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R.A. Potyrailo 2018 1Public Copyright © 2018 General Electric Company - All rights reserved
Highly Selective and Stable Multivariable Gas Sensors for Enhanced Robustness and Reliability of SOFC Operation
GE: Radislav Potyrailo, Vijay Srivastava, Joleyn Brewer, Claire Henderson, Brian Scherer, Majid Nayeri, Andrew Shapiro
SUNY Poly: Michael Carpenter, Nicholas Karker, Nora Houlihan, Vitor Vulcano Rossi, Laila Banu
NETL Contract FE0027918
19th Annual SOFC Project Review Meeting, Washington, D.C., June 13-15, 2018
R.A. Potyrailo 2018 1Public Copyright © 2018 General Electric Company - All rights reserved
R.A. Potyrailo 2018 2Public Copyright © 2018 General Electric Company - All rights reserved
Project strategy:Develop in-line gas sensor for real-time SOFC diagnostics and enhancement of operation reliability
Project approach: Implement bio-inspired multivariable gas sensors for multi-gas quantitation at high temperaturesPerform laboratory optimization followed by field validation
Phase 1 outcomes:Fundamental understanding of performance and development of design rules of multivariable gas sensors at high temperatures
Project overview
This year top FIVE accomplishments
Initial
Improved
Time
Ref
lect
ance
PC1
H2CO
H2 + CO
Blank
PC2
-2
-1
0
1
2
3
4
5
6
7
8
9
10
11
0 1 2 3
Pred
icte
d H
2co
nc. (
AU)
Actual H2 conc. (AU)
H2 conc. = 5, 10, 15 %
Conventional technique
New technique
Benchmark
Sensor
Initial field validation
Sensitivity control
Selectivity control
Detection of gas mixtures
Sensor stability
1 µm
R.A. Potyrailo 2018 3Public Copyright © 2018 General Electric Company - All rights reserved
Mul
tivar
iate
resp
onse
#1
Gas 1
Gas 2
Gas 3
$ 250K instrument
Unmet need for real-time monitoring of H2 and CO gases
Status quo:Mature traditional detector
conceptsPerformance need:Multi-gas discrimination
Our approach:Multivariable photonic gas
sensors
Real-time knowledge of H2/CO ratio (3:1–2:1) of anode tail gases:• will allow control of efficiency of reforming process in the SOFC system• will deliver a lower operating cost for SOFC customers
In-line gas detection is not straightforward
R.A. Potyrailo 2018 4Public Copyright © 2018 General Electric Company - All rights reserved
Biomimicry –imitation of biological systems
Bioinspiration –new functionality, beyond Nature
High temperatureBiomimetics –recreation of observed functionality
Room temperature
Learning from Nature
1 µm
500 nm
2 mm
1 µm
Potyrailo, Carpenter, et al., J. Opt., 2018
Potyrailo et al., Nat. Commun. 2015
Potyrailo et al., Nat. Photon. 2007
R.A. Potyrailo 2018 5Public Copyright © 2018 General Electric Company - All rights reserved
Adsorbed gas molecules
Mul
tivar
iate
resp
onse
#1
Gas 1
Gas 2
Gas 3
Performance need:Multi-gas
discrimination
Our approach:Multivariable gas sensors
blankbottommiddletop
Free gas molecules
Potyrailo et al. Nature Photonics 2007Potyrailo et al., Proc. Natl. Acad. Sci. U.S.A. 2013Potyrailo et al. Nature Communications 2015
Design rules for gas-selectivity control• Spatial orientation of surface functionalization• Chemistry of surface functionalization• Extinction and scattering of nanostructure
Multi-gas detection using
bio-inspired multivariable photonic sensors
∆R
efle
ctan
ce
300 650Wavelength (nm)
Differential reflectance ΔR(λ) =100% R(λ)/R0(λ)
R(λ) = sensor with analyteR0(λ) = sensor with blank
R.A. Potyrailo 2018 6Public Copyright © 2018 General Electric Company - All rights reserved
Advancing design rules of nanostructures for high temperature gas-sensing applications
Selectivity control for vapors at room temp.
Selectivity control for gases at high temp.
