Transcript of 1 Sandia is a multiprogram laboratory operated by Sandia Corporation, a Lockheed Martin Company, for...
- Slide 1
- 1 Sandia is a multiprogram laboratory operated by Sandia
Corporation, a Lockheed Martin Company, for the United States
Department of Energys National Nuclear Security Administration
under contract DE-AC04-94AL85000. Robert Bernstein Sandia National
Laboratories Organic Materials Department Albuquerque, NM
rbernst@sandia.gov505-284-3690 179 th Technical Meeting Rubber
Division April 18-20, 2011 Akron, Ohio Polymers/Organic Materials
Aging Overview
- Slide 2
- 2 O-rings Shorting Plugs Textiles Nuclear Power Plant Cable
Insulation Labeled Polymers Organic Materials Problems; Organic
Materials Aging and Degradation
- Slide 3
- 3 Accelerated Aging Temperature Reaction Coordinate
- Slide 4
- 4 General Approach/Goals Physical property Chemical Property
Macroscopic level Molecular Level Tensile Strength UV-VIS
Spectroscopy Infra-red Spectroscopy Molecular Weight Analysis
Density Differential Scanning Calorimetry X-Ray Analysis Surface
Analysis Additives Nuclear Magnetic Resonance Goals Prediction of
physical properties vs. time Prediction of physical properties vs.
time Predict remaining lifetime of field materials Predict
remaining lifetime of field materials Develop condition monitoring
method Develop condition monitoring method GPC PermeationElongation
Dimensional changes Sealing Force Compression Set
- Slide 5
- 5 Deception ! Conclusions derived from initial high
temperature, short duration (even out to 1 year) accelerated aging
can be misleading. Chemistry / mechanisms must be understood.
Results must be critically analyzed to identify and understand
mechanism changes
- Slide 6
- 6 Thermal-oxidative Aging: Nylon 2000 days ~ 5.5 years
Bernstein, R.; Gillen, K. T. Polymer Degradation and Stability,
Nylon 6.6 accelerating aging studies: II. Long- term
thermal-oxidative and hydrolysis results 2010, 95, 1471-1479.
- Slide 7
- 7 k =Ae -Ea/RT Arrhenius equation: Arrhenius Equation Old
Chemist expression: increase rate by 10 C will double the rate
- Slide 8
- 8 Time Warp Back to High School. ..but only briefly.
- Slide 9
- 9 Equation of a Line y=mx + b what you want slope what you know
y-intercept
- Slide 10
- 10 Function of a Line y=mx + b x y slope =m y intercept =b
- Slide 11
- 11 k =Ae -E a /RT Empirical equation Arrhenius Equation rate
Pre-exponential factor Temperature (Kelvin) Gas constant e
Activation Energy
- Slide 12
- 12 k =Ae -Ea/RT ln(k) = ln(A) Ea/RT Arrhenius Equation ln(k) =
Ea/RT + ln(A) ln(k) =( Ea/R)(1/T) + ln(A)
- Slide 13
- 13 Function of a Line y=mx + b x y slope =m y intercept =b
- Slide 14
- 14 Function of a Line 1/T ln(k) slope = -Ea/R y intercept
=ln(A) ln(k) =( Ea/R)(1/T) + ln(A)
- Slide 15
- 15 Plot log(a T ) vs 1/T linear if Arrhenius k =Ae -Ea/RT
Arrhenius equation: Arrhenius Equation What is Ea? k = anything
ln(k) =( Ea/R)(1/T) + ln(A)
- Slide 16
- 16 EaEaEaEa Reaction coordinate Energy reactants products
---Imagine a marble---
- Slide 17
- 17 EaEaEaEa Reaction coordinate Energy reactants products
- Slide 18
- 18 EaEaEaEa Reaction coordinate Energy reactants products
Intermediates/Transition states EaEaEaEa
- Slide 19
- 19 Are Diamonds forever?
