gas sensors and sensor systems for air quality monitoring...gas sensors and sensor systems for air...

LAB FOR MEASUREMENT TECHNOLOGY

Prof. Dr. rer. nat. A. Schütze

EuNetAir 2nd Scientific Meeting

Gas Sensors and Sensor Systems

for Air Quality Monitoring

Queens College, December 18-20, 2013, Cambridge, GB

Andreas Schütze Saarland University, Lab for Measurement Technology

VOC-IDS

Slide Gas Sensors and Sensor Systems for Air Quality Monitoring – MACPoll workshop – JRC Ispra 2

> Background: Indoor Air Quality

Why worry about indoor air?

Safety

Gas leak detection (combustible gases, e.g. CH4)

Fire detection (various gases)

Hazardous gas detection (e.g. CO)

Malodor detection (kitchen & bathroom ventilation)

HVAC systems

Reduced air circulation for greatly reduced energy consumption

CO2 monitoring for fresh air

Increased levels of VOCs lead to sick building syndrome

Selective (formaldehyde, benzene etc.)

and sensitive (ppb level) detection

Systems have to be adapted to the specific room use scenario

Nov. 19, 2013


> Background: Indoor Air Quality

Sensor requirements

Low cost

Networked systems (in major buildings, but also private homes)

Long lifetime: >10 years without maintenance for private homes

Which sensors are used today?

Safety

Gas leak detection: human nose, Japan: MOS; pellistors: only industr.

Fire detection: various sensors, mostly optical;

gas sensor systems under development (EC, MOS, GasFET)

Hazardous gas detection: EC, MOS

Malodor detection: MOS

HVAC systems

CO2 monitoring: NDIR (in major rooms/buildings), EC, GasFET

VOCs: MOS (total VOC), GasFET (emerging)

Nov. 19, 2013


> Background: our research focus

VOC-IDS: Volatile Organic Compound Indoor Discrimination Sensor

Transnational project funded within MNT-ERA.net

Selective VOC detection, primarily formaldehyde, benzene

Novel ceramic nanomaterial metal-oxide semiconductor gas sensors

Intelligent signal processing based on temperature cycling

Networked systems connected to KNX bus

SENSIndoor: Nanotechnology based intelligent multi-SENsor System

with selective pre-concentration for Indoor air quality control

EU-FP7 project NMP.2013.1.2-1:

Nanotechnology-based sensors for environmental monitoring

Microtechnology based approach for MOS and SiC-GasFET sensors

Pre-concentration to boost sensitivity and selectivity

Integrated multi-sensor approach

Application specific priorities and field tests

Nov. 19, 2013

Slide Gas Sensors and Sensor Systems for Air Quality Monitoring – MACPoll workshop – JRC Ispra

Metal Oxide Semiconductor (MOS), e.g. SnO2, Ga2O3, WO3

Oxygen adsorption leads to energy barrier at grain boundaries

Gas adsorption or reaction with O- influences energy barrier

Very high sensitivity (exponential effect of energy barrier on resistance)

Very low cost: manufacturing based on MEMS and screen printing

5

> Gas sensors for air quality

So

urce: F

igaro

Inc., Jap

an

Source: MicroChemical Systems S.A., Corcelles, CH Source: UST Umweltsensortechnik GmbH

Nov. 19, 2013


Metal Oxide Semiconductor (MOS), e.g. SnO2, Ga2O3, WO3

6

> Gas sensors for air quality

So

urc

e: F

igar

o I

nc.

, Ja

pan

Great robustness (> 10 years

lifetime in applications)

Poor stability

Sensor drift due to poisoning etc.

Influence of background, esp.

humidity

quantitative meas. difficult

Poor selectivity

Response is mainly due to

changing oxygen coverage

“Its surprising if the MOS sensor

does not show a reaction!”

greatest challenge for R&D

Nov. 19, 2013


> Novel developments

SiC Gas-sensitive Field Effect Sensors (Linköping U, SenSiC)

high temperature operation

allows temperature cycled operation as for MOS

(nano-)porous platinum and iridium gate materials

7

C. Bur et al.: Detecting Volatile Organic Compounds in the ppb Range with Pt-gate

SiC-Field Effect Transistors, Proc. IEEE Sensors 2013; Baltimore, USA, Nov. 3-6, 2013

Nov. 19, 2013


> Gas measurement systems – more than sensors

The three “S”

Sensitivity

Broad spectrum

from below ppb (for malodors, ozone, hazardous VOCs)

up to 1000 ppm (gas leak, CO2)

Selectivity

False alarms are primary concern for fire detection (ratio 10:1)

VOC detection: hazardous (formaldehyde) vs. neutral (alcohol

vapor, cleaning agents) vs. wanted (odorants)

Stability

Industrial applications: maintenance interval < 6 months

Public buildings: annual or bi-annual tests (if that)

Private homes: 10 years lifetime w/o regular maintenance?

