olfactory cortex)

Electronic Nose Sensor array

Analogue to Digital Converter

Computer ( Signal Processor & Pattern Recognition Engine)

SENSOR 1

SENSOR 2

SENSOR 3

SENSOR n

ARRAYPROCESSOR

PARCENGINE

KNOWLEDGE BASE

SENSORPROCESSOR

SENSORPROCESSOR

SENSORPROCESSOR

SENSORPROCESSOR

TRAIN TEST

ANALOGUE SENSING DIGITAL PROCESSING

V1j(t)

V2j(t)

V3j(t)

Vnj(t)

X1j

X2j

X3j

Xnj

Xj

Source: Gardner & Bartlett Sens. Actuators 18 (1994) 211

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Early Commercial Macro E-nosesFox 2,000Alpha MOS

E-Nose 4000 EEV Ltd

Agilent 4440

Osmetech

NST

Smartnose

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Warwick Smart Tongue

• Mimick human sense of taste• Concept in late 1990s• Warwick SAW based design – 60 MHz

20

200

22

)()/())(()/(

2 TPr

TPrrrsK

vv

20

20

2

)()/())(/(

2 TPr

TPrsK

k

Cole et al 2004 IEEE Sensors Journal, 4, 543-550

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Applications Space

• Food• Beverages• Healthcare

– Bacterial infection– Cancer detection

• Security• Robotics – molecular communication

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E-nose: Eye Infection

E-coli

Morax catar

Pseudo aerug

Strept pneumo

Haemop influ

Staph aureus

nnkkkk xaxaxaX ...2211

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E-Tongue: Milk Freshness

-1

-0.5

0

0.5

1

-3 -2 -1 0 1 2 3 4

Full Milk Semi-skimmed Skimmed milk

PC 2

PC 1

PC 1

PC

2

-2

-1.5

-1

-0.5

0

0.5

1

1.5

2

-3 -2 -1 0 1 2 3 4

Day 1

Day 4

Day 5

Day 3

Day 2

Fat content in Milk Milk freshness/bacterial load?

Cole et al. 2004 IEEE Sensors Journal, 4, 543-550 SkSkFkFkk aAaaAaX 4321

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Problems with Chemical Sensors to address

• High power consumption (need < 5 mW)• Low sensitivity (need ppb)• Poor selectivity (in real world)• Limited life (need calibration)• Expensive for mass market

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Solutions Proposed so Far …

→ Nanomaterials & Nanostructures→ Low Power SOI CMOS technology→ Massive CMOS sensor arrays→ Spatial-temporal microsystems (eMucosa)→ Biology, e.g. ligand receptors→ Advanced neuromorphic signal processing

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Gas/Odour Microsensors• Nanomaterials

– Metal oxides– CNTs– Polymers

• CMOS gas sensors– Resistive, Calorimetric– SAW delay/R

• Micro-noses

• Artificial e-mucosa

13

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What about NWs or sCNTFET?• Single CNT transistor• Low power

With Cambridge and ETHZ

• Boundary electron scattering effects• Molecule m.f.p. is ca. 10-100 nm

Limitations?

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Nano Calorimeters?

Parameter: Scaling factor K: K =1 K =10-3 K =10-6 Supported hotplate: Edge dimension (1 m thick square membrane)

K 1000 m 1 m 1 nm

Thermal response time ~ K2 100 ms 0.1 s 0.1 ps DC Power loss at 300C ~ K 100 mW 100 W 100 nW

Fundamental Limitations

Linear scaling theory

• Convection dominates so gas sensitivity constant • Mass transport issue as m.f.p. approached (100nm)• Molecular noise increases

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Human Olfactory Mucosa

• Distributed array of olfactory cells along mucous coated nasal cavity

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E-mucosa for better selectivity?

From: IEEE Sensors, Atlanta, 2007

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Employ large CMOS sensor arrays?5 rows by 14 columns 70 resistive and 70 FET sensors

Each row is deposited with a different polymer to increase discrimination capability

10 mm

5 m

m

PVPH

PEG

PCLPEVAPSB

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25 x 12 Sensor Array Response to Oils

19

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Biosensors to BioMEMS?• Bio-liquid packages• Liquid analytes

– SAW delay line– SAW Resonators

• Optical immunoassays

• Receptors and Cells– Insect

chemoreception

20

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Cell-based SAW sensor for selectivity?Cell deposition

SAW device

Liquid chamber

20 μm 2.5 μm

HEK cells on SAW device

HEK cells on SAW device

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Neuromorphic & neural systems• aVLSI implementation

of olfactory bulb

• Neuro-morphic models

• Convolution based models

• Spatio-temporal signal modelling

• Neural networks

dtSSty AB )()()(

22

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Silicon implementation of synapse and somata cell

10 mm by 5 mm die: 3 RN, 27 synapses and 1 PN per chip Multi-chip configurable

Ref: Hamilton, ISACS 2006

Footprint of neuromorphicaVLSI circuit implementationAMS 0.6 um CMOS process

Neuron circuit

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Neuromorphic Model of Insect Antennal Lobe in FPGA

Open FET 2011

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31 13

22

E-Glands and E-Noses on Robotshttp://www.youtube.com/watch?v=lBLN3sCbb

PY

Thank You for Listening