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Computational Modeling and Assessment of Nanocoatings for USC Boilers Presented by: D. Gandy (EPRI), [email protected] S. Cheruvu (SWRI), [email protected] J. Shingledecker (EPRI), [email protected] DOE Sponsored Program: DE-FC26-07NT43096

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Page 1: Computational Modeling and Assessment of Nanocoatings for … · 2014. 3. 24. · Computational Modeling and Assessment of Nanocoatings for USC Boilers Presented by: D. Gandy (EPRI),

Computational Modeling and Assessment of Nanocoatings

for USC Boilers

Presented by:D. Gandy (EPRI), [email protected]

S. Cheruvu (SWRI), [email protected]. Shingledecker (EPRI), [email protected]

DOE Sponsored Program: DE-FC26-07NT43096

Page 2: Computational Modeling and Assessment of Nanocoatings for … · 2014. 3. 24. · Computational Modeling and Assessment of Nanocoatings for USC Boilers Presented by: D. Gandy (EPRI),

2© 2009 Electric Power Research Institute, Inc. All rights reserved.

Background

• Fireside corrosion of boiler waterwalls continues to be the #1 issue resulting in forced outages and boiler unavailability for “conventional” coal-fired fossil boiler power plants.

Equivalent Availability Loss from Boiler Tube Failures in US is 2.5-3.0%

Page 3: Computational Modeling and Assessment of Nanocoatings for … · 2014. 3. 24. · Computational Modeling and Assessment of Nanocoatings for USC Boilers Presented by: D. Gandy (EPRI),

3© 2009 Electric Power Research Institute, Inc. All rights reserved.

Background--Annual Corrosion Costs

O&M Corrosion

Cost

Depreciation Corrosion

Cost

Total Corrosion

Cost Corrosion Problem

$ Millions $ Millions $ MillionsWaterside/Steamside Corrosion of Boiler Tubes 916.0 228.4 1,144.4

Turbine CF & SCC 458.0 142.8 600.8 Oxide Particle Erosion of Turbines 274.8 85.7 360.5

Heat Exchanger Corrosion 274.8 85.7 360.5 Fireside Corrosion of Waterwall Tubes 183.2 142.8 326.0

Generator Clip to Strand Corrosion 183.2 28.6 211.8

Copper Deposition in Turbines 91.6 57.1 148.7 Fireside Corrosion of SH & RH tubes 91.6 57.1 148.7

Source: Syrett, et al. Low Temperature Corrosion, EPRI

Page 4: Computational Modeling and Assessment of Nanocoatings for … · 2014. 3. 24. · Computational Modeling and Assessment of Nanocoatings for USC Boilers Presented by: D. Gandy (EPRI),

4© 2009 Electric Power Research Institute, Inc. All rights reserved.

Background

• Typical boiler wastage rates are:– Subcritical – 20 mils

(0.5mm)/year– Supercritical – 40-100

mils (1.0-2.5mm)/year• Corrosion rates tend to

increase with increasing temperatures.

• Higher operating metal temperature of supercritical boiler tubes tend to increase corrosion rates by 2-5X

Page 5: Computational Modeling and Assessment of Nanocoatings for … · 2014. 3. 24. · Computational Modeling and Assessment of Nanocoatings for USC Boilers Presented by: D. Gandy (EPRI),

5© 2009 Electric Power Research Institute, Inc. All rights reserved.

Background

• USC boiler metal temperatures will approach 1400F (760C).– Accelerated corrosion rates are anticipated at

these temperatures• Alloys such as P91, Super 304H (austenitic SS), and Alloy 230 (nickel-based) alloys will be required.

• Advanced austenitic SS typically exhibit poor sulfidization or coal ash resistance.– Reliable sulfidization and oxidation resistant

nanocoatings are required for improved durability of USC boiler tubes.

Page 6: Computational Modeling and Assessment of Nanocoatings for … · 2014. 3. 24. · Computational Modeling and Assessment of Nanocoatings for USC Boilers Presented by: D. Gandy (EPRI),

6© 2009 Electric Power Research Institute, Inc. All rights reserved.

DOE Nanocoatings Project Objectives

1. Develop/demonstrate nano-structured coatings using computational modeling methods to improve corrosion/ erosion performance of tubing in USC boiler applications.