- Slide 20
- 20 Kinetics vs. Thermodynamics (really the same thing) Reaction
coordinate Energy Diamond Graphite
- Slide 21
- 21 EaEaEaEa Reaction coordinate Energy Diamond Graphite
Intermediates/Transition states EaEaEaEa
- Slide 22
- 22 k =Ae -Ea/RT Arrhenius Equation Critical assumption is that
E a is CONSTANT Ass-u-me Assume
- Slide 23
- 23 Time-Temperature Superposition If same mechanism: same shape
(log graph) same shape (log graph) should be constant acceleration
(multiple) should be constant acceleration (multiple) Plot log(a T
) vs 1/T linear if Arrhenius Does mechanism change as a function of
temperature? 1.Pick a reference temperature 2.Multiply the time at
each temperature by the constant that gives the best overlap with
the reference temperature data 3.Define that multiple as a T (a T =
1 for ref. temp.) 4.Find a T for each temperature k =Ae -Ea/RT
ln(k) = ln(A) Ea/RT Empirical equation Arrhenius equation: Gillen,
K. T.; Celina, M.; Clough, R. L.; Wise, J. Trends in Polymer
Science, Extrapolation of Accelerated Aging Data -Arrhenius or
Erroneous? 1997, 5, 250-257.
- Slide 24
- 24 Thermal-oxidative Aging: Nylon 2000 days ~ 5.5 years
Bernstein, R.; Gillen, K. T. Polymer Degradation and Stability,
Nylon 6.6 accelerating aging studies: II. Long- term
thermal-oxidative and hydrolysis results 2010, 95, 1471-1479.
- Slide 25
- 25 Thermal-oxidative Aging: Nylon Shifted Data Bernstein, R.;
Gillen, K. T. Polymer Degradation and Stability, Nylon 6.6
accelerating aging studies: II. Long-term thermal-oxidative and
hydrolysis results 2010, 95, 1471-1479.
- Slide 26
- 26 Thermal-oxidative Aging: Nylon Shift Factor Graph Bernstein,
R.; Gillen, K. T. Polymer Degradation and Stability, Nylon 6.6
accelerating aging studies: II. Long-term thermal-oxidative and
hydrolysis results 2010, 95, 1471-1479.
- Slide 27
- 27 Thermal Exposure Polymer O2O2O2O2 Oxidized Polymer +
Thermal-Oxidation Quantify amount of oxygen consumed Simple in
theorySimple in theory Difficult in practiceDifficult in practice
Amazingly sensitiveAmazingly sensitive
- Slide 28
- 28 Schematic of Oxuptake Initial Pressure of O 2 O2O2O2O2
O2O2O2O2 O2O2O2O2 O2O2O2O2 O2O2O2O2 O2O2O2O2 O2O2O2O2 O2O2O2O2
O2O2O2O2 O2O2O2O2 O2O2O2O2 O2O2O2O2 O2O2O2O2 + Time Polymer
Oxidized Polymer Final Pressure of O 2
- Slide 29
- 29 Oxygen Consumption
- Slide 30
- 30 Enhanced Extrapolation Good 1/Temperature, K -1 Normalized
Measured Property X X X X X X O O O O O O O O Shift Factor, a T
High Temp Low Temp X Measured Property O Oxygen Consumption X
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- 31 Enhanced Extrapolation: Bad 1/Temperature, K -1 Normalized
Measured Property X X X X X X O O O O O O O O Shift Factor, a T
High Temp Low Temp X X Measured Property O Oxygen Consumption
O
- Slide 32
- 32 Diffusion Limited Oxidation (DLO) effects if oxygen
dissolved in material used up faster by reaction than it can be
replenished by diffusion from surrounding air atmosphere Race
between: the oxygen consumption rate versus the oxygen diffusion
rate the oxygen consumption rate versus the oxygen diffusion rate
Therefore we need estimates of: 1.O 2 permeability versus aging
temperature 2.O 2 consumption versus aging temperature DLO, Need to