Interference rejection control
•Polymeric nanostructure
•Absorption and adsorption of vapors
•Multi-material inorganic •nanostructure
•Catalytic reactions of gases
•Inorganic nanostructure
•Catalytic reactions of gases
500 nm500 nm1 µm
Potyrailo, Karker, Carpenter, Minnick, J. Opt., 2018
Potyrailo, Chem. Rev. 2016Potyrailo et al., Nat. Commun. 2015
R.A. Potyrailo 2018 7Public Copyright © 2018 General Electric Company - All rights reserved
400 450 500 550Wavelength (nm)
Spec
tral r
espo
nse
Needed diversity in spectral response for gas discrimination
600 700 800 900Wavelength (nm)
Spec
tral r
espo
nse
Diverse spectral response facilitates discrimination between different gases
R.A. Potyrailo 2018 8Public Copyright © 2018 General Electric Company - All rights reserved
Gas-discrimination control
100
Lamella spacing (nm)
150 200
75 100 125 150 Simulation data with SiO2 lamella
Diverse spectral response using different lamella spacing for discrimination between different gases
400 1400
Ref
lect
ance
Wavelength (nm)
600 1400
Ref
lect
ance
Wavelength (nm)
400 1400
Ref
lect
ance
Wavelength (nm)
600 1400
Ref
lect
ance
Wavelength (nm)
R.A. Potyrailo 2018 9Public Copyright © 2018 General Electric Company - All rights reserved
Sensitivity boosted by seven fold by• material selection • 3D structure design
Sensitivity control
Initial 3D
Improved 3D
Exposure to 8% H2
R.A. Potyrailo 2018 10Public Copyright © 2018 General Electric Company - All rights reserved
Example of H2 detection
0358
H2 conc. (%)
H2 spectral response H2 response: dynamics
Diverse spectra and dynamics uncover different response mechanisms in nanostructurePotyrailo, Karker, Carpenter, Minnick, J. Opt., 2018
500 600 700 800 900
Del
ta R
Wavelength (nm)
Del
ta R
Del
ta R
TimeTime
50 min50 min
860 nm660 nm
R.A. Potyrailo 2018 11Public Copyright © 2018 General Electric Company - All rights reserved
00.50.751
CO conc. (%)
CO spectral response CO response: dynamics
Diverse spectra and dynamics uncover different response mechanisms in nanostructure
Example of CO detection
Potyrailo, Karker, Carpenter, Minnick, J. Opt., 2018
500 600 700 800 900
Del
ta R
Wavelength (nm)
Del
ta R
Time
Del
ta R
Time
50 min 50 min
790 nm670 nm
R.A. Potyrailo 2018 12Public Copyright © 2018 General Electric Company - All rights reserved
670
675
680
685
690
695
0 5 10 15 20
Pea
k P
ositi
on (n
m)
H2 concentration (%)
Initial stability tests: univariate response
Peak position of one of spectral bands in a planar (control) sensor film
ExperimentH2, % = 5, 8, 12, 15, 20Number of cycles = 10 Test duration = 17 days replicates n = 10
Calibration curve over 17 days of testing
0
5
0
5
0
5
0 2 4 6 8 10 12 14 16
Time (days)
Peak
posit
ion
Peak
posit
ion
Tests with a planar sensor film and analysis of univariate (single output) response allows determination of sensor stability using classical methods
R.A. Potyrailo 2018 13Public Copyright © 2018 General Electric Company - All rights reserved
ROC curves with initial sensor stability at day 1
Receiver Operating Characteristic (ROC) curves
0 0.2 0.4 0.6 0.8 10
0.2
0.4
0.6
0.8
1
Prob
abilit
y of
det
ectio
n
Probability of false alarm0 0.2 0.4 0.6 0.8 1
Probability of false alarm
0
0.2
0.4
0.6
0.8
1
Prob
abilit
y of
det
ectio
n
ROC curves illustrate the diagnostic ability of the developed sensor to reliably detect gas concentrations
1.0000.5000.2500.1000.0750.050
H2 conc. (%)1.0000.5000.2500.1000.0750.050
H2 conc. (%)
ROC curves with sensor stability at days 1 - 17
R.A. Potyrailo 2018 14Public Copyright © 2018 General Electric Company - All rights reserved
Car driving modes
Software-driven boost of system performance
Smart phones: zoom, brightness control
Smart phones: face recognition
