an account of our efforts towards air quality monitoring in … · 2014-07-12 · 9 scanning kelvin...
TRANSCRIPT
ESF provides the COST Office
through a European Commission contractCOST is supported
by the EU Framework Programme
European Network on New Sensing Technologies for Air Pollution
Control and Environmental Sustainability - EuNetAir
COST Action TD1105
2nd International Workshop EuNetAir on
New Sensing Technologies for Indoor and Outdoor Air Quality Control
ENEA - Brindisi Research Center, Brindisi, Italy, 25 - 26 March 2014
An account of our efforts towards air quality monitoring
in epitaxial graphene on SiC
Jens Eriksson
Applied Sensor Science, Linköping University/ Sweden
2
Outline
Why graphene sensors?
Epitaxial graphene on SiC
Effect of graphene layer thickness on gas sensitivity and selectivity
Understanding unintentional doping in epitaxial graphene
Controlling graphene layer uniformity
Tuning sensor properties by surface modifications
3
Why Graphene sensors?
Unique band structure of graphene leads to a low density of states near the Dirac point (ED) – small changes in the number of charge carriers results in large changes in the electronic state
Every atom at the surface – ultimate surface to volume ratio
Low noise, chemically stable (in non-oxidizing environment) p
p*
|e|<1eV
Graphene is highly sensitive to chemical gating due to its linear energy dispersion and vanishing density of states near the Dirac point and therefore has potential as a low noise, ultra-sensitive transducer.
Graphene sensors are normally highly sensitive, but suffer from poor reproducibility, selectivity, and speed of response.... d
e
Reproducibility is an issue that partly arises from the graphene synthesis
4
Jens Eriksson Linköping 2013 2013-11-20
manufactures and supplies
Graphene on SiC
Spin off from Linköping University,
Sweden
22.11.2011
Sublimation of Si from SiC in Ar at 2000ºC
Scalable, wafer-scale films compatible with standard semiconductor processing
High thickness uniformity (> 90% ML, rest 2 ML)
Thickness controlled by temperature
Silicon carbide
Wide band gap
High electron drift velocity
High breakdown field
High thermal conductivity
Ceramic Semiconductor
High chemical inertness
• Oxidation resistant
• Stable at high temperature
Hardness
Melting point ~ 2700°C
Light-weight
Polytypism: > 200 chemically identical polytypes
Eg = 3.0 eV Eg = 2.4 eV Eg = 3.2 eV
5
6
Graphene production
Graphene on SiC has EF pinned above the Dirac point
Causes electron doping!
Graphene layers sit on a buffer or interfacial layer
The buffer layer is covalently bound to the underlying SiC
Electronic coupling between SiC and graphene
C. Riedl et al. PRL 103 (2009)
Hall measurements show that our graphene has Ns ≈ 1012 cm-2
A. Tzalenchuk, et al, Nat Nano, 5, 186-189, (2010)
Ideal Epitaxial
S. Sonde et al., Physical Review B 80, 241406 (R) (2009)
S. Y. Zhou, et al., Nat. Mater. 6, 770 (2007)
ARPES: EF 0.4 eV above ED
7
Sensor response to environmental gating
Why is single layer more sensitive?
Current flow through all layers gas adsorption only on top layer
Different band structure leads to different responsivity; change resistivity with carrier density
Or difference in sticking coefficients of gases on single and multi layer graphene
Single layer Multi layer
Large n-type response to ppb concentration NO2 Small p-type response to ppm concentration NO2
R. Pearce et al. Sens. and actuators B. Chem. , 155(2): 451-455, 2011
0 5 10 15 20 25 30 350.80
1.00
1.20
1.40
1.60
1.80
Re
sis
tan
ce
cha
ng
e R
/R0
Time [h]
0
20
40
60
80
100
NO
2 C
oncentr
ation [ppb] in
N2
NO2 strongly electron withdrawing
NO2 sensing, single or double layer graphene?
9
Scanning Kelvin probe microscopy – work function mapping
Nanoscale mapping of graphene thickness uniformity and doping
-20 -10 0 10 20 30 40 50 600
2
4
6
8
10
12
14
16
18
20
Cou
nts
(%
)
V (mV)
Morphology Δ Vpot Potential distribution 5 nm 100 mV
2L
0 300 600 900 1200 1500
-10
0
10
20
30
40
50
V
(m
V)
Distance (nm)
Δvpot
≈ 50 mV 1L
2L
≈ 88 % 1L 1L
2L Shifts from single to bilayer domains normally occur at terrace edges
10 × 10 µm2
ΔΦ between 1LG and 2LG allows nanoscale mapping of graphene thickness
Controllable environment allows observing changes in 1LG and 2LG upon gas interaction
Eriksson et al.,Applied Physics Letters 100 (2012) 24160
Topography is mapped in 1st pass
Surface Potential is mapped in 2nd pass
Maps difference in work function
10
SKPM in controlled environment
Ambient
Corrugations in 2LG upon repeated gas exposure and vacuum ‘cleaning’
NO2: Electron withdrawing gas increases ΔVCPD, 2L-1L
NO2 on
NO2 off
In N2: after vacuum Φ1LG = Φ2LG
VCPD (1LG) and VCPD (2LG) decrease, but VCPD (1LG)
decreases more
1LG 2LG
1LG
2LG
11
Different shifts for 1LG and 2LG?
