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Kinetic Data for Polymers
Sergey Vyazovkin
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Bulk kinetics Polymers are materials
Processes of interest: Thermal and oxidative degradation Molding (thermoplastics) Reactive injection molding (thermosets) Fire resistance Methods: DSC (heat release kinetics) TGA (mass loss kinetics)
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Importance of TGA and DSC
ISI Web of Science ®: DSC and polymer - 3,900 TGA and polymer – 1,200 FTIR and polymer – 2,900
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Application to particular processes
DSC and crystallization and kinetics – 820 Microscopy and crystallization and kinetics – 810 DSC and curing/cure and kinetics FTIR and curing/cure and kinetics - 247 TGA and polymer and degradation/decomposition – 420 FTIR and polymer and degradation/decomposition – 540
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Kinetics by TGA and DSC
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Typical kinetic approach
Single-step treatment preferred over multiple-step Nonisothermal conditions preferred over isothermal Single heating rate data analysis preferred over multiple heating programs
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Single step rate equation
k(T) – rate constant f() – reaction model
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Arrhenius equation (1889) Svante Arrhenius
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Single step rate equation
“Kinetic triplet”: E – activation energy A – preexponential factor f() – reaction model, f()= (1-)n
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Transition state theory
ORIGINAL Henry Eyring E activation energy
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Transition state theory
Henry Eyring 1. no medium (gas phase) 2. single-step reaction
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Multiple reactions
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Diffusion
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Condensed phase Reactions occur in the solid or liquid medium
Medium affects the temperature dependence of the rate Experimental E involves physical properties of the medium
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Single heating rate data analysis
Coats-Redfern method (1964): ~2000 citations! TGA or DSC at 1 heating rate vs T data fit to different g() models
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Compensation effect Large uncertainty in E and lnA!
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Compensation effect, lnA=aE+b
Decomposition of HMX T.B. Brill et al J. Phys. Chem. 1994, 98, 12242
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Solid state reaction models
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HMX: Kinetic triplets by Coats-Redfern method
Best fits
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Practical purpose: predictions
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HMX: Predictions
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Thermal degradation of PMMA
Atmosphere Step 1 E / kJ mol-1 Step 2 Step 3 Experiment Reference vacuum 130 – 176 Isothermal manometry 1, 2 138 Isothermal TGA 3 242 117 5 N2 150 – 250 Nonisothermal TGA 8 210 9 154 133 11 12 31 224 233 104 Isothermal heating 13 113 15 130 – 180 16 [1] Single E values are listed under Step 1 regardless of the number of steps reported [2] E increases with [3] Not reported
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Thermal degradation of PP
Atmosphere E / kJ mol-1 Method Ref N2 244 Nonisothermal TGA 10 216 isothermal TGA 11 214 18 160 22 115 – 200 19 130 – 200 23 230 Factor-jump TGA Vacuum 257 Ar 98, 328 25
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ICTAC Kinetics Project
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ICTAC Kinetics Project
Thermochim. Acta 355(2000)125 Single heating rate methods should be avoided Use multiple heating rate methods instead Importance of detecting complex processes
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“Model-free” kinetics
Rate equation Log derivative
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“Model-free” kinetics
Isoconversional principle Uses multiple heating rates Yields a model-free estimate E
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Isoconversional method
E varies with multi-step process
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Thermal degradation of PP
Atmosphere E / kJ mol-1 N2 244 216 214 160 115 – 200 130 – 200 230 Vacuum 257 Ar 98, 328
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Epoxy-amine cure: Variation of Eα with α
Decrease in Eα suggests a shift from kinetic to diffusion control that usually associated with vitrification.
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TTT cure diagram In the glassy state molecular motion is largely reduced
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Detecting vitrification by temperature modulated DSC
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Epoxy-amine cure: Variation of Eα with α
70 2.68 -1 60 -1 K / kJ mol 2.64 -1 / J g E a Vitrification 50 * 2.60 C p 40 2.56 0.2 0.4 0.6 0.8 1.0 a Epoxy-amine cure: Variation of Eα with α Decrease in Eα is actually caused by vitrification
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Melt crystallization kinetics
Poly(ethylene terephthalate) Aldrich, MW ~18,000, Tm=280oC Cooled from 290 to 25C β = -3, -4, -6, -8, -12C/min
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Temperature dependence of growth rate
Hoffman-Lauritzen theory:
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Evaluating Kg and U* E vs E vs T:
I: Kg= K2 , U*=4300 J/mol II: Kg= K2 , U*=2300 J/mol Macromol. Rapid Commun. 2004, 25, 733
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Model-free predictions
Assuming that kinetic triplet (E, A, reaction model) at a given does not change when changing T
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Model-free predictions
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Model-free predictions, HMX
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Model-free predictions, shelf-life
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Model-free predictions, shelf-life
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Model-based methods Model-based methods that use multiple heating programs are being developed By far less common than model-free methods
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Model-based Model-free
Model-based and model-free methods are interrelated via E dependence
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Conclusions E dependence can generally be interpreted as a function of the activation energies of individual steps E is useful in exploring reaction mechanisms The model-free approach requires only E for kinetic predictions E dependence provides a link to model-based methods Model-free approach can serve as a uniform framework for creating a database of bulk polymer (and solid-state) kinetics of thermal reactions
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“The 16 questions” (polymers and solid-state)
3) nonisothermal data important 4) include overall or both (overall and elementary) reactions 7) complex reactions unavoidable 8) cannot be limited to single dif. Eq. 9) the database should include: D) solid-state reactions H) macromolecular reactions I) polymerization reactions
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“The 16 questions” (polymers and solid-state)
11) long term success via agreements w/journals 13) critical assessment is important
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ThermoML
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ThermoML @ J. Chem. Eng. Data
ThermoML is an XML-based format for the exchange and storage of thermophysical property data Authors download and use the GDC software to capture the experimental property data that has been accepted for publication. The output of the GDC Software converted into ThermoML format at TRC Upon release of the manuscript the ThermoML files are posted on the public-domain TRC Web site
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“KineticML” @ Thermochim. Acta?
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