2. Improve the reliability and availability of USC fossil-fired boilers and oxy-fuel advanced combustion systems by developing advanced nano-stuctured coatings:

• optimized utilizing science-based computational methodologies

• validated via experimental verification and testing in simulated boiler environments

Page 7: Computational Modeling and Assessment of Nanocoatings for … · 2014. 3. 24. · Computational Modeling and Assessment of Nanocoatings for USC Boilers Presented by: D. Gandy (EPRI),

7© 2009 Electric Power Research Institute, Inc. All rights reserved.

What is a Nanocoating?

Nanocrystalline materials/coatings:

• Single or multi-phase• Grain size <100 nm (1nm = 10 Angstroms)• Interfaces cover significant portion of the microstructure• Dense• Very hard and tough• Offer excellent corrosion/oxidation/erosion properties

compared to conventional materials/coatings

Human Hair = 85µm = 85000nm

Page 8: Computational Modeling and Assessment of Nanocoatings for … · 2014. 3. 24. · Computational Modeling and Assessment of Nanocoatings for USC Boilers Presented by: D. Gandy (EPRI),

8© 2009 Electric Power Research Institute, Inc. All rights reserved.

Oxidation Behavior of Nanocoatings--@ 1000◦C (1832◦F)

Effect of Grain Size

60nm

250nm

370nm

50nm

500nm

1) Gao et al., Advanced Materials, 2001, 13, pp. 1001, 2) Liu et al., Oxidation of Metals, 1999, 51, pp.403, and 3) Wang et al., Oxidation of Metals, 1996, 45, pp. 39

SpallationResistance

Lower oxidation kinetics

Ni-20Cr-2Al

Similar results were reported for CoCrAlY/FeNiCrAl microcrystalline coatingsImproved scale spallation resistance

Page 9: Computational Modeling and Assessment of Nanocoatings for … · 2014. 3. 24. · Computational Modeling and Assessment of Nanocoatings for USC Boilers Presented by: D. Gandy (EPRI),

9© 2009 Electric Power Research Institute, Inc. All rights reserved.

Finer Grain Size Promotes Formation of Stable Alumina Scale

Gao et al., Nano and Microcrystal Coatings, Advanced Materials, 2001, 13, pp. 1001

60 nm

370 nm

• Coating Ni-20Cr-2 Al• Exposed @ 1000°C for 100 hrs• Fine grained coating (60nm) exhibited

continuous protective alumina scale • Coarse grained coating severely

oxidized

Finer grain size lowers minimumAl requirement!

This would increase life by 3 to 4X

Page 10: Computational Modeling and Assessment of Nanocoatings for … · 2014. 3. 24. · Computational Modeling and Assessment of Nanocoatings for USC Boilers Presented by: D. Gandy (EPRI),

10© 2009 Electric Power Research Institute, Inc. All rights reserved.

Corrosion Resistance of Nanocoatings--Finer grain size also lowers minimum Cr requirement!!

Ni-10% CrConventional

Ni-20% CrConventional

Ni-11% CrNanostructure

K2SO4-20%NaCl-10K2SO4 @ 700°C for 50 hrs

For corrosion resistance formation of chromia scale is crucialTypically 20% Cr is required for protective scale formation

• Ni-10% conventional coating was severely corroded (no continuous chromia scale!)

• Continuous chromia scale was formed under the Ni-rich oxide in Ni-20% Cr coating - showed minor internal sulfidation

• Nanostructured Ni-11% coating showed continuous chromia scale (no sulfidation)

Page 11: Computational Modeling and Assessment of Nanocoatings for … · 2014. 3. 24. · Computational Modeling and Assessment of Nanocoatings for USC Boilers Presented by: D. Gandy (EPRI),

11© 2009 Electric Power Research Institute, Inc. All rights reserved.

Project Tasks

• Task 1: Computational Modeling of MCrAl Systems • Task 2: Establishment of Baseline Coating Data • Task 3: Process Advanced MCrAl Nanocoatings• Task 4: Fire-Side Corrosion Testing • Task 5: Computational Modeling & Validation • Task 6: Mockup Demonstration • Task 7: Project Management & Reporting

Page 12: Computational Modeling and Assessment of Nanocoatings for … · 2014. 3. 24. · Computational Modeling and Assessment of Nanocoatings for USC Boilers Presented by: D. Gandy (EPRI),

Task 1: Computational Modeling of MCrAl Systems--completed

Objective: Select potential MCrAlnanostructured coating compositions using computational modeling

Page 13: Computational Modeling and Assessment of Nanocoatings for … · 2014. 3. 24. · Computational Modeling and Assessment of Nanocoatings for USC Boilers Presented by: D. Gandy (EPRI),

13© 2009 Electric Power Research Institute, Inc. All rights reserved.