Different energy dispersions • Linear for 1LG • Parabolic for 2LG
Response to < 1 ppm NO2 vs. time
R. Pearce, J. Eriksson, T. Iakimov, L. Hultman, A. Lloyd Spetz
and R. Yakimova, ACS Nano 7 (5), pp 4647–4656 (2013)
From 1-2L ΔVCPD: Non-invasive estimation of carrier concentration
Calculated change in carrier concentration not the same for 1 and 2LG
Different responsivity for 1 and 2LG doesn’t account for all difference in sensitivity
Different sticking coefficients also important
Effect of humidity on surface potential
Environment affects the surface potential VCPD (1LG) decreases VCPD (2LG) constant
12
13
Controlling graphene layer uniformity and
unintentional doping
Large spread observed in NS for samples grown under identical conditions
There is strong indication that a correlation exists between the substrate surface
morphology and the electronic properties of the epitaxial graphene.
Yakes et al., Nano Lett. 10, 1559–1562 (2010)
Mono layer coverage depends on terrace width
200 400 600 800 1000 1200 1400 1600 1800 200030
40
50
60
70
80
90
100
2
4
5
7
8
9
1
3
11
6
1LG
(%
)
Terrace width (nm)
1012
Terrace width < 300 nm – no 1LG
As the terrace width increases, the area covered by 1LG increases
Graphene growth starts at step edges; many step edges → many nucleation sites
Terrace width > 1200 nm – gradual decrease of 1LG - Island growth in the absence of steps
Substrate polytype and doping for hexagonal SiC (n-type 6H-SiC or SI 4H-SiC) do not significantly influence uniformity
3C-SiC – higher 1LG % for lower terrace width , 1LG % independent on terrace width
3C-SiC
14
15
Carrier concentration depends on SiC surface
400 600 800 1000 1200 1400 1600 1800
0
50
100
150
200
250
300
1LG
(me
V)
Terrace width (nm)
Φ (so NS) depends strongly on terrace width
NS
Φ1LG vs. terrace width
ΔND,Max ≈ 8 × 1012 cm-2
σΔND ≈ 6 × 1011 cm-2 2
20 FED
N
For 1LG:
Variations in φ1LG follow variations in EF: Unintentional doping
Scattering indicates that also other factors affect EF
ΔND,Max ≈ 8 × 1012 cm-2
σΔND ≈ 6 × 1011 cm-2 2
20 FED
N
For 1LG:
Variations in φ1LG follow variations in EF: Unintentional doping
Eriksson et al., Applied Physics Letters 100 24160 (2012)
3C-SiC
3C-SiC: Lower doping, independent on terrace width
16
Surface restructuring during Si sublimation
0,00,51,01,52,02,53,03,54,0-800
-600
-400
-200
0
200
400
600
800 SiC
Graphene
Heig
ht (p
m)
Distance (m)
0 200 400 600 800
-0,20,00,20,40,60,81,01,21,4
T
err
ace
wid
th (
m
)
Substrate terrace width (nm)
All substrates undergo significant restructuring during graphene growth
Differing restructuring of different nominally on-axis SiC substrates
No correlation seen between SiC step distance before growth and how much the SiC restructures upon graphene growth
3C-SiC restructures less, and even a reduction of the terrace width is possible
3C-SiC
Step profile
0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5-2.0
-1.5
-1.0
-0.5
0.0
0.5
1.0
1.5
EG
Heig
ht (n
m)
Distance (m)
SiC
Change in terrace width
He
igh
t (1
nm
)
5 × 5 µm2 5 × 5 µm2 He
igh
t (5
nm
)
10 × 10 µm2
SiC substrate Graphene
SiC substrate Graphene
4H-SiC
3C-SiC
10 × 10 µm2
Effects of surface restructuring
-200 0 200 400 600 800-10
0
10
20
30
40
(
meV
)
Terrace width (nm)
a)
Minimize the restructuring → Use 3C-SiC substrates
Due to less step-bunching, 3C-SiC better lends itself to a well-controlled surface morphology and better control of the electronic properties of the graphene
More significant restructuring leads to less uniform graphene
Work function decreases (n-doping increases) with amount of restructuring
