methodology for estimating ea for catalyst deactivation · 2017. 6. 14. · apply the protocol to...
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Methodology for Estimating Ea for Catalyst Deactivation
Bukky Oladipo, Tom Pauly, Marco Lopez
May 2, 2012
2012 DOE Crosscut Workshop on Lean Emissions Reduction Simulation
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2012 DOE Crosscut Workshop on Lean Emissions Reduction Simulation
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Rationale for Current Work
¶ Assessing catalyst system performance deterioration over in-use lifetime very costly and time-consuming
¶ Need to correctly reflect impact of thermal aging and chemical exposure can complicate bench aging acceleration to mimic field aging
¶ Typically, aging acceleration simulated through oven-, burner-, and engine bench-aging with select time @ temperature specifications
¶ For gasoline application, Arrhenius expression has been a successful tool used for determining equivalent aging acceleration over the years
¶ Industry interest is growing to develop appropriate protocol for accelerating diesel catalyst system aging to demonstrate end-of-life performance for various heavy-duty applications
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Objectives
¶ Employ the Arrhenius expression as a tool for developing accelerated aging protocol for diesel catalyst systems
¶ Apply the protocol to SCR catalyst aging and evaluate applicability of the Arrhenius expression for representing loss of overall NOx conversion with aging and/or the inherent functionalities of the SCR
¶ Establish Ea (energy of activation) for the deactivation of the catalyst and establish the variants related to functional deactivation due to thermal aging and chemical exposure
¶ Identify conditions under which the global Arrhenius method is not sufficient to determine the required aging acceleration
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Arrhenius Time and Temperature Dependency of Catalyst System Aging
Arrhenius equation relates rate of a reaction to temperature
Example: Ea = 96.5 kJ/mol for CO oxidation on Pt 111 face (gasoline) Source: SwRI – HD-DAAAC Consortium EPA Presentation, 17 March 2009
RTEa
Aek−
=
activation energy
gas constant
temperature (Kelvin)
pre-exponential factor
rate constant
natural log, e
kA
T
eEa
R
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Our Ultimate Objective is to Establish Performance DF for the Catalyst
AGING DURATION
NOx
CONV
ERSI
ON
NOx Conversion Deterioration With Oven-Aging at 675 °C; Evaluation Testing at 250 deg C SCR Inlet Temp
• Aging model effectively establishing DF for simulating end-of-life (EUL) performance
• HD Truck: 435,000 miles (~8,000 hrs)
• Locomotive line-haul: >64,000 hours EUL
• Can Arrhenius-type expression work to predict EUL activity?
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In the literature on catalyst simulation, inhibition terms are usually expressed in the Arrhenius form:
For NO oxidation over DOC as an example,
where the inhibition terms K1, K2, K3, & K4 have Arrhenius dependence just like the main reaction rate term k3
Source: Pandya, Mmbaga, Hayes, Hauptmann and Votsmeier, “Global Kinetic Model and Parameter Optimization for a Diesel Oxidation Catalyst,” National Research Council Canada, Pan2009
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For simulation purposes, can we then separate deactivation into distinct sources?
);( poisoningagingthermalfonDeactivati =
)()( poisoninggthermalfref
×=Δ
ηη
⎟⎟⎠
⎞⎜⎜⎝
⎛ −=
Δ
aging
ompositeccomposite
ref RTE
A expηη
Therefore, can we write
leading to:
where poisoningthermalcomposite EEE +=
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SCR1 ∅10.5“x 6.0“
8.5 L ∅10.5“x 6.0“
8.5 L = 17.0 L
Performance evaluation with NO2
CDPF Pt/Pd
DOC Pt/Pd
Aged
∅10.5“x 6.0“ 300/5
8.5 L
∅10.5“x 12.0“ 200/12 AC
17.0 L
A simple example with hydrothermal aging: Fe-Zeolite SCR over short to long aging duration
Aged 16H @ 750C
Temperature
Time
¶ 400°C
¶ 350°C
¶ 300°C
¶ 250°C
¶ Temp. ¶ NO2-Content
¶ 56 %
¶ 59 %
¶ 46 %
¶ 27 %
¶ Space Velocity
¶ SCR Volume
¶ 33.0 k
¶ 25.5 k
¶ 21.5 k
¶ 19.5 k
¶ 17 L
Time Dependence of Thermal Aging: 550 C 200h 550 C 400h 550 C 800h Temperature Dependence of Thermal Aging: § 16 hr 550°C § 16 hr 700°C 16 hr 800°C
SCR2
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Approach
¶ Arrhenius expression to describe performance loss due to aging:
¶ For (global) SCR NOx conversion reaction, consider: • Deactivation = Change in NOx conversion from Fresh to Aged State
= Function (time, temperature) • Assuming:
§ Linearity with aging time
§ Exponential with temperature
• Deactivation where Δη/taging is the rate of loss of NOx conversion efficiency and
Δη is normalized by appropriate reference value ηref, e.g. 100 for alpha =1.0, etc.