Consumer products
Electronics analytics
• Principal component analysis (PCA)• Discriminant Analysis (DA)• Artificial Neural Network (ANN)• Hierarchical cluster analysis (HCA) • Support Vector Machines (SVM)• Independent Component Analysis (ICA)• Partial least squares (PLS) regression• Principal Component Regression (PCR)
Potyrailo Chem. Rev. 2016
R.A. Potyrailo 2018 15Public Copyright © 2018 General Electric Company - All rights reserved
Multivariate data analysis e.g. PCA = Principal Components Analysis
Raw spectra PCA-processed
PCA
PCA – “classic” tool for reduction of data dimensionality and noise
PC = principal component
Poor sensitivityGood selectivity
Good sensitivityPoor selectivity
Good sensitivityGood selectivity
2-D response dispersion
R.A. Potyrailo 2018 16Public Copyright © 2018 General Electric Company - All rights reserved
0.985
0.99
0.995
1
1.005
1.01
1.015
1.02
400 480 560 640 720 800 880 960
Del
ta R
Wavelength (nm)
Initial discrimination between individual H2 and CO gases
Conditions:planar sensing filmTwo concentrations of H2Two concentrations of COSpectral replicates (n=2)
BlankH2 conc1H2 conc2CO conc1CO conc2
Different spectral regions of optical response of a single sensing to H2 and CO gases should allow discrimination of two gases
Spectral response to H2
Spectral response to CO
R.A. Potyrailo 2018 17Public Copyright © 2018 General Electric Company - All rights reserved
H2
CO
H2 + CO
Initial discrimination between individual and mixtures of H2 and CO gases
0.985
0.99
0.995
1
1.005
1.01
1.015
1.02
400 480 560 640 720 800 880 960
Del
ta R
Wavelength (nm)
Blank H2 conc1H2 conc2
CO conc1CO conc2
H2 + CO conc 1+1H2 + CO conc 1+2
Different spectral regions of optical response of a single sensing to H2 and CO gases should allow discrimination of two gases
R.A. Potyrailo 2018 18Public Copyright © 2018 General Electric Company - All rights reserved
-30 -20 -10 0 10 20 30 40PC1
H2CO
H2 + CO
Blank
-10
-8
-6
-4
-2
0
2
4
6
8
10PC
2H2
CO
H2 + CO
Initial discrimination between individual and mixtures of H2 and CO gases
Different spectral regions of optical response of a single sensing to H2 and CO gases allow discrimination of two gases
R.A. Potyrailo 2018 19Public Copyright © 2018 General Electric Company - All rights reserved
PCC / PFA = 1.0 / 0 PCC / PFA = 0.9 / 0.002 PCC / PFA = 0.7 / 0.03
No added noise Added 0.001 noise Added 0.002 noise
Wavelength Wavelength Wavelength
0.98
1
1.02D
elta
R
0.98
1
1.02
Del
ta R
0.98
1
1.02
Del
ta R
1
3
5
b
6
4
2
Predicted gas composition1 3 5b 6421 3 5b 6421 3 5b 642
1
3
5
b
6
4
2
1
3
5
b
6
4
2
Predicted gas composition Predicted gas composition
Actu
al g
as c
ompo
sitio
n
Actu
al g
as c
ompo
sitio
n
Actu
al g
as c
ompo
sitio
n
BlankH2 1H2 2CO 1CO 2H2 + CO 1H2 + CO 2
b123456
Probability
0
1
PCC = probability of correct classification; PFA = probability of false alarm
Confusion matrix analysis
Visualization of quality of prediction of classes
Gas compositions
R.A. Potyrailo 2018 20Public Copyright © 2018 General Electric Company - All rights reserved
Time
19 days with total of 75 cycles of H2 exposures
H20 1 2 3
H2 test cycle
Long-term response stability testing
H20 1 2 3
H2 test cycleH2 conc. = 5, 10, 15 %
50 min
Time
Spec
tral r
espo
nse
Planar sensor film and analysis of multivariate (many wavelengths) response allows determination of sensor stability using new machine learning methods
R.A. Potyrailo 2018 21Public Copyright © 2018 General Electric Company - All rights reserved
39500
42000
0 20
Co
unts
Time (days)
84000
89000
0 20
Co
unts
Time (days)
Raw sensor response to H2: effects of drift
650 nm
750 nm
Diverse temporal profiles of drift - possibility for drift correction ?
