Coatings Technology at NIST

Christopher C. White

FEDERAL LABS AS BEACONS FOR INNOVATION AND ENTREPRENEURSHIPFLC Mid-Atlantic Regional Meeting

Maritime Institute of Technology and Advanced Graduate Studies (MITAGS)Linthicum Heights, MDNovember 18-19, 2014

Opportunity

Conventional test methods for the service life prediction of polymeric materials in outdoor exposures do not generate reliable or repeatable results.

They are expensive and time consuming.

Goal: Develop test methods which have the ability to accurately, precisely and reliably predict the in-service performance of polymeric materials designed for specific outdoor exposure in less than real time.

Durability testing now:

• Threshold testing– Accelerated, typically machine based.

– Based on historical performance.

– Not typically correlated to in-service performance.

– Equipment is based around a specific test.

• Long term outdoor exposure, again threshold.– Slower, requires years.

– Typically, not repeatable.

– Not predictive.

Current SLP problem…• I did an accelerated/ threshold test , how long will

the product last in service?

• The same as: If I tell you the tensile strength of steel, tell me how big of a bridge I can build…

• Currently, we have prescriptive tests. Very difficult to correlate to real world performance.

• Manufacturer’s Dilemma:

Time to ProfitCoatings > 15 yr product

introductionIC Chip ~ 4 months

Increased LiabilityFire Retardant PlywoodPolybutyldiene PipeMoisture Resistant CoatingsEFISAutomotive Clear Coats (4-6 $B/yr. In warranty costs.)

Class Action Lawsuits

Increase Time to Profit or Increase Liability Exposure

Current Service Life Methodology:

Inability to establish durability creates a barrier to innovation.

Service Life Prediction

Outdoor exposure Laboratory exposureor

“ This brings us face-to-face with one of the most perplexing problems concerned with outdoor weathering, that the weather does not duplicate itself. How can one ever expect a laboratory method to duplicate the weather when the weather can never duplicate itself” [Grinsfelder, 1967]

“ Successful laboratory simulation of the effects of weather on coatings, plastics and other materials has eluded scientists for over fifty years. Published literature report hundreds of attempts to duplicate and accelerate weathering effects and conclude that there is no substitute for natural weathering “ [Dreger, 1973]

Current Reality:

The Standard is Outdoor Weathering

“Current estimates of Service Life Prediction are Crude and there is Little or no Correlation between Laboratory and Field Exposure.” Rilem State of the Art Report, 1999.

How do we get to Reliability Based SLP?

Elements of a Standard Methodology for Service Life Prediction:• Characterize the service environment- Dose• Characterize the material - Damage• Identify the degradation mechanisms – • Develop a model for predicting the rate of degradation• Define the failure criterion• Using the model, calculate the time to failure• Prepare a report of the results in standard format stating clearly the

assumptions made

ASTM E632 Protocol

Creating Controlled ExposureSPHERE: Simulated Photodegradationby High Energy Radiant Exposure

Lots of LightStable to limit of detectionUniformity >95 %

Temperature ± 0.1 CHumidity ± 0.2%

32 Chambers, 17 samples/chamber>500 samples at a time.

Use design of experiments for all correlations of Temp, Humidity, UV, & Load

Equipment• Need to be able to transfer all of

this equipment to the public. – Commercially viable versions of our

SPHERE. • Independent control of light, temperature

and humidity.

• Data should be equivalent to our SPHERE or better.

• Guidance from customers, suppliers to help shape this device.

Reliability-Based SLP Methodology

Temperature

MaterialResponse

LaboratoryCumulative Dosage

Model

SpecificSLP Estimate

Damage Mechanism

Instrumented Outdoor Exposure

ControlledSeparableHigh VolumeHigh FluxEnvironmental Exposure

Moi

stur

eUV

Cumulative UV Dosage Models

l

( ) dt )101)(,()(0

)(max

min

llflt

l

l dtEtD Aototal òò --=

• Dtotal (t) = Damage to material.• min and max = minimum and maximum photolytically

effective wavelengths• Eo(,t) = spectral UV irradiance from light source• (1-10-A()) = spectral adsorption of specimen• () = spectral quantum yield of specimen• A() = adsorption at wavelength

DO

SE

-1.2

-1

-0.8

-0.6

-0.4

-0.2

0

-1.8 -1.6 -1.4 -1.2 -1 -0.8 -0.6 -0.4 -0.2 0

Loss of 1510 cm-1

Lo

ss

of

12

50

cm

-1

Lab: 25°C,100% ND (16) 35°C,4RH,4WL, 100% (64) 45°C,2RH,4WL, 100% (32) 55°C/75%RH,60% ND (16)

Outdoor: G4-17 (56)

Changes from Current Practice- Predictive Models: Field and Laboratory

Failure Mechanisms are the Same

Model, based on Laboratory data, successfully predicts damage occurring outdoors

Using Model-Free Heuristic Approach

Modulus

Opportunity

Conventional test methods for the service life prediction of polymeric materials in outdoor exposures do not generate reliable or repeatable results.

They are expensive and time consuming.

Goal: Develop test methods which have the ability to accurately, precisely and reliably predict the in-service performance of polymeric materials designed for specific outdoor exposure in less than real time.

Coatings Technology at NIST

Christopher C. White

FEDERAL LABS AS BEACONS FOR INNOVATION AND ENTREPRENEURSHIPFLC Mid-Atlantic Regional Meeting

Maritime Institute of Technology and Advanced Graduate Studies (MITAGS)Linthicum Heights, MDNovember 18-19, 2014