⎟⎠
⎞⎜⎝
⎛−=RTEAk aexp
⎟⎟⎠
⎞⎜⎜⎝
⎛=
Δ=
agingagingref RTEA
tRateonDeactivati exp
ηη
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Variation of NOx Conversion Efficiency with Aging Temperature (Aging Duration = 16 hrs)
α = 1.0
30 40 50 60 70 80 90
100
250 300 350 400 Temperature [°C]
NO
x C
onve
rsio
n [%
]
0 50 100 150 200 250 300 350
NH
3 Slip [ppm
]
16 hr @ 550 C 16 hr @ 800 C 16 hr @ 700 C NH3-Slip 16 hr @ 550 C NH3-Slip 16 hr @ 800 C NH3-Slip 16 hr @ 700 C
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Variation of NOx Conversion Efficiency with Aging Duration (Aging Temperature = 550 C)
30 40 50 60 70 80 90
100
250 300 350 400 Temperature [°C]
NO
x C
onve
rsio
n [%
]
0 50 100 150 200 250 300 350
NH
3 Slip [ppm
]
16 hr @ 550 C 200 hr @ 550 C 400 hr @ 550 C 800 hr @ 550 C NH3-Slip 16 hr @ 550 C NH3-Slip 200 hr @ 550 C NH3-Slip 400 hr @ 550 C NH3-Slip 800 hr@ 550 C
Two Major Observations: � There is no significant loss of NOx conversion except @ 400 deg C temperature; � Aging temperature influences deactivation more than aging duration
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Estimating Ea for Degreened & Aging Modes (NOx Eff)ref, % 100Time Aged Temp NOx Eff Eff Deac. Inv Temp Deac/time (D) ln(D)hr deg C % - 1/K 1/s16 550 94.38 5.62 0.00121 9.757E-07 -13.84
16 700 91.25 8.75 0.00103 1.519E-06 -13.4016 800 80.5 19.5 0.00093 3.385E-06 -12.6016 550 94.44 5.56 0.00121 9.653E-07 -13.85200 550 92.68 7.32 0.00121 1.017E-07 -16.10400 550 90.17 9.83 0.00121 6.826E-08 -16.50800 550 90 10 0.00121 3.472E-08 -17.18
y = -2392.9389188x - 10.9384323R2 = 0.9995698
y = -14121.1373361x + 0.5625532R2 = 0.9530623
-18.00
-17.00
-16.00
-15.00
-14.00
-13.00
-12.00
-11.00
-10.00
0.0009 0.0010 0.0011 0.0012 0.0013
1/T
LN(D)
Degrnd Mode Aging Mode
Linear (Degrnd Mode) Linear (Aging Mode)
y = -10496x - 2.7345R2 = 0.4878
-18.00
-17.00
-16.00
-15.00
-14.00
-13.00
-12.00
-11.00
-10.00
0.0009 0.0010 0.0011 0.0012 0.00131/T
LN(D)
All Aging Levels Linear (All Aging Levels)
Estimation of Activation Energy (Ea) for the Deactivation Mechanism (400 deg C data)
⎟⎠
⎞⎜⎝
⎛−=
Δ
RTEA
ta
agingref
NOx expηη
We consider:
hence,
( ) ⎟⎠
⎞⎜⎝
⎛−=⎟
⎟⎠
⎞⎜⎜⎝
⎛ Δ
TREA
ta
agingref
NOx 1LNLNηη
Normal aging mode Degreened mode
Degrn'd Aging-Ea/R -2,393 -14,121R 8.314 8.314 kJ/kmolEa 19,894.9 117,403.1 kJ/kmolln(A) -10.93843 0.562553A 1.78E-05 1.755148 1/s
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Fe-SCR example shows aging influence only at the high end (400 deg C) of aging temperature
¶ This is likely due to loss of NH3 storage capability; dealumination of Zeolite or other mechanisms
¶ Must look at component functionalities rather than global NOx conversion efficiency • NO oxidation • NH3 storage capacity • Surface coverage dependent NOx conversion • NH3 oxidation
¶ Attempt to correlate the component processes (functionalities) using the Arrhenius expression
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Another Example Using Cu-Zeolite SCR (Hydrothermal Oven Aging)
0
10
20
30
40
50
60
70
80
90
100
100 150 200 250 300 350 400 450 500 550 600 650
T in front of SCR [°C]
NO
con
vers
ion,
nor
med
by
alph
a [%
]
4h/800°C hydrothermal 4h/850°C hydrothermal 4h/875°C hydrothermal4h/900°C hydrothermal 4h/950°C hydrothermal
Short hydrothermal aging reaching up to 950 deg C
Estimating Ea for Aging Modes (NOx Eff)ref, % 100
Time Aged Temp NOx Eff Eff Deac. Inv Temp Deac/time (D) ln(D)hr deg C % - 1/K 1/hr
4 800 98.0 2.0 0.00093 1.389E-06 -13.494 850 92.0 8.0 0.00089 5.556E-06 -12.104 875 83.0 17.0 0.00087 1.181E-05 -11.354 900 57.5 42.5 0.00085 2.951E-05 -10.434 950 6.5 93.5 0.00082 6.493E-05 -9.64
Performance Deterioration at 200 deg C
⎟⎠
⎞⎜⎝
⎛−=
Δ
RTEA
ta
agingref
NOx expηη