Task 1- Computional Modeling Of MCrAlComposition Selection

• Completed computations of FeNiCrAlx phase diagrams

• Al additions suppress sigma phase formation, while Mo and Co promotes.

• 4-5%Al is required to form a continuous Alumina scale.

• To ensure sufficient Al source, 10% Al is selected.

• Suggested nano-coating systems for evaluation:

• 310 +10%Al • 310 +30-35Ni +10%Al • Fe-35-40Ni-25Cr-10%Al

Al Content, Mass %0 2 4 6 8 10 12 14 16

Tem

pera

ture

, K

200

400

600

800

1000

1200

1400

1600

Fe-Cr-Ni-Al

Application ConditionsNo σ phaseWith σ phase

Continuous Al2O3

Page 14: Computational Modeling and Assessment of Nanocoatings for … · 2014. 3. 24. · Computational Modeling and Assessment of Nanocoatings for USC Boilers Presented by: D. Gandy (EPRI),

14© 2009 Electric Power Research Institute, Inc. All rights reserved.

Task 1 - Computational Modeling--Grain Growth Modeling

• Grain growth model results showed that the presence of high concentration low angle boundaries in the coating prevents grain growth

• Thermal exposure at 750ºC leads to sintering

• Coating/interface toughness was determined

• The sputtered coatings exhibited good toughness

• Indentation testing showed no coating delamination

Time hrs1 10 100 1000 10000

Gra

in D

iam

eter

, μm

0.1

1

10

100

1000

Model, Q = 404 kJ/mol KModel, Q = 245 kJ/mol K

Fe-18Cr-8Ni-10Al Coating

Grain Growth

Experimental Data

Page 15: Computational Modeling and Assessment of Nanocoatings for … · 2014. 3. 24. · Computational Modeling and Assessment of Nanocoatings for USC Boilers Presented by: D. Gandy (EPRI),

15© 2009 Electric Power Research Institute, Inc. All rights reserved.

Candidate Nanocoatings for Evaluation

Model Recommendation• Coating composition: Fe-25Cr- 30/40Ni-10 Al

Candidate Nanocoatings Selected For Evaluation• 310 + Al (Fe-25Cr-20Ni-10Al)• Haynes 120+Al (Fe-37Ni-25Cr-Al)• Haynes 160+Al (Ni-29Cr-28Cr-3Si-Al)• Haynes 188+Al (Co-22Ni-22Cr-14W-10Al)

Page 16: Computational Modeling and Assessment of Nanocoatings for … · 2014. 3. 24. · Computational Modeling and Assessment of Nanocoatings for USC Boilers Presented by: D. Gandy (EPRI),

Task 2: Establishment of Baseline Coating Data--completed

Objective: Evaluate conventional-and available vendor nanocoatings to assess properties

Page 17: Computational Modeling and Assessment of Nanocoatings for … · 2014. 3. 24. · Computational Modeling and Assessment of Nanocoatings for USC Boilers Presented by: D. Gandy (EPRI),

17© 2009 Electric Power Research Institute, Inc. All rights reserved.

Task 2. Establishment of Baseline Coating Data

• Fe-18Cr-8Ni-xAl Nano-coatings were deposited on 304SS and P91 samples

• Ni-20Cr-xAl Nano-coatingswere deposited on Haynes 230 and P91 samples

• Long term cyclic oxidation tests were conducted on the coated samples

Page 18: Computational Modeling and Assessment of Nanocoatings for … · 2014. 3. 24. · Computational Modeling and Assessment of Nanocoatings for USC Boilers Presented by: D. Gandy (EPRI),

18© 2009 Electric Power Research Institute, Inc. All rights reserved.