Know
- Slide 33
- 33 Diffusion-Limited Oxidation (DLO) O2O2O2O2 O2O2O2O2 O2O2O2O2
O2O2O2O2 O2O2O2O2 O2O2O2O2 O2O2O2O2 O2O2O2O2 O2O2O2O2 O2O2O2O2
O2O2O2O2 O2O2O2O2 HomogeneousHeterogeneous rxn rate > diffusion
rate rxn rate < diffusion rate
- Slide 34
- 34 Modulus Profiling Measure of Inverse tensile compliance
Closely related to tensile modulus Indentation technique ca. 50 m
resolution Excellent to examine geneity of aging (heteo- or homo-)
(DLO issues) Modulus vs. Shore A
- Slide 35
- 35 Schematic of Modulus Profile Experiment Mass is applied in
two stepsProbe tip, sample and mass Gillen, K. T.; Clough, R. L.;
Quintana, C. A. Polym. Degrad. Stab., Modulus profiling of polymers
1987, 17, 31-47
- Slide 36
- 36 Modulus Profiler
- Slide 37
- 37 Modulus Profiler Sample
- Slide 38
- 38 Aging of a nitrile rubber at temperatures ranging from 65C
to 125C ranging from 65 C to 125 C Modulus profiles of samples aged
at 65C indicate the presence of homogeneous aging Modulus profiles
of samples aged at 65 C indicate the presence of homogeneous aging
Homogeneous Aging Wise, J.; Gillen, K. T.; Clough, R. L. Polymer
Degradation and Stability, An ultrasensitive technique for testing
the Arrhenius extrapolation assumption for thermally aged
elastomers 1995, 49, 403-418.
- Slide 39
- 39 Modulus profiles for samples aged at 95C show that
diffusion-limited oxidation (DLO) is becoming important; at 125C,
DLO effects are very significant Heterogeneous Aging Wise, J.;
Gillen, K. T.; Clough, R. L. Polymer Degradation and Stability, An
ultrasensitive technique for testing the Arrhenius extrapolation
assumption for thermally aged elastomers 1995, 49, 403-418.
- Slide 40
- 40 Nylon: Tensile versus Oxygen Consumption
- Slide 41
- 41 Thermal-oxidative tensile: Prediction vs. Experimental
Arrhenius predictions severely off target suggest change in
mechanism/non- Arrhenius behavior Oxygen consumption suggests no
change in thermal-oxidative mechanism in thermal-oxidative
mechanism Possible explanation involving mechanism change? 64 C
Thermal-oxidative Initial data Predicted: 92% at ca. 3700 days
Observe: 92% at ca. 835 days Observe: 92% at ca. 835 days Arrhenius
Predictions
- Slide 42
- 42 Nylon 6.6 n 1,6 -Hexanediamine Adipic Acid + H2OH2OH2OH2O
Nylon Structure
- Slide 43
- 43 Humidity Aging Schematic Time, O2O2O2O2 O2O2O2O2 O2O2O2O2
O2O2O2O2 O2O2O2O2 O2O2O2O2 O2O2O2O2 O2O2O2O2 O2O2O2O2 H2OH2O H2OH2O
H2OH2O H2OH2O H2OH2O H2OH2O O2O2O2O2 O2O2O2O2 O2O2O2O2 O2O2O2O2
O2O2O2O2 O2O2O2O2 H2OH2O H2OH2O H2OH2O H2OH2O H2OH2O H2OH2O H2OH2O
H2OH2O
- Slide 44
- 44 Humidity Aging Hardware
- Slide 45
- 45 Organic Materials Aging and Degradation Specifics -o-rings
General path most organic materials This talk details not important
(all published)
- Slide 46
- 46 O-ring Published Documentation Gillen, K. T.; Celina, M.;
Bernstein, R. In Polymer Degradation and Stability Validation of
Improved Methods for Predicting Long-Term Elastomeric Seal
Lifetimes from Compression Stress-Relaxation and Oxygen Consumption
Techniques, 2003; Vol. 82, pp 25-35. Gillen, K. T.; Bernstein, R.;
Wilson, M. H. Polymer Degradation and Stability, Predicting and
Confirming the Lifetime of O-rings 2005, 87, 257-270. Chavez, S.