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Potential to Identify Transition Points for Change in Aging (Deactivation) Mechanism
Inverse Temp (1/K)
⎟⎟ ⎠⎞⎜⎜ ⎝⎛ Δ
tLN
refNOX
ηη
Ea=188,135 kJ/kmol
Ea=290,031 kJ/kmol
HIGH THERMAL DEACTIVATION
LOW TO MEDIUM THERMAL
DEACTIVATION
Increasing Aging Temperature
High Temperature Aging Deactivation
Potentially a result of:
• Zeolite collapse
• Phase change
• Cu sintering
• Cristobalite
Deactivation under Normal/Medium Temperature
Potentially a result of (some generic chemistry facts):
• Loss of catalytic sites
• Cu migration
• Dealumination
• Chemical poisoning (P; S;…)
• ….
Aging Impact on Low Temperature Deactivation; GHSV = 30,000 (1/hr)
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Identifying Aging Limit for SCR Deactivation Source: “CLEERS SCR Teleconference,” Stephen J Schmieg, GM R&D
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Need to look at inherent “component” processes rather than global NOx conversion only
¶ Recall that the Fe-SCR example shows aging influence only at relatively high operating temperature (400 deg C)
¶ It suggests potential benefit of looking at the detailed processes
¶ Component functionalities to consider: • NO oxidation • NH3 storage capacity • Surface coverage dependent NOx conversion • NH3 oxidation
¶ Can these inherent processes (functionalities) be correlated with the Arrhenius even when overall NOx conversion shows no impact?
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Component Functionalities of SCR NOx Conversion Source: “CLEERS SCR Teleconference,” Stephen J Schmieg, GM R&D
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0
50
100
150
200
250
300
Time
PPM
/ de
g C
0
1
2
3
4
5
6
7
8
9
Test
Ste
p
Temp NO NH3 Step Temp NO NH3 Step Temp NO NH3 Step
Influence of 650 °C Hydrothermal Aging Change in NH3 storage at 175 °C reveal impact of aging
Aging hours as indicated on the curves
NH3 storage capacity is almost entirely gone after 1000 hrs of hydrothermal aging at 650 deg C
NO Efficiency almost unchanged
250 hrs 1000 hrs
16 hrs
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Influence of 650 °C Hydrothermal Aging No change in NH3 storage at 400 °C with the aging
Aging hours as indicated on the curves
0
50
100
150
200
250
300
350
400
450
Time
ppm
or
o C
0
1
2
3
4
5
6
7
8
Temp NO NH3 Temp NO NH3 Temp NO NH3 Step
16 hrs 250 hrs 1000 hrs
NO Efficiency equal
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We decide to employ a DoE approach involving aging temperature and duration
5
10
1
8
3
2, 4, 9
7
11
7 Relevant aspects to consider: • Response of SCR component functionalities
to aging level (time @ temp)
• Contribution of exposure to chemical poisoning elements (P, S, Zn, Ca, etc.)
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If Successful, Potential Application of the Arrhenius Correlation for Aging Representation
§ Estimate likely performance deactivation for aging duration and temperature of a given application
§ May also lend itself to correlation of different aging platforms (e.g. burner versus engine aging; etc)
§ Determining new aging time (or temperature) corresponding to a baseline or field aging
⎥⎥⎦
⎤
⎢⎢⎣
⎡⎟⎟⎠
⎞⎜⎜⎝
⎛−−=
121
2 11expTTR
Ekk a
k1 = deactivation rate at temperature T1
k2 = deactivation rate at temperature T2
With Ea known, calculate k2 corresponding to given aging temperature T2
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Next Steps
¶ Complete performance testing and analysis of the aging DoE
¶ Establish impact of chemical exposure and attempt to correlate combined thermal and chemical aging effects
¶ Determine suitability of the procedure for extrapolating required accelerated aging for extended-duration applications e.g. locomotive
¶ Apply same principle to DOC and CDPF aging