Task 2. Baseline Coating Data--Cyclic Oxidation Behavior of Fe-18Cr-8Ni-xAl Coatings

• Fe-18Cr-8Ni-xAl Nano-Coating Improved Oxidation Resistance By 2X.• The Addition Of Al Improved

– Oxide-Scale Spallation Resistance– And Oxidation Resistance

Thermal Cycles at Peak Temperature of 7500C

0 200 400 600 800 1000 1200

Wei

ght C

hang

e, g

rms/

cm2

-0.20

-0.15

-0.10

-0.05

0.00

0.05

304-UncoatedRegr 304 uncoatedFe-18CCr-8Ni coating Regr -Fe-18Cr-8NiFe-18Cr-8Ni-4Al CoatingRegr-Fe-18Cr-8Ni-4Al

Thermal Cycles at Peak Temperature of 7500C

0 200 400 600 800 1000 1200

Wei

ght C

hang

e, g

rms/

cm2

-0.20

-0.15

-0.10

-0.05

0.00

0.05

304-UncoatedRegr 304 uncoatedFe-18Cr-8Ni coating Regr -Fe-18Cr-8NiFe-18Cr-8Ni-4Al CoatingRegr-Fe-18Cr-8Ni-4AlFe-18Cr-8Ni-10Al CoatingRegr-Fe-18Cr-8Ni-10Al

Page 19: Computational Modeling and Assessment of Nanocoatings for … · 2014. 3. 24. · Computational Modeling and Assessment of Nanocoatings for USC Boilers Presented by: D. Gandy (EPRI),

19© 2009 Electric Power Research Institute, Inc. All rights reserved.

Task 2. Baseline Coating Data-- Coating Oxidation CharacterizationFe-18Cr-8Ni-xAl

1). The protective oxide layer• 0% Al coating Cr2O3• 4 and 10%Al coatings Al2O32). 4% Al coating was oxidized3). 10% Al coating was free from internal

oxidation4). Inward diffusion of Al led to formation

of inter-diffusion zone

0% Al

4% Al

10% Al

Page 20: Computational Modeling and Assessment of Nanocoatings for … · 2014. 3. 24. · Computational Modeling and Assessment of Nanocoatings for USC Boilers Presented by: D. Gandy (EPRI),

20© 2009 Electric Power Research Institute, Inc. All rights reserved.

Task 2. Baseline Coating Data--Cyclic Oxidation Behavior of Ni-20Cr-xAl Nanocoated and Uncoated Samples at 750ºC

Continuous mass gain of the coated samples indicates the outward growth of oxide scale

Scale is highly resistant to spallation

Haynes 230 may not need a coating at 750C

Thermal Cycles at Peak Temperature of 7500C

0 500 1000 1500 2000 2500

Wei

ght C

hang

e, g

ram

s/cm

2

0.00000

0.00005

0.00010

0.00015

0.00020

0.00025

0.00030

Un-coated

4%Al

7% Al10% Al

Page 21: Computational Modeling and Assessment of Nanocoatings for … · 2014. 3. 24. · Computational Modeling and Assessment of Nanocoatings for USC Boilers Presented by: D. Gandy (EPRI),

21© 2009 Electric Power Research Institute, Inc. All rights reserved.

Task 2. Baseline Coating Data--Oxide Scale on Ni-20Cr-xAl NanoCoating After Exposure at 750ºC

Al2O3

Al content in the coating

1.6 wt.%

Al content in the coating 4.8 wt.%

Al2O3

• Protective external oxide scale is dense, free from cracks• Highly resistant to spallation and coating is free from internal oxidation• Continuous mass gain is due to outward growth of the scale• Al consumption rate is high• The coating with 4% Al may not be durable for long-term service • Established need for at least 7% Al for long-term durability

Page 22: Computational Modeling and Assessment of Nanocoatings for … · 2014. 3. 24. · Computational Modeling and Assessment of Nanocoatings for USC Boilers Presented by: D. Gandy (EPRI),

Task 3: Processing of Advanced NanoCoatings--in progress

Objective: Apply advanced nanocoatings on USC substrates and evaluate properties

Samples

To Pump

Rotary Worktable

FilamentFilament Generated Plasma

Magnetron Generated PlasmaMagnetron

Motor-drivenShaft

VacuumFeedthrough

Ti Target

Samples

To Pump

Rotary Worktable

FilamentFilament Generated Plasma

Magnetron Generated PlasmaMagnetron

Motor-drivenShaft

VacuumFeedthrough

Ti Target

Page 23: Computational Modeling and Assessment of Nanocoatings for … · 2014. 3. 24. · Computational Modeling and Assessment of Nanocoatings for USC Boilers Presented by: D. Gandy (EPRI),

23© 2009 Electric Power Research Institute, Inc. All rights reserved.