Nov. 19, 2013


> Gas measurement systems – more than sensors

atm

osp

here

to

be a

naly

zed

sensor

electronics

signal processing

and evaluation

chemical and/or IR gas sensors

r.h.

T

display

data interface

generic modular gas sensor system

Nov. 19, 2013


0

10

20

30

Benzene

0 5 10 15 200

10

20

30

40

50

Diethyl Ether

Iso-Pentane

Methyl Alcohol

0 5 10 15 20

Methyl Tert-Butyl Ether

Co

ndu

cta

nce

[a

.u.]

Time in Temperature Cycle [sec]

70% r.h.

30% r.h.

Signal

evaluation:

1. Normalization of the response curves reduces sensor drift 2. Generation of secondary features, i.e. levels, slopes etc. 3. Suitable patterns are extracted for further evaluation

A. S

chü

tze,

A. G

ram

m, T

. R

üh

l IE

EE

Sen

sors

Jo

urn

al, V

ol.

4, N

o. 6

, 200

4

0 5 10 15 20

Propylene Oxide

Gas measurement systems – more than sensors Temperature Cycled Operation (TCO)

Nov. 19, 2013


Evaluation of sensor data based on

temperature cycling (example)

Virtual multisensor

Characteristic features of the curve shapes

(i.e. slope at the end of the high

temperature phase and curvature during

the low temperature phase) are evaluated, to

discriminate between different gases in

several steps.

Note: the decision tree reflects the chemical

composition of the solvents starting with the

alkane pentane and the aromatic benzene

(both pure CH-compounds), then the alcohol

(R-COH) and finally the three ether

compounds (R1-O-R2). This indicates that

an expansion might be possible to classify

many different molecules.

Decision 3

Synthetic air, Iso-Pentane,

Benzene, Methyl Alcohol,

Methyl Tert-Butyl Ether,

Diethyl Ether, Prop. Oxide

Decision 4

Decision 1

Decision 2

Methyl 4-Butyl Eth.

clean air &

interferents

Propylene Oxide

Diethyl Ether

Benzene

Iso-Pentane

Methyl Alcohol

T-Cycle 2

T-Cycle 1

So

urc

e: A

. S

chü

tze,

A. G

ram

m, T

. R

üh

l IE

EE

Sen

sors

Jo

urn

al, V

ol.

4, N

o. 6

, 2

00

4

11

Gas measurement systems – more than sensors Temperature Cycled Operation (TCO)

Nov. 19, 2013


Gas measurement systems – more than sensors Temperature Cycled Operation (TCO) – hardware

• Heater temperature control Heater resistor RH(T) controlled for exact temperature control of (micro-)hotplates

• Sensor read-out with large dynamic range for MOS, GasFET and pellistor type sensors

Hardware platform GasTON for exact temperature control and large dynamic

range data acquisition – Gas sensor T-cycle Operating uNit

0 2 4 6 8 10 12242

243

244

245

246

247

248

249

250+120°C

-20°C

ambient temperature

-20°C

time [h]

0°C

20°C

40°C

60°C

80°C

100°C

120°C

se

nso

r te

mpe

ratu

re [

°C]

T=5,5°C

R1

Rpot

Radj

R2

RH

R3

R4

R6

R5

_

+

UV

now commercialized “OdorChecker”

by 3S GmbH (spin-off of LMT)

Nov. 19, 2013


-40 -20 0 20 40 60 80 100 120-20

-15

-10

-5

0

5

10

75 ppm

60

4530

800 ppm

600

400

NO2

20, 30, 40, 50 ppm

NH3

2n

d d

isc

rim

ina

nt

fun

cti

on

(2

.8%

)

1st discriminant function (96.78%)

N2 +

5% O2

CO

200

13

Gas measurement systems – more than sensors Gate Bias Cycled Operation (GBCO) for GasFETs

TCO hardware platform extended to allow Gate Bias Variation

C. Bur et al.: Combination of Temperature Cycled and Gate Bias Cycled Operation to enhance the Selectivity of SiC-FET

Gas Sensors, Proc. Transducers 2013 & Eurosensors XXVII; Barcelona, Spain, June 16 - 20, 2013

Nov. 19, 2013

• Heater resistor RH(T) controlled

for exact temperature control

• Sensor read-out: voltage drop VD

measured at constant current ID

• Gate voltage VG varied to

influence the operating point


Target appl.

E. L

eon

hard

t, Th

esis pro

ject, UdS

-LM

T, 2

00

7.

Many possibilities for

optimization:

• Sensor selection

• Operating mode • TCO

• EIS

• GBCO

• Data acquisition

• Signal preprocessing

• Feature extraction

• Separation

• Classification

…and always testing under real

application conditions (field

testing)!

GMA

Sensor

Messhardware

Datennormierung

Merkmalsextraktion

Unterscheidung/

Trennung

Klassifizierung

T-Zyklus

Messdaten

Sta

tisch

e

Messung

dynam

isch

e

Me

ssu

ng

Sig

na

lvera

rbeitu

ng

En

tsch

eid

ung

s-

pro

zess

sensors

electronics

normalization

feature extract.

discrimination/

separation

classification

gas test system

raw data

TCO/EIS

Sig

nal p

rocessin

g

dynam

ic

meas.