-200 0 200 400 600 800 1000 120050
60
70
80
90
1L
G (
%)
Terrace width (nm)
Eriksson et al., Mater. Sci. Forum 740-742 (2013) 153-156
17
Step bunching in 4H, 6H, and 3C-SiC
Yazdi et al., Carbon 57 477 –484 ( 2 0 1 3 )
4H-SiC
6H-SiC
3C-SiC
4H-SiC
3C-SiC
18
19
Uniform 1LG leads to very reproducible sensor characteristics
60 70 80 90 100 110 120 130 1401,00
1,05
1,10
1,15
1,20
1,25
NO2
Air
100 ppb50 ppb
No
rma
lize
d R
esis
tan
ce
Time (hours)
sensor 1
sensor 3
sensor 2
Uniform 1LG leads to very reproducible sensor characteristics
1LG is more sensitive to NOx than 2LG or
MLG
Uniform 1LG required for maximum sensitivity and reproducibility
Different sensors fabricated on 100% 1LG show identical
response
Epitaxial graphene on SiC enables highly
reproducible sensor fabrication
NO2 withdraws electrons
Ambient 1 ppm NO2
R. Pearce, J. Eriksson, T. Iakimov, L. Hultman, A. Lloyd Spetz and R.
Yakimova, ACS Nano 7 (5), pp 4647–4656 (2013)
Same change in charge carriers causes larger shift of the Fermi energy for 1LG
ΔS depends on thickness due to differing band structures for 1LG, 2LG... MLG
NO2 sensing interesting for:
•Emission control (few ppm)
•Air quality control (few ppb)
20
Graphene sensors issues: selectivity, response/recovery time, reproducibility
Obstacles: sensitivity, selectivity, response/recovery time, reproducibility
Sensitivity
UV “cleaning”: ppt and ppq level detection – surpassing specially trained dogs!
o O-functionalizes graphene Chen et al., Applied Physics Letters 101, 053119 (2012)
Sensors and Actuators B 166– 167, 172– 176 (2012)
J. Mater. Chem. 22, 11009 (2012)
Selectivity
Surface functionalizations by e.g. oxygen, nanoparticles, defect engineering, smart operation and smart analysis
Response/recovery times Functionalization, current-, bias- or temperature cycling. Integration of UV-LED
Reproducibility Sensors on epitaxial graphene
Variations in Ns can be compensated by the use of FET sensor
• SenSiC AB patent application
21
Functionalization with metal and metal oxide nanostructures for selectivity tuning
Graphene growth Sputtering nano-pouros metal
Contact deposition
Before metallization
After metallization
Gas testing
AFM, SKPM, Kelvin Probe
AFM, SKPM, Kelvin Probe
Sensor fabrication
Aim: To develop a reproducible method for functionalization with nano structures
• Thin layers of Au and Pt DC sputtered onto EG/SiC at elevated pressure
• Ideally we want islands or nanoparticles to maximize metal-graphene-gas boundaries SI 4H-SiC
on-axis
Epitaxial graphene
Au, Pt
22
Functionalization with metal and metal oxide nanostructures for selectivity tuning
Morphology shows deposition of continuous porous metal – ideally: islands…
1LG/2LG potential contrast: surface retains the electronic properties of graphene
Pt wets the surface better than Au – screens the graphene for ‘thick’ depositions
Scanning Kelvin probe microscopy: Maps surface morphology and surface potential
As-grown Thin porous metallization5 nm
1LG
Morphology Surface potential
100 mV
As-grown Au ≈ 5 nm
Morphology Surface potential
Morphology Morphology
Surface potential Surface potential
10 µm 10 µm
1 µm2 1 µm2 1 µm2
1LG2LG
Au ≈ 2 nm Pt ≈ 2 nm Pt ≈ 0-1 nm
1 nm
As-grown Thin porous metallization5 nm
1LG
Morphology Surface potential
100 mV
As-grown Au ≈ 5 nm
Morphology Surface potential
Morphology Morphology
Surface potential Surface potential
10 µm 10 µm
1 µm2 1 µm2 1 µm2
1LG2LG
Au ≈ 2 nm Pt ≈ 2 nm Pt ≈ 0-1 nm
1 nm
As-grown Thin porous metallization5 nm
1LG
Morphology Surface potential
100 mV
As-grown Au ≈ 5 nm
Morphology Surface potential