Task 3 - Processing of Advanced NanoCoatings

• Plasma EnahancedMagnetron Sputtering

• Process optimization study was conducted to improve the density of the coating– power applied to targets

and bias voltage were varied

• Several trial coatings: 304+10Al, 310+10Al and Ni-20-10Al were deposited

• Coated samples were destructively examined

Samples

To Pump

Rotary Worktable

FilamentFilament Generated Plasma

Magnetron Generated PlasmaMagnetron

Motor-drivenShaft

VacuumFeedthrough

Ti Target

Samples

To Pump

Rotary Worktable

FilamentFilament Generated Plasma

Magnetron Generated PlasmaMagnetron

Motor-drivenShaft

VacuumFeedthrough

Ti Target

Page 24: Computational Modeling and Assessment of Nanocoatings for … · 2014. 3. 24. · Computational Modeling and Assessment of Nanocoatings for USC Boilers Presented by: D. Gandy (EPRI),

24© 2009 Electric Power Research Institute, Inc. All rights reserved.

Task 3 - Processing of Advanced NanoCoatings--Metallographic Examination

1000X 2000X

Result: Dense Nanocoating Microstructures

Page 25: Computational Modeling and Assessment of Nanocoatings for … · 2014. 3. 24. · Computational Modeling and Assessment of Nanocoatings for USC Boilers Presented by: D. Gandy (EPRI),

25© 2009 Electric Power Research Institute, Inc. All rights reserved.

Task 3 - Processing of Advanced NanoCoatings --Coating Adhesion Results

No coating delamination,DE 3 parameters were selected

Page 26: Computational Modeling and Assessment of Nanocoatings for … · 2014. 3. 24. · Computational Modeling and Assessment of Nanocoatings for USC Boilers Presented by: D. Gandy (EPRI),

26© 2009 Electric Power Research Institute, Inc. All rights reserved.

Task 3 - Processing of Advanced NanoCoatings --Selection of Process

• Process parameters of DE 3 produced good quality coating • Four advanced coatings (next slide) were deposited on P91,

304 SS and Haynes 230 samples for corrosion testing using DE 3 parameters

Concerns:Accelerated Al consumption rateRepeatability of Coating Quality Coating Cracking

Page 27: Computational Modeling and Assessment of Nanocoatings for … · 2014. 3. 24. · Computational Modeling and Assessment of Nanocoatings for USC Boilers Presented by: D. Gandy (EPRI),

27© 2009 Electric Power Research Institute, Inc. All rights reserved.

Task 3 - Processing of Advanced NanoCoatings

• Four advanced coatings were deposited:310 + Al (Fe-25Cr-20Ni-10Al)Haynes 120+Al (Fe-37Ni-25Cr-Al)Haynes 160+Al (Ni-29Cr-28Cr-3Si-Al)Haynes 188+Al (Co-22Ni-22Cr-14W-10Al)

• Coated P91, 304SS and Haynes 230 samples were shipped to Foster Wheeler for Corrosion Testing

• Process optimization trials for depositing interlayer and advanced coatings are in progress

Page 28: Computational Modeling and Assessment of Nanocoatings for … · 2014. 3. 24. · Computational Modeling and Assessment of Nanocoatings for USC Boilers Presented by: D. Gandy (EPRI),

28© 2009 Electric Power Research Institute, Inc. All rights reserved.

Task 3 - Processing of Advanced --Comparison of Nanocoatings with Conventional Plasma-Sprayed NiCoCrAlY

Thermal Cycles at Peak Temperature 10100C0 1000 2000 3000 4000 5000

Wei

ght C

hang

e, g

ram

s/cm

2

-0.0160

-0.0140

-0.0120

-0.0100

-0.0080

-0.0060

-0.0040

-0.0020

0.0000

0.0020

NiCoCrAlYRegr.NiCoCrAlY

TIN/NI-20Cr-10AlRegr. TINTiSiCN/Ni-20Cr-10AlRegr. TiSiCNAlN/Ni-20Cr-10Al

Regr.AlN

NiCoCrAlY

Zero weight loss with Diffusion Barrier Interlayer

2100 cycles

Page 29: Computational Modeling and Assessment of Nanocoatings for … · 2014. 3. 24. · Computational Modeling and Assessment of Nanocoatings for USC Boilers Presented by: D. Gandy (EPRI),