R.A. Potyrailo 2018 22Public Copyright © 2018 General Electric Company - All rights reserved
Conventional technique
New technique
Predicted H2 concentrations
H2 conc. = 5, 10, 15 %
Drift correction became a reality using new machine learning tools
R.A. Potyrailo 2018 23Public Copyright © 2018 General Electric Company - All rights reserved
-2
-1
0
1
2
3
4
5
6
7
8
9
10
11
0 1 2 3
Pred
icte
d H
2co
ncen
tratio
n (n
orm
aliz
ed u
nits
)
Actual H2 concentration (normalized units)
Correlation of actual vs predicted H2 concentrations
H2 conc. = 5, 10, 15 %
Developed data analytics technique improved the prediction ability of the sensorin detecting and quantifying a single gas
by more than 10 fold
Conventional technique
New technique
R.A. Potyrailo 2018 24Public Copyright © 2018 General Electric Company - All rights reserved
Benchmark instrumentsystem
Sensor under development
Initial tests of multivariable sensorat the SOFC factory at GE–Fuel Cells LLC
Benchmark system:Rosemount Analytical (Model X-STREAM Enhanced XEXF)
R.A. Potyrailo 2018 25Public Copyright © 2018 General Electric Company - All rights reserved
Spectrograph
Lightsource
Gas flow cell
Data acquisitionGas in
Light in/out
Fiber-optic reflection probe
Details of multivariable sensorat the SOFC factory at GE–Fuel Cells LLC
Gas flow cell
Laboratory components for testing of performance of 3D fabricated nanostructure
R.A. Potyrailo 2018 26Public Copyright © 2018 General Electric Company - All rights reserved
Sensing chip in gas cell with white light illumination
0
1.4 105
400 500 600 700 800 900 1000
Cou
nts
Wavelength (nm)
In-situ spectral collection
N2H2 = 4%CO = 22 %
Spectral features of 3D fabricated nanostructure are preserved in the gas cell design for field use
R.A. Potyrailo 2018 27Public Copyright © 2018 General Electric Company - All rights reserved
-1000
0
Del
ta C
ount
s
-3000
0
Del
ta C
ount
s
-2500
0
Del
ta C
ount
s
-5000
0
0 10 20 30 40 50
Del
ta C
ount
s
Time (min)
H2 H2 H2 CO COCO
460 nm
530 nm
600 nm
960 nm
Initial tests of developed 3D sensing nanostructure at the SOFC factory at GE–Fuel Cells LLC
H2 = 4%CO = 22 %
0.7
1
500 600 700 800 900
Del
ta R
efle
ctan
ce
Wavelength (nm)
Diversity of spectral features of 3D fabricated nanostructureFor independent quantitation of several gases with a single sensor
R.A. Potyrailo 2018 28Public Copyright © 2018 General Electric Company - All rights reserved
Summary of photonic multivariable gas sensors:developed capabilities
Next steps:• Summarize and document developed design rules for photonic multivariable
sensing at high temperature• Complete validation of developed multivariable sensor at the SOFC factory at
GE–Fuel Cells LLC
This year top FIVE accomplishments
Initial
Improved
Time
Ref
lect
ance
PC1
H2CO
H2 + CO
Blank
PC2
-2
-1
0
1
2
3
4
5
6
7
8
9
10
11
0 1 2 3
Pred
icte
d H
2co
nc. (
AU)
Actual H2 conc. (AU)
H2 conc. = 5, 10, 15 %
Conventional technique
New technique
Benchmark
Sensor
Initial field validation
Sensitivity control
Selectivity control
Detection of gas mixtures
Sensor stability
1 µm
R.A. Potyrailo 2018 29Public Copyright © 2018 General Electric Company - All rights reserved
Acknowledgements
• GE Global Research Team• SUNY Polytechnic Institute team • US Department of Energy Cooperative Agreement FE0027918
This material is based upon work supported by the Department of Energy under Award Number DE-EE00027918. This presentation was prepared as an account of work sponsored by an agency of the United States Government. Neither the United States Government nor any agency thereof, nor any of their employees, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constituted or imply its endorsement , recommendation, or favoring by the United States Government or any agency thereof. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof.
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