Morphology Morphology
Surface potential Surface potential
10 µm 10 µm
1 µm2 1 µm2 1 µm2
1LG2LG
Au ≈ 2 nm Pt ≈ 2 nm Pt ≈ 0-1 nm
1 nm
As-grown Thin porous metallization
5 nm
1LG
Morphology Surface potential
100 mV
As-grown Au ≈ 5 nm
Morphology Surface potential
Morphology Morphology
Surface potential Surface potential
10 µm 10 µm
1 µm2 1 µm2 1 µm2
1LG2LG
Au ≈ 2 nm Pt ≈ 2 nm
ΔΦ between 1LG and 2LG allows nanoscale mapping of graphene thickness (and doping)
23
Effect of decoration on sensor response
Effects of metallization:
• Improved speed of response
• Improved detection limit
• More stable base line
• Suppressed response to H2/CO while maintaining NO2 response (Au < 5 nm)
Response to ppb concentrations of NO2
As-grown graphene Au decorated graphene
0 2 4 6 8 10 12 14 16 18 20 22
1,0
1,2
1,4
1,6
1,8
2,0
Re
sis
tan
ce
ch
an
ge
R/R
0
Time (hours)
0
200
400
600
800
1000
NO
2 c
on
ce
ntr
atio
n (
pp
b)
in N
2
Au on graphene 100°C
RT
(b)
0 5 10 15 20 25 30 35
1,0
1,1
1,2
1,3
1,4
1,5
1,6
1,7
Re
sis
tan
ce
ch
an
ge
R/R
0
Time (hours)
0
20
40
60
80
100
120
140
100°C
NO
2 c
on
ce
ntr
atio
n (
pp
b)
in N
2As grown graphene
Selectivity
Response % Response Time (min), 50 ppb NO2 Recovery Time (min)
As-grown Au, 5 nm Pt, 5 nm As-grown Au, 5 nm Pt, 2 nm
30% 6 1.5 2.3 316 14 14,8
60% 23 9 10.9 834 47 49
90% 99 74 41.7 2136 135 175,5
J. Eriksson, D. Puglisi, Y. H. Kang, R. Yakimova, A. Lloyd Spetz , Physica B 439, 105–108 (2014)
0 2 4 6 8 10 12 14 16 18
0,50,60,70,80,91,01,11,21,31,41,51,6
Resis
tance c
han
ge R
/R0
Time (hours)
500 ppb
NO2
40 ppm
NH3
50 ppm
NH3
100 ppb
NO2
250 ppm
H2
500 ppm
CO
50 ppb
NO2
30 ppb
NO2
400 ppb
NO2
100°C
RT
Increased sensitivity
Detection limit < 1 ppb
0 100 200 300 400
10
15
20
25
30
35
40
45
5 nm Au on graphene
Se
nso
r re
sp
on
se
(%)
NO2 concentration (ppb) in N
2/ 20% O
2
Porous metal grains or nanoparticles increase the probability of interaction between the graphene surface and adsorbates
Metal decoration leads to
increased interaction due to
Increased spillover zones
Metal-graphene e-
transfer → Increased Oad
e-
e- e-
e-
O- O-
X X
Graphene
SiC
e-
24
Designed Nanoparticles by Pulsed Plasma
Preliminary show that TiO2 NPs allow enhanced sensitivity towards formaldehyde and benzene
The effect depends on the size of the deposited NPs (< 5 nm, sensitive to benzene, > 50 nm, sensitive to formaldehyde)
Plasma-based nanoparticle (NP) synthesis process
Highly reproducible thin film deposition technique
It is expected that decoration with different metals or metal-oxide nanostructures will allow careful targeting of selectivity to specific molecules
25 120 150 180 210 240 270 300
1796
1798
1800
1802
1804
1806
1808
1810
1812
Resis
tance
Time (min)
Annealed at 250°C before test
20% r.h.
125°C
500 ppb
formaldehyde
5 10 15718
720
722
724
Re
sis
tan
ce
Time (h)
0
10
20
30
Co
nce
ntr
atio
n (
pp
b)
C6H
6
C10
H8
CH2O
26
CONCLUSIONS
Sensing with epitaxial graphene – promising, ppb level NO2 detection
Obstacles (selectivity and speed) are being overcome
Thin (0.5 – 5 nm), porous decoration can result in improved selectivity, sensitivity, stability,
and response/recovery times
The effect depends on the choice, thickness, and nanostructure of the decoration
Air quality control: ppb level detection limit required,– a likely application
Emerging interest in detection of VOCs in living environments – ppb level detection crucial.
Graphene is an excellent candidate
It is expected that decoration with different metals or metal-oxide nanostructures will allow
careful targeting of selectivity to specific molecules