Cla

ssific

atio

n

Sta

tic

meas. Gas measurement systems – more than sensors Temperature Cycled Operation – system design

Nov. 19, 2013


> Indoor Air Quality monitoring

MNT-ERA.net project VOC-IDS

Volatile Organic Compound Indoor Discrimination Sensor

Scenario specific detection of hazardous VOC

Integration of sensor system into KNX building automation networks

15 Nov. 19, 2013




Example for selective detection of VOCs in interfering background

Classification of Formaldehydye, Benzene, Naphthalene in presence of ethanol

16

interferent

concentrat.

relative

humidity

number of

LDA steps

for charac.

Estimated

number of

LDAs

0, 0.4, 2 40%, 60% 1 1

None 40%, 60% 2 1+10(?)*1

0, 0.4, 2 None 1 (2) (1+) 5*1

target gas Concentration (ppb) humidity Interferents (EtOH ppm)

Air NA 40%, 60% none, 0.4, 2

Formaldehyde 10, 100 40%, 60% none, 0.4, 2

Benzene 0.5, 4.7 40%, 60% none, 0.4, 2

Naphthalene 2, 20 40%, 60% none, 0.4, 2

generalized classification

classification w known EtOH

classification w known r.h.

Nov. 19, 2013

Slide Gas Sensors and Sensor Systems for Air Quality Monitoring – MACPoll workshop – JRC Ispra Nov. 19, 2013

air

formaldehyde

benzene

naphthalene

w/o additional information

air

formaldehyde

benzene

naphthalene

with known EtOH concentration



Example for selective detection of VOCs in interfering background

Classification of Formaldehydye, Benzene, Naphthalene in presence of ethanol

17

air

formaldehyde

benzene

naphthalene

with known rel. humidity



Highly sensitive VOC detection with SiC GasFETs (SenSiC AB)

18

874

875

876

877

878

879

880

881

882

0.5

ppb1.5

ppb2.5

ppb3.5

ppb

sensor response VDS

smoothed signal

sen

so

r sig

nal V

DS

[m

V]

4.5

ppb

quasi static sensor response Pt-gate @ 220 °C

0 2 4 6 8 100

1

2

3

4 Benzene

co

nc. [p

pb

]

time [h]

866

868

870

872

874

876

878

quasi static sensor response Pt-gate @ 220 °C

sen

so

r sig

nal V

DS

[m

V]

sensor response VDS

smoothed signal

0 1 2 3 4 5 6 7 8 9 100

50

100

150

200

co

nc. [p

pb

]

time [h]

40 % rel. hum

C. Bur et al.: Detecting Volatile Organic Compounds in the ppb Range with Pt-gate SiC-Field Effect Transistors,

Proc. IEEE Sensors 2013; Baltimore, USA, Nov. 3-6, 2013

Nov. 19, 2013



System integration: Gate Bias Cycled Operation for SiC-GasFETs

C. Bur et al.: Influence of a Changing Gate Bias on the Sensing Properties of SiC Field Effect Gas Sensors, IMCS 2012

0 1 2 3 4 50

40

80

120

160

200

240 5% O

2 in N

2

40 s ramp

cu

rre

nt

i DS (

µA

)

gate bias UG

(V)

200°C

0 1 2 3 4 50

40

80

120

160

200

240

cu

rre

nt

i DS (

µA

)

gate bias UG

(V)

400 ppm CO

40 s ramp

200°C

0 1 2 3 4 50

50

100

150

200

250

300

150°C

cu

rre

nt

i DS [

µA

]

gate bias UG [V]

5% O2 in N

2

40 s ramp

0 1 2 3 4 5

10

20

30

40

50

60

70

80

90

cu

rre

nt

I DS [

µA

]

gate bias UG [V]

5% O2 in N

2

120 s ramp

200°C

0 20 40 60 80 100 120 140

0

1

2

3

4

5

6 U

gate

ga

te b

ias

Ug

ate (

V)

time (s)

19 Nov. 19, 2013



Sensor self-monitoring with combination of TCO and EIS

A.

Sch

ütz

e et

al.

: Im

pro

vin

g M

OS

Vir

tual

Mult

isen

sor

Sy

stem

s by

C

om

bin

ing

Tem

per

atu

re C

ycl

ed O

per

atio

n w

ith

Im

ped

ance

S

pec

tro

scop

y, I

SO

EN

20

11

classification classification

feature extraction

feature extraction

discrimination discrimination

output

diagnostic

T-cycle EIS

d e

c i s

i o n

p r o

c e

s s

yes

no

difference d e

c i s

i o n

p r o

c e

s s

hardware for EIS

- poor mobility

- high cost

- long acquisition time

hardware for TCO

operation available

at reasonable cost

20 Nov. 19, 2013

gas sensors and sensor systems for air quality monitoring...gas sensors and sensor systems for air...

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