Task 4: Fireside Corrosion Testing --in progress

Objective: Conduct accelerated fireside corrosion tests

Samples

To Pump

Rotary Worktable

FilamentFilament Generated Plasma

Magnetron Generated PlasmaMagnetron

Motor-drivenShaft

VacuumFeedthrough

Ti Target

Samples

To Pump

Rotary Worktable

FilamentFilament Generated Plasma

Magnetron Generated PlasmaMagnetron

Motor-drivenShaft

VacuumFeedthrough

Ti Target

Page 30: Computational Modeling and Assessment of Nanocoatings for … · 2014. 3. 24. · Computational Modeling and Assessment of Nanocoatings for USC Boilers Presented by: D. Gandy (EPRI),

30© 2009 Electric Power Research Institute, Inc. All rights reserved.

Task 4 - Corrosion Testing

• In addition to the 4 newly developed test nanocoatings, two vendors supplied nanocoatings for corrosion testing:– N-TECH Inc. – NanoSteel

Page 31: Computational Modeling and Assessment of Nanocoatings for … · 2014. 3. 24. · Computational Modeling and Assessment of Nanocoatings for USC Boilers Presented by: D. Gandy (EPRI),

31© 2009 Electric Power Research Institute, Inc. All rights reserved.

Task 4 - Corrosion Testing--Testing Conditions

Waterwall Testing– 850F (454C), 975F (524C), and 1100F (593C)– 40 percent FeS and 0.2 percent chlorides (same as

USC program)

Superheater/Reheater Testing– 1100F (593C), 1300F (704C), and 1500F (816C). – 5 percent alkali sulfates (same as USC program)– simulate Eastern bituminous coal compositions.

• Perform 1000hr tests (at 100hr intervals).

Page 32: Computational Modeling and Assessment of Nanocoatings for … · 2014. 3. 24. · Computational Modeling and Assessment of Nanocoatings for USC Boilers Presented by: D. Gandy (EPRI),

32© 2009 Electric Power Research Institute, Inc. All rights reserved.

Task 4 - Corrosion Testing-- Following first 100hrs of testing

Waterwall Test Rack at 850F (100 hrs)

Page 33: Computational Modeling and Assessment of Nanocoatings for … · 2014. 3. 24. · Computational Modeling and Assessment of Nanocoatings for USC Boilers Presented by: D. Gandy (EPRI),

33© 2009 Electric Power Research Institute, Inc. All rights reserved.

Task 4 - Corrosion Testing-- Following 500hrs of testing

• A few nanocoatings still in good shape after 500hrs exposure.

• Many samples exhibited some level of blistering.– Suggests coating

processing issues.• Metallography just starting• Will require recoating

(process improvement warranted) and additional corrosion testing.

Page 34: Computational Modeling and Assessment of Nanocoatings for … · 2014. 3. 24. · Computational Modeling and Assessment of Nanocoatings for USC Boilers Presented by: D. Gandy (EPRI),

34© 2009 Electric Power Research Institute, Inc. All rights reserved.

Conclusions To Date

• For long-term term durability, nano-coatings should contain ~10%Al.– A continuous, Al-rich protective oxide scale can be

achieved with this level of aluminum.• 4 nanocoatings selected using computational thermodynamics.

• Good cyclic oxidation performance exhibited for baseline nanocoatings (Fe-18Cr-8Ni-xAl, Ni-20Cr-xAl)

• Early nanocoatings corrosion results suggest processing concerns—more work to do!

• A diffusion barrier layer slows Al consumption rate dramatically.

Page 35: Computational Modeling and Assessment of Nanocoatings for … · 2014. 3. 24. · Computational Modeling and Assessment of Nanocoatings for USC Boilers Presented by: D. Gandy (EPRI),

35© 2009 Electric Power Research Institute, Inc. All rights reserved.

What’s Next

• Complete fire-side corrosion testing (1000 hr) of nanocoatings at Foster-Wheeler (Task 4)

• Repeat coating processing trials (Task 3) and additional corrosion work.

• Validate computational model (Task 5)• Nanocoating mockup demonstration (Task 6)

Page 36: Computational Modeling and Assessment of Nanocoatings for … · 2014. 3. 24. · Computational Modeling and Assessment of Nanocoatings for USC Boilers Presented by: D. Gandy (EPRI),

36© 2009 Electric Power Research Institute, Inc. All rights reserved.

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