L.; Domeier, L. A. "Laboratory Component Test Program (LCTP),
Stockpile O-Rings," BB1A3964, 2004. Bernstein, R.; Gillen, K. T.
"Fluorosilicone and Silicone O-Ring Aging Study," SAND2007-6781,
Sandia National Laboratories, 2007. Bernstein, R.; Gillen, K. T.
Polymer Degradation and Stability, Predicting the Lifetime of
Fluorosilicone O-rings 2009, 94, 2107-2133.
- Slide 47
- 47 O-rings Background Used as environmental seals or other
seals O-RING CROSS-SECTIONS UNAGED15 yr in field Most systems
filled with inert gas to protect interior components from oxidation
& hydrolysis Previously: No technique to measure equilibrium
sealing force No technique to rapidly achieve equilibrium
compression set No correlation
- Slide 48
- 48 CSR Jigs Gap of jig can be adjusted to any desired size
O-ring pieces cut to allow air circulation Measurement of force
involves very slow and slight compression until electrical contact
is broken between the top and bottom plates Jigs can be placed in
ovens, thus providing isothermal measurements
- Slide 49
- 49 Compression Stress Relaxation (CSR) Shawbury-Wallace
Compression Stress Relaxometer (CSR) MK II (Wallace Test Equipment,
Cryodon, England) Commercial Instrument Measure of Force -O-ring
sealing force Can Adjust Gap Size to Approximate Actual Compression
in System
- Slide 50
- 50 Accelerated aging 1) Physical force decay -Equilibrium
values achieved starting point -Ability to get field returned
o-ring force ending point 2) Chemical force decay Prediction of
force changes as a function of aging
- Slide 51
- 51 Why we do isothermal measurements Sealing force per unit
length versus time out of a 110 C oven for two CSR jigs containing
Butyl-A o-ring segments that had aged under 25% compression until
the force degraded by ~42% (top curve) and ~72% (bottom curve),
respectively. ~2 hrs Gillen, K. T.; Celina, M.; Bernstein, R. In
Polymer Degradation and Stability Validation of Improved Methods
for Predicting Long-Term Elastomeric Seal Lifetimes from
Compression Stress- Relaxation and Oxygen Consumption Techniques,
2003; Vol. 82, pp 25-35.
- Slide 52
- 52 All Jigs at Temperatures -Fluorosilicone Bernstein, R.;
Gillen, K. T. "Fluorosilicone and Silicone O-Ring Aging Study,"
SAND2007-6781, Sandia National Laboratories, 2007. Bernstein, R.;
Gillen, K. T. Polymer Degradation and Stability, Predicting the
Lifetime of Fluorosilicone O-rings 2009, 94, 2107-2133.
- Slide 53
- 53 Time-Temperature Superposition If same mechanism: same shape
(log graph) same shape (log graph) should be constant acceleration
(multiple) should be constant acceleration (multiple) Plot log(a T
) vs 1/T linear if Arrhenius Does mechanism change as a function of
temperature? 1.Pick a reference temperature 2.Multiply the time at
each temperature by the constant that gives the best overlap with
the reference temperature data 3.Define that multiple as a T (a T =
1 for ref. temp.) 4.Find a T for each temperature k =Ae -Ea/RT
ln(k) = ln(A) Ea/RT Empirical equation Arrhenius equation: Gillen,
K. T.; Celina, M.; Clough, R. L.; Wise, J. Trends in Polymer
Science, Extrapolation of Accelerated Aging Data -Arrhenius or
Erroneous? 1997, 5, 250-257.
- Slide 54
- 54 Time-Temperature Superposition
- Slide 55
- 55 Shift Factor Plot
- Slide 56
- 56 Accelerated Aging Temperature Reaction Coordinate
- Slide 57
- 57 Shift Factor Plot
- Slide 58
- 58 Shifted Data with RT Prediction w/o 80 C data
- Slide 59
- 59 Shift Factor Plot
- Slide 60
- 60 Shifted Data with RT Prediction All data
- Slide 61
- 61 Shift Factor Plot
- Slide 62
- 62 Shifted Data with RT Prediction 109 and 80 only
- Slide 63
- 63 Shift Factor Plot ~50% in ~ 1000 years ~50% in ~ 100 years
~50% in ~ 20 years
- Slide 64
- 64 O-ring Sealing force arguably most important parameter
compression set Easy to measure quick and simple Difficult to
measure slow and laborious sealing force Correlation between
equilibrium values O-RING CROSS-SECTIONS UNAGED15 yr in field
- Slide 65
- 65 Force versus Compression Set Data -Fluorosilicone
- Slide 66
- 66 Field Data* * not quite the whole story, but good enough for
this conversation! Compression set measurements of three
fluorosilicone o-rings taken on surveillance units approximately 1
day after removal from the unit. The solid curve and the dashed
curve assume a linear relationship between set and force decay.
Bernstein, R.; Gillen, K. T. Polymer Degradation and Stability,
Predicting the Lifetime of Fluorosilicone O-rings 2009, 94,
2107-2133 Aging time, years
- Slide 67
- 67 Other Compression Set Data Different Silicone Different
Program Different PI Gillen, K. T. "Silicone seal analysis,"
Internal Memo, SNL, 2001.
- Slide 68
- 68 Compression Set Data Analyzed by Gillen Added in 40 year RT
data from another source Gillen, K. T. "Silicone seal analysis,"
Internal Memo, SNL, 2001.
- Slide 69
- 69 Arrhenius Plot for Compression Set Arrhenius plot of the
shift factors for silicone compression set which leads to an aging
room temperature prediction for compression set Gillen, K. T.
"Silicone seal analysis," Internal Memo, SNL, 2001.
- Slide 70
- 70 Force versus Compression Set Data
- Slide 71
- 71 Force versus Compression Set Data Correlation between
current Silicone Force data and Compression set data obtained from
three different sources (and different sizes!) Fluorosilicone
versus Silicone!! Displays confidence in generalized predictions
about silicone o-rings state of health (CS easy to measure) under
oxidative environments*
- Slide 72
- 72 Butyl Force vs. Compression set; lab and field aged
Equilibrium values of compression set plotted versus F/F 0 for
laboratory- aged o-rings for three butyl materials plus field
results for Butyl-B plotted assuming that F 0 = 10 N/cm. Gillen, K.
T.; Bernstein, R.; Wilson, M. H. Polymer Degradation and Stability,
Predicting and Confirming the Lifetime of O-Rings 2005, 87,
257-270.
- Slide 73
- 73 Heavily Filled Silicone Conducting o-rings compression set
versus force remaining
- Slide 74
- 74 SIGYY -191 psi=133 N/cm 2 -89 psi= 61 N/cm 2 13 psi= 9 N/cm
2 Time = 0 Time =.5sec Time =.8sec Time = 1sec Time = 30 years Time
= 56 year Time 90 years Slide Courtesy of David Lo Progression of
Stress Relaxation due to Chemical Aging
- Slide 75
- 75 Take home messages 1)Be aware of mechanism changes
2)Understand chemistry/be careful with the details DLO, O 2 vs. H 2
O etc 1)Find something to measure 2)Do things at many temp (as far
apart as possible) 3)Do things for very very long time 4)Validate
against real world 5)It would be nice to know your performance
requirements
- Slide 76
- 76 Lots of help Dora Derzon, Brad Hance, Don Bradley, Roger
Assink, James Hochrein, Steven Thornberg, David Lo, Kathy Alam,
Laura Martin, John Schroeder, Patti Sawyer, Mark Stavig, and Ken
Gillen
- Slide 77
